Geochemical result of the analysis soil samples.
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Traditional exploration geochemistry usually employs earth materials such as rock, stream sediment and soil to detect unusual concentration of elements that may serve as pathfinder for concealed ore body [1, 2, 3]. The distribution of pathfinder elements in these media especially stream sediment and soil is governed by weathering and hydromorphic conditions of the area under investigation in addition to the mobility of such elements. Despite their dispersion, trace and rare earth elements still retain their bedrock characteristics. These elements are adsorbed unto surfaces of weathered products and possess the ability to remain on the surfaces of these weathered particles for long periods unless they are mobilized by decomposition processes such as redox conditions [4]. Bowen [5] believes that the residence time of these elements in temperate soils is not the same. For example, the residence time of Pb is between 740 and 5900 years, Zn has a residence time of 70–510 years, 13–1100 years is the residence time for Cd, and 310–1500 years is the residence time for Cu, while the residence time in tropical soils is 40 years due to the shorter rate of leaching. Soil geochemical surveys have proven to be highly effective with long and impressive history of discovering blind deposits [6].
Akilolu [7] reports the gossan manganite occurrences in Buya and Derena area, northwestern Nigeria. He groups these ores into three which are Buya, Derena north and Derena south clusters. In his paper, he argues that the Buya gossans are purer than other clusters. Bamigboye et al. [8] report goethite mineralization in addition to the manganite mineralizations reported by Akilolu [7] in Kaoje, northwestern Nigeria. Furthermore, an exposure of brown laminated manganite ore, south of Barkin-Ruwa, was also reported to earlier reported manganite clusters in these areas. This exposure is relatively unique in terms of its brown colouration as against the black colour of those in Buya and Derena clusters. The report of Akilolu [7] and Bamigboye et al. [8] did, however, not give account of the distribution of trace and rare earth elements in the soil in Kaoje and its environs, neither is vivid account given on the possibility of discovering concealed bodies of these ores or others within Kaoje and its environs. Other work related to this include the work of Adekoya [9], Mucke [10], Okorie et al. [11, 12] and Fillie [13, 14], among others. This work is therefore aimed at identifying the mineralized zones in Kaoje and its environs using geochemical signatures in soils around Kaoje and its environs, northwestern Nigeria. The study area is bounded by Long. 3°55′ and 4°10′E and Lat. 11°00′ and 11°15′N covering an approximate area of 676 km2.
The geology of the area can grossly be divided into the basement complex rock and sedimentary rocks. The basement complex rocks are mainly banded gneiss, migmatite, granite gneiss, quartz-mica schist and granite (Figure 1).
Geological map of Kaoje and its environs with insect of map of Nigeria and Africa.
The banded gneiss occurs as elongated rock body within the schist and is seen about 2 km south-west of Buya and midway between Idowa and Derena. The banded gneisses are rich in quartz with pervasive jointing, filled by quartz and quartzofeldspathic vein in most cases. Migmatite trends in SE-NW direction mainly. The granite gneisses have a sharp contact with the mica schist. Mineralogically, quartz, biotite and sodic feldspar predominate, but crystals of tourmaline are seen in some localities. The quartz-mica schist is extensively weathered and covers about one-fifth of the area studied. It occurs as a low-lying exposure and stream-cut exposure. Some of the schists occur as xenolith with a large pegmatitic body close to Barkin-Ruwa, along Barkin-Ruwa-Buya road.
The granitic bodies occur towards the southern part of the study area. The granitic rocks occur as boulders and cobbles of rocks and are closely associated with weathered schist in the southernmost part of the area. The pegmatitic rocks in this area are seen associated with the schist and migmatite mainly. Some of the pegmatites are also seen at the contact between the schist and the sedimentary rock in the northwestern area. Mineralogically, the pegmatites are made up of quartz, biotite, k-feldspar tourmaline (in the southeastern part) and chalcedony (in the northwestern part).
Sedimentary rocks in this area occupy about 60% of the area. This rock includes the Biongbe, Morongba and Koremi hills. These hills are essentially clastic sedimentary rocks that include the sandstone and silty sandstone. In the northeastern part of Kaoje, sedimentary rocks occur as remnant of gully eroded sedimentary rocks. These rocks are finely laminated with characteristic ichnofossil. Other characteristic of these rocks are their semi-consolidated nature that is typical of Taloka Formation in the Sokoto Basin. The rocks in this area include silty sandstones that are finely laminated, while some are massive. Other sedimentary rock types seen associated with the sandstone are goethite, kaolinitic mudstone, finely laminated siltstones and kaolinitic purple claystone. All these are exposed along Kaoje-Idowa road and towards the edge of the area studied in the northeastern part.
The iron ore occur as vein, boulders and sedimentary capping in the northeast and southeast mainly. It shows conspicuous alternating bands of iron and chert-rich layers in most of the location, while few are massive iron ore with little or no cherty contents. Bamigboye et al. [8] describe these irons to be of hydrothermal origin but now remobilized. Manganite gossans occur as boudins in an almost NE-SW direction from Buya through Derena to the eastern part of Barkin-Ruwa. These ores occur as black laminated exposures mainly around the Buya-Derena axis and as brown folded brown laminated body south of Barkin-Ruwa. Mn is associated with quartz veins. From the work of Bamigboye et al. [8], the iron ores are made up of feroxhyte, gibbsite, goethite, maghemite, magnetite and haematite essentially with subordinate manganite, while the manganites are composed of manganite, gibbsite, magnetite, bayerite, akaganeite and nordstrandite among others.
The methods adopted in this work are grossly divided into two. These are fieldwork and laboratory work. The fieldwork was carried out between 2011 and 2012. During this period, rock and soil samples were taken. The soil samples were taken from a grid of 1 km × 1 km from a depth range of 30–50 cm corresponding to the B-horizon as recommended by Vareikiene and Lehtonen [15]. Thirty soil samples were prepared and subjected to geochemical analysis at ACME Analytical laboratory, Vancouver, Canada. In the laboratory, 0.5 g of the soil samples were digested with a modified aqua regia solution of equal parts concentrated HCl, HNO3 and DI H2O for 1 h in a heating block. The resulting solution was thereafter analysed by ICP-ES and ICP-MS for trace and rare earth elemental concentration. The selected elements that were considered related to iron and manganite mineralization from the geochemical data was correlated. Others were subjected to principal component statistical analysis (PCSA) using the SPSS software, while isograde plotting of the data was done using Surfer 12.
The result of the geochemical analysis where the concentration of 53 elements was determined is shown in Table 1. From the result, sample 83a and 86 had the highest concentration of most of the elements, while sample 64 and 222 had the lowest concentration of most of the elements. S had a constant value of <0.02 except in sample 83a where the value is 0.02%. This same sample had 0.05 ppm concentration of W as against <0.05 in the remaining samples. This is equally similar to the slight higher concentration of 0.02 ppm concentration of Se as against <0.1 in other samples.
Sample no. | Cd (ppm) | Sb (ppm) | Bi (ppm) | V (ppm) | Ca (%) | P (%) | La (ppm) | Cr (ppm) | Mg (%) | Ba (ppm) | Ti (%) | B (ppm) | Al (%) | Na (%) | K (%) | W (ppm) | Sc (ppm) | Tl (ppm) | S (%) | Hg (ppb) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10 | <0.01 | 0.04 | 0.06 | 17 | 0.02 | 0.006 | 9.4 | 9.0 | 0.02 | 18.7 | 0.009 | <20 | 0.43 | <0.001 | 0.03 | <0.05 | 2.3 | 0.05 | <0.02 | 11 |
18 | 0.02 | 0.05 | 0.05 | 22 | 0.15 | 0.009 | 15.8 | 15.1 | 0.03 | 42.4 | 0.019 | <20 | 0.41 | <0.001 | 0.03 | <0.05 | 2.4 | 0.04 | <0.02 | 30 |
33 | <0.01 | 0.04 | 0.05 | 14 | 0.02 | 0.004 | 8.9 | 11.3 | 0.02 | 14.5 | 0.021 | <20 | 0.23 | <0.001 | 0.01 | <0.05 | 1.6 | 0.03 | <0.02 | 6 |
44 | <0.01 | <0.02 | 0.11 | 20 | 0.03 | 0.006 | 12.4 | 12.5 | 0.07 | 40.3 | 0.018 | <20 | 0.45 | 0.002 | 0.08 | <0.05 | 2.1 | 0.11 | <0.02 | 9 |
60 | <0.01 | 0.06 | 0.07 | 45 | 0.08 | 0.011 | 13.4 | 20.8 | 0.03 | 50.8 | 0.008 | <20 | 0.49 | <0.001 | 0.03 | <0.05 | 2.3 | 0.07 | <0.02 | 14 |
64 | <0.01 | <0.02 | 0.02 | 10 | 0.03 | 0.004 | 7.1 | 6.0 | 0.02 | 42.4 | 0.004 | <20 | 0.14 | <0.001 | 0.02 | <0.05 | 1.0 | 0.03 | <0.02 | 8 |
73 | <0.01 | 0.02 | 0.04 | 13 | 0.03 | 0.005 | 7.3 | 8.1 | 0.02 | 33.4 | 0.008 | <20 | 0.25 | <0.001 | 0.02 | <0.05 | 1.3 | 0.04 | <0.02 | 7 |
76 | 0.01 | 0.03 | 0.05 | 33 | 0.01 | 0.010 | 10.9 | 21.3 | 0.02 | 15.1 | 0.014 | <20 | 0.69 | <0.001 | 0.01 | <0.05 | 5.2 | 0.04 | <0.02 | 14 |
78 | <0.01 | 0.03 | 0.05 | 21 | 0.06 | 0.008 | 16.1 | 14.2 | 0.02 | 19.1 | 0.012 | <20 | 0.47 | <0.001 | 0.02 | <0.05 | 2.7 | 0.03 | <0.02 | 19 |
83a | 0.02 | <0.02 | 0.15 | 19 | 0.74 | 0.020 | 24.4 | 10.7 | 0.24 | 135.9 | 0.068 | <20 | 1.55 | 0.003 | 0.42 | 0.05 | 2.0 | 0.33 | 0.02 | 17 |
86 | 0.01 | <0.02 | 0.22 | 59 | 0.13 | 0.011 | 24.2 | 44.8 | 0.50 | 144.3 | 0.096 | <20 | 1.98 | 0.003 | 0.51 | <0.05 | 6.9 | 0.29 | <0.02 | 11 |
112 | <0.01 | 0.05 | 0.05 | 26 | 0.05 | 0.008 | 14.8 | 17.5 | 0.02 | 26.5 | 0.023 | <20 | 0.38 | <0.001 | 0.02 | <0.05 | 3.2 | 0.04 | <0.02 | 23 |
122 | <0.01 | 0.07 | 0.11 | 73 | <0.01 | 0.010 | 21.0 | 24.7 | 0.01 | 9.1 | 0.024 | <20 | 1.07 | <0.001 | 0.02 | <0.05 | 7.8 | 0.07 | <0.02 | 23 |
128 | <0.01 | 0.04 | 0.05 | 45 | 0.07 | 0.011 | 14.1 | 21.2 | 0.02 | 45.0 | 0.015 | <20 | 0.55 | <0.001 | 0.03 | <0.05 | 3.4 | 0.03 | <0.02 | 15 |
135 | <0.01 | 0.05 | 0.09 | 39 | 0.02 | 0.008 | 15.4 | 19.1 | 0.03 | 14.6 | 0.022 | <20 | 0.74 | <0.001 | 0.03 | <0.05 | 5.4 | 0.06 | <0.02 | 15 |
151 | 0.01 | 0.04 | 0.06 | 25 | 0.14 | 0.009 | 17.4 | 11.2 | 0.04 | 86.3 | 0.009 | <20 | 0.42 | <0.001 | 0.05 | <0.05 | 2.4 | 0.06 | <0.02 | 28 |
187 | 0.02 | 0.04 | 0.03 | 18 | 0.05 | 0.006 | 12.5 | 14.3 | 0.02 | 30.8 | 0.019 | <20 | 0.25 | <0.001 | 0.02 | <0.05 | 2.1 | 0.03 | <0.02 | 34 |
190 | <0.01 | 0.04 | 0.05 | 23 | 0.03 | 0.007 | 12.2 | 17.0 | 0.02 | 18.7 | 0.027 | <20 | 0.44 | <0.001 | 0.02 | <0.05 | 3.0 | 0.04 | <0.02 | 28 |
194 | <0.01 | 0.05 | 0.08 | 43 | <0.01 | 0.011 | 11.0 | 19.6 | 0.01 | 7.4 | 0.013 | <20 | 0.87 | <0.001 | 0.02 | <0.05 | 5.3 | 0.05 | <0.02 | 16 |
199 | <0.01 | 0.05 | 0.06 | 24 | 0.11 | 0.011 | 17.8 | 18.8 | 0.03 | 17.4 | 0.024 | <20 | 0.46 | <0.001 | 0.04 | <0.05 | 3.0 | 0.05 | <0.02 | 29 |
214 | <0.01 | <0.02 | 0.06 | 17 | 0.26 | 0.007 | 20.0 | 9.5 | 0.11 | 154.3 | 0.009 | <20 | 0.53 | 0.001 | 0.08 | <0.05 | 3.1 | 0.10 | <0.02 | 22 |
217a | <0.01 | <0.02 | 0.04 | 14 | 0.09 | 0.006 | 14.4 | 10.1 | 0.04 | 40.0 | 0.005 | <20 | 0.38 | <0.001 | 0.03 | <0.05 | 1.7 | 0.05 | <0.02 | 21 |
219 | 0.02 | 0.05 | 0.07 | 40 | 0.15 | 0.010 | 21.6 | 13.9 | 0.06 | 259.8 | 0.012 | <20 | 0.46 | 0.003 | 0.03 | <0.05 | 2.9 | 0.16 | <0.02 | 13 |
222 | <0.01 | <0.02 | 0.02 | 6 | 0.04 | 0.003 | 8.5 | 5.8 | 0.02 | 28.8 | 0.005 | <20 | 0.17 | 0.002 | 0.02 | <0.05 | 1.5 | 0.03 | <0.02 | 8 |
225 | <0.01 | <0.02 | 0.08 | 24 | 0.11 | 0.007 | 17.3 | 15.2 | 0.08 | 59.2 | 0.004 | <20 | 0.76 | <0.001 | 0.07 | <0.05 | 3.7 | 0.13 | <0.02 | 13 |
244 | <0.01 | 0.05 | 0.07 | 36 | 0.04 | 0.011 | 14.9 | 14.9 | 0.03 | 27.4 | 0.025 | <20 | 0.56 | 0.001 | 0.03 | <0.05 | 3.5 | 0.06 | <0.02 | 20 |
258 | 0.02 | 0.03 | 0.06 | 18 | 0.11 | 0.010 | 24.5 | 10.8 | 0.07 | 190.6 | 0.008 | <20 | 0.43 | 0.001 | 0.06 | <0.05 | 2.6 | 0.06 | <0.02 | 27 |
261 | 0.02 | 0.04 | 0.07 | 29 | 0.09 | 0.009 | 22.9 | 11.6 | 0.04 | 68.9 | 0.010 | <20 | 0.47 | <0.001 | 0.04 | <0.05 | 2.9 | 0.06 | <0.02 | 25 |
266 | 0.02 | 0.05 | 0.07 | 30 | 0.08 | 0.013 | 30.6 | 15.6 | 0.04 | 43.8 | 0.021 | <20 | 0.48 | <0.001 | 0.04 | <0.05 | 3.7 | 0.07 | <0.02 | 29 |
286 | 0.01 | 0.04 | 0.09 | 42 | 0.06 | 0.009 | 18.3 | 12.6 | 0.03 | 43.9 | 0.011 | <20 | 0.82 | <0.001 | 0.04 | <0.05 | 4.7 | 0.08 | <0.02 | 21 |
Sample no. | Se (ppm) | Te (ppm) | Ga (ppm) | Cs (ppm) | Ge (ppm) | Hf (ppm) | Nb (ppm) | Rb (ppm) | Sn (ppm) | Ta (ppm) | Zr (ppm) | Y (ppm) | Ce (ppm) | In (ppm) | In (ppm) | Re (ppb) | Be (ppm) | Li (ppm) | Pd (ppb) | Pt(ppb) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10 | <0.1 | <0.02 | 2.6 | 0.48 | <0.1 | <0.02 | 0.15 | 8.7 | 0.5 | <0.05 | 1.4 | 8.11 | 33.8 | 0.03 | 0.03 | <1 | 0.3 | 1.2 | <10 | <2 |
18 | <0.1 | <0.02 | 3.1 | 0.36 | <0.1 | 0.09 | 0.65 | 7.4 | 0.7 | <0.05 | 3.2 | 9.57 | 33.1 | 0.02 | 0.02 | <1 | 0.2 | 1.2 | <10 | <2 |
33 | <0.1 | <0.02 | 2.1 | 0.28 | <0.1 | 0.07 | 0.37 | 4.7 | 0.6 | <0.05 | 2.8 | 5.35 | 21.8 | <0.02 | <0.02 | <1 | 0.1 | 0.7 | <10 | <2 |
44 | <0.1 | <0.02 | 2.7 | 1.16 | <0.1 | <0.02 | 0.18 | 17.9 | 0.5 | <0.05 | 0.9 | 5.62 | 25.8 | 0.02 | 0.02 | <1 | 0.4 | 3.4 | <10 | <2 |
60 | <0.1 | <0.02 | 3.1 | 0.39 | <0.1 | 0.04 | 0.26 | 8.9 | 0.5 | <0.05 | 2.3 | 8.98 | 33.2 | <0.02 | <0.02 | <1 | 0.5 | 1.1 | <10 | <2 |
64 | <0.1 | <0.02 | 0.8 | 0.22 | <0.1 | <0.02 | 0.10 | 3.9 | 0.2 | <0.05 | 0.6 | 3.85 | 12.7 | <0.02 | <0.02 | <1 | 0.1 | 0.6 | <10 | <2 |
73 | <0.1 | <0.02 | 1.7 | 0.26 | <0.1 | <0.02 | 0.17 | 5.1 | 0.3 | <0.05 | 1.1 | 4.63 | 21.8 | <0.02 | <0.02 | <1 | 0.3 | 0.6 | <10 | <2 |
76 | <0.1 | <0.02 | 5.5 | 0.44 | <0.1 | 0.17 | 0.35 | 2.8 | 0.9 | <0.05 | 8.7 | 9.11 | 35.2 | 0.04 | 0.04 | <1 | 0.2 | 1.0 | <10 | <2 |
78 | <0.1 | <0.02 | 3.0 | 0.42 | <0.1 | 0.03 | 0.33 | 5.4 | 0.6 | <0.05 | 1.9 | 10.48 | 55.0 | <0.02 | <0.02 | <1 | 0.2 | 1.1 | <10 | <2 |
83a | 0.2 | <0.02 | 7.2 | 3.66 | <0.1 | 0.11 | 2.63 | 57.1 | 1.1 | <0.05 | 3.8 | 4.52 | 49.0 | <0.02 | <0.02 | <1 | 1.4 | 28.8 | <10 | <2 |
86 | <0.1 | 0.05 | 7.5 | 4.66 | <0.1 | 0.03 | 0.49 | 55.1 | 1.0 | <0.05 | 1.7 | 10.84 | 60.8 | 0.03 | 0.03 | <1 | 1.1 | 32.2 | <10 | <2 |
112 | <0.1 | <0.02 | 3.5 | 0.41 | <0.1 | 0.04 | 0.50 | 7.1 | 0.8 | <0.05 | 3.3 | 9.72 | 41.0 | 0.03 | 0.03 | <1 | 0.3 | 0.9 | <10 | <2 |
122 | <0.1 | <0.02 | 9.5 | 0.81 | <0.1 | 0.36 | 0.35 | 5.5 | 1.6 | <0.05 | 19.6 | 10.67 | 79.6 | 0.05 | 0.05 | <1 | 0.2 | 1.4 | 14 | <2 |
128 | <0.1 | <0.02 | 4.5 | 0.41 | <0.1 | 0.05 | 0.45 | 6.0 | 0.9 | <0.05 | 2.4 | 11.38 | 38.4 | <0.02 | <0.02 | <1 | 0.3 | 1.1 | <10 | <2 |
135 | <0.1 | <0.02 | 7.0 | 0.75 | <0.1 | 0.22 | 0.25 | 10.8 | 1.3 | <0.05 | 11.2 | 9.41 | 85.1 | 0.04 | 0.04 | <1 | 0.3 | 1.7 | <10 | <2 |
151 | <0.1 | <0.02 | 2.3 | 0.39 | <0.1 | 0.06 | 0.26 | 9.9 | 0.4 | <0.05 | 2.4 | 13.53 | 47.9 | 0.02 | 0.02 | <1 | 0.4 | 1.2 | <10 | <2 |
187 | <0.1 | <0.02 | 2.0 | 0.29 | <0.1 | 0.05 | 0.40 | 5.4 | 0.7 | <0.05 | 2.9 | 9.95 | 26.0 | <0.02 | <0.02 | <1 | 0.2 | 0.7 | <10 | <2 |
190 | <0.1 | <0.02 | 3.9 | 0.42 | <0.1 | 0.04 | 0.39 | 6.5 | 0.8 | <0.05 | 3.9 | 8.94 | 40.4 | 0.03 | 0.03 | <1 | 0.2 | 1.2 | <10 | <2 |
194 | <0.1 | <0.02 | 6.8 | 0.55 | <0.1 | 0.19 | 0.43 | 5.0 | 1.4 | <0.05 | 10.5 | 5.06 | 48.3 | 0.04 | 0.04 | <1 | 0.2 | 1.5 | <10 | <2 |
199 | <0.1 | <0.02 | 4.1 | 0.41 | <0.1 | 0.08 | 0.54 | 7.9 | 1.0 | <0.05 | 3.4 | 10.10 | 45.8 | <0.02 | <0.02 | <1 | 0.3 | 1.1 | <10 | <2 |
214 | <0.1 | <0.02 | 2.3 | 0.46 | <0.1 | 0.04 | 0.25 | 14.1 | 0.7 | <0.05 | 2.1 | 15.96 | 43.3 | <0.02 | <0.02 | <1 | 1.0 | 3.1 | <10 | <2 |
217a | <0.1 | 0.02 | 1.6 | 0.32 | <0.1 | <0.02 | 0.13 | 8.0 | 0.3 | <0.05 | 1.1 | 8.44 | 31.5 | <0.02 | <0.02 | <1 | 0.3 | 1.1 | <10 | <2 |
219 | <0.1 | <0.02 | 3.1 | 0.50 | <0.1 | 0.07 | 0.40 | 8.2 | 0.6 | <0.05 | 3.6 | 17.46 | 78.6 | 0.02 | 0.02 | <1 | 0.6 | 1.2 | <10 | <2 |
222 | <0.1 | <0.02 | 0.9 | 0.26 | <0.1 | <0.02 | 0.09 | 4.0 | 0.2 | <0.05 | 0.4 | 4.74 | 17.6 | <0.02 | <0.02 | <1 | 0.4 | 0.6 | <10 | <2 |
225 | <0.1 | <0.02 | 4.1 | 0.82 | <0.1 | 0.04 | 0.18 | 14.3 | 0.6 | <0.05 | 2.0 | 9.58 | 39.4 | <0.02 | <0.02 | <1 | 0.7 | 3.1 | <10 | <2 |
244 | <0.1 | 0.03 | 4.5 | 0.56 | <0.1 | 0.07 | 0.48 | 9.8 | 1.1 | <0.05 | 4.4 | 10.24 | 54.8 | <0.02 | <0.02 | <1 | 0.4 | 1.5 | <10 | <2 |
258 | <0.1 | <0.02 | 1.9 | 0.44 | <0.1 | 0.03 | 0.26 | 11.2 | 0.4 | <0.05 | 1.1 | 24.93 | 48.4 | <0.02 | <0.02 | <1 | 0.7 | 1.3 | <10 | <2 |
261 | <0.1 | <0.02 | 3.5 | 0.57 | <0.1 | 0.06 | 0.25 | 8.9 | 0.8 | <0.05 | 3.3 | 14.57 | 83.8 | <0.02 | <0.02 | <1 | 0.4 | 1.4 | <10 | <2 |
266 | <0.1 | <0.02 | 3.7 | 0.66 | <0.1 | 0.04 | 0.53 | 12.4 | 1.2 | <0.05 | 3.1 | 22.52 | 58.9 | <0.02 | <0.02 | <1 | 0.4 | 1.8 | <10 | <2 |
286 | <0.1 | <0.02 | 6.0 | 0.82 | <0.1 | 0.15 | 0.35 | 10.8 | 1.0 | <0.05 | 7.6 | 15.61 | 45.8 | 0.04 | 0.04 | <1 | 0.4 | 2.1 | <10 | <2 |
Geochemical result of the analysis soil samples.
The good correlation coefficient of Mn with Ni and Mg and the weak correlation especially between Mn and Cu are related to Mn-rich end member (Table 2). Similarly, good correlation coefficients between Fe and Ti and P coupled with the correlation between Co and Ti and the weak-to-low correlation between Ti and Ca, Ca and P, Ca and Co, and Ca and Fe are all related to Fe-rich end member. Likewise, the strong correlation between Al and K (r = 0.845) is related to aluminosilicate minerals, while the fairly good correlation coefficients between Mg and Mn and Cr and Ca are related to mantle-derived ultramafic materials.
Mo | Pb | Zn | Ni | Co | Mn | Fe | As | Th | Sr | Cd | Bi | V | Ca | P | Cr | Mg | Al | K | Sc | Cs | Nb | Rb | Sn | Zr | Ce | In | Be | Li | Pd | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mo | 1 | |||||||||||||||||||||||||||||
Pb | 0.610 | 1 | ||||||||||||||||||||||||||||
Zn | 0.499 | 0.332 | 1 | |||||||||||||||||||||||||||
Ni | 0.674 | 0.412 | 0.767 | 1 | ||||||||||||||||||||||||||
Co | 0.523 | 0.602 | 0.525 | 0.752 | 1 | |||||||||||||||||||||||||
Mn | 0.374 | 0.593 | 0.439 | 0.615 | 0.924 | 1 | ||||||||||||||||||||||||
Fe | 0.930 | 0.667 | 0.482 | 0.521 | 0.388 | 0.267 | 1 | |||||||||||||||||||||||
As | 0.827 | 0.506 | 0.693 | 0.605 | 0.352 | 0.240 | 0.854 | 1 | ||||||||||||||||||||||
Th | 0.634 | 0.564 | 0.091 | 0.090 | 0.043 | −0.050 | 0.755 | 0.537 | 1 | |||||||||||||||||||||
Sr | 0.031 | 0.284 | 0.758 | 0.310 | 0.256 | 0.317 | 0.100 | 0.341 | −0.106 | 1 | ||||||||||||||||||||
Cd | −0.094 | 0.427 | 0.202 | 0.052 | 0.311 | 0.407 | −0.013 | −0.034 | −0.095 | 0.469 | 1 | |||||||||||||||||||
Bi | 0.764 | 0.497 | 0.834 | 0.874 | 0.627 | 0.435 | 0.693 | 0.769 | 0.379 | 0.400 | 0.030 | 1 | ||||||||||||||||||
V | 0.911 | 0.666 | 0.244 | 0.455 | 0.378 | 0.248 | 0.926 | 0.718 | 0.739 | −0.127 | −0.113 | 0.581 | 1 | |||||||||||||||||
Ca | 0.037 | 0.222 | 0.768 | 0.277 | 0.198 | 0.238 | 0.115 | 0.378 | −0.074 | 0.987 | 0.425 | 0.403 | −0.132 | 1 | ||||||||||||||||
P | 0.502 | 0.576 | 0.676 | 0.373 | 0.354 | 0.321 | 0.603 | 0.664 | 0.382 | 0.653 | 0.398 | 0.558 | 0.454 | 0.659 | 1 | |||||||||||||||
Cr | 0.866 | 0.395 | 0.430 | 0.751 | 0.510 | 0.365 | 0.753 | 0.669 | 0.426 | −0.093 | −0.161 | 0.684 | 0.777 | −0.098 | 0.369 | 1 | ||||||||||||||
Mg | 0.516 | 0.287 | 0.856 | 0.950 | 0.671 | 0.537 | 0.381 | 0.557 | −0.066 | 0.502 | 0.086 | 0.840 | 0.258 | 0.480 | 0.380 | 0.598 | 1 | |||||||||||||
Al | 0.774 | 0.478 | 0.849 | 0.814 | 0.482 | 0.290 | 0.763 | 0.828 | 0.449 | 0.452 | 0.001 | 0.930 | 0.616 | 0.470 | 0.643 | 0.711 | 0.808 | 1 | ||||||||||||
K | 0.493 | 0.253 | 0.951 | 0.866 | 0.575 | 0.437 | 0.399 | 0.633 | −0.033 | 0.653 | 0.146 | 0.849 | 0.211 | 0.655 | 0.526 | 0.499 | 0.957 | 0.845 | 1 | |||||||||||
Sc | 0.808 | 0.534 | 0.270 | 0.487 | 0.272 | 0.120 | 0.856 | 0.605 | 0.799 | −0.164 | −0.186 | 0.592 | 0.864 | −0.164 | 0.348 | 0.766 | 0.309 | 0.680 | 0.242 | 1 | ||||||||||
Cs | 0.597 | 0.301 | 0.937 | 0.880 | 0.593 | 0.414 | 0.511 | 0.695 | 0.097 | 0.565 | 0.109 | 0.913 | 0.329 | 0.578 | 0.540 | 0.576 | 0.938 | 0.901 | 0.982 | 0.366 | 1 | |||||||||
Nb | 0.213 | 0.215 | 0.755 | 0.243 | 0.173 | 0.163 | 0.312 | 0.532 | 0.121 | 0.839 | 0.412 | 0.438 | 0.024 | 0.881 | 0.776 | 0.057 | 0.392 | 0.532 | 0.616 | −0.014 | 0.596 | 1 | ||||||||
Rb | 0.449 | 0.271 | 0.964 | 0.805 | 0.565 | 0.427 | 0.377 | 0.613 | −0.002 | 0.718 | 0.194 | 0.855 | 0.180 | 0.726 | 0.584 | 0.417 | 0.911 | 0.829 | 0.982 | 0.202 | 0.968 | 0.684 | 1 | |||||||
Sn | 0.676 | 0.505 | 0.324 | 0.264 | 0.189 | 0.090 | 0.810 | 0.643 | 0.860 | 0.055 | 0.046 | 0.496 | 0.719 | 0.090 | 0.602 | 0.554 | 0.134 | 0.587 | 0.194 | 0.798 | 0.310 | 0.362 | 0.221 | 1 | ||||||
Zr | 0.577 | 0.413 | 0.012 | −0.033 | −0.137 | −0.201 | 0.744 | 0.472 | 0.913 | −0.191 | −0.124 | 0.239 | 0.695 | −0.151 | 0.261 | 0.351 | −0.172 | 0.358 | −0.128 | 0.776 | 0.003 | 0.069 | −0.123 | 0.786 | 1 | |||||
Ce | 0.582 | 0.821 | 0.264 | 0.328 | 0.462 | 0.412 | 0.640 | 0.376 | 0.654 | 0.136 | 0.277 | 0.461 | 0.633 | 0.109 | 0.484 | 0.391 | 0.187 | 0.447 | 0.167 | 0.627 | 0.245 | 0.134 | 0.198 | 0.637 | 0.537 | 1 | ||||
In | 0.571 | 0.242 | 0.021 | 0.103 | −0.091 | −0.244 | 0.644 | 0.355 | 0.793 | −0.314 | −0.326 | 0.296 | 0.630 | −0.284 | 0.097 | 0.433 | −0.036 | 0.415 | −0.034 | 0.802 | 0.101 | −0.067 | −0.059 | 0.647 | 0.864 | 0.368 | 1 | |||
Be | 0.218 | 0.377 | 0.819 | 0.623 | 0.475 | 0.419 | 0.219 | 0.418 | −0.068 | 0.831 | 0.263 | 0.657 | 0.076 | 0.794 | 0.548 | 0.189 | 0.770 | 0.652 | 0.810 | 0.092 | 0.746 | 0.576 | 0.849 | 0.072 | −0.211 | 0.224 | −0.207 | 1 | ||
Li | 0.512 | 0.247 | 0.956 | 0.838 | 0.550 | 0.402 | 0.433 | 0.660 | 0.005 | 0.651 | 0.141 | 0.844 | 0.227 | 0.665 | 0.548 | 0.502 | 0.934 | 0.861 | 0.994 | 0.259 | 0.985 | 0.661 | 0.977 | 0.239 | −0.076 | 0.170 | 0.013 | 0.781 | 1 | |
Pd | 0.515 | 0.330 | 0.013 | 0.002 | −0.120 | −0.144 | 0.618 | 0.483 | 0.588 | −0.147 | −0.102 | 0.195 | 0.565 | −0.118 | 0.076 | 0.245 | −0.094 | 0.240 | −0.072 | 0.542 | 0.014 | −0.024 | −0.089 | 0.448 | 0.738 | 0.348 | 0.548 | −0.137 | −0.049 | 1 |
Result of correlation analysis of selected elements.
The result of the PCA shows a total of six factor groups (Table 3 and Figure 2). These are factors 1–6. Factor 1 with Mg, Ni, Cs, K, Te, Li, Ti, Rb, Bi, Al, Zn, Cu, Tl, U, Cr, Co, Na and Be accounts for a total of 43.59% before rotation and 31.86% after rotation. This is factor 2 with Zr, Hf, Th, Ga, In, Sc, Sn, Fe, V, Pd, Mo, Sb and As, and Ce accounts for 20.701% before rotation and 23.09% after rotation. Factor 3 has Se, Nb, Ca, Sr and P. This factor group accounts for 9.95% before rotation and 14.697% after rotation. Factor 4 with Ba, Pb, Y, Mn, La and Cd gave an account of 8.518% before rotation and 10.078% after rotation, while factor 5 with the following elements: Hg, Ag and Au account for 3.412% before rotation and 2.758% after rotation. Factor 6 does not have the highest loading of any element. Despite this, it still accounts for 2.658% before rotation and 3.106% after rotation.
Component | ||||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | |
Mg | 0.959 | |||||
Ni | 0.956 | |||||
Cs | 0.921 | 0.343 | ||||
K | 0.909 | 0.393 | ||||
Te | 0.900 | |||||
Li | 0.893 | 0.430 | ||||
Ti | 0.881 | |||||
Rb | 0.854 | 0.488 | ||||
Bi | 0.850 | 0.376 | ||||
Al | 0.812 | 0.481 | ||||
Zn | 0.795 | 0.563 | ||||
Cu | 0.770 | 0.354 | 0.319 | 0.315 | ||
Tl | 0.769 | 0.511 | ||||
U | 0.734 | 0.351 | 0.379 | |||
Cr | 0.711 | 0.476 | ||||
Co | 0.662 | 0.576 | 0.349 | |||
Na | 0.632 | 0.358 | 0.358 | −0.335 | ||
Be | 0.628 | 0.520 | 0.380 | |||
Zr | 0.969 | |||||
Hf | 0.948 | |||||
Th | 0.943 | |||||
Ga | 0.420 | 0.864 | ||||
In | 0.845 | |||||
Sc | 0.388 | 0.841 | ||||
Sn | 0.827 | |||||
Fe | 0.428 | 0.826 | ||||
V | 0.347 | 0.818 | ||||
Pd | 0.735 | |||||
Mo | 0.602 | 0.706 | ||||
Sb | −0.320 | 0.618 | 0.305 | 0.564 | ||
As | 0.584 | 0.608 | 0.313 | |||
Ce | 0.603 | 0.542 | ||||
Se | 0.942 | |||||
Nb | 0.307 | 0.914 | ||||
Ca | 0.311 | 0.903 | ||||
Sr | 0.318 | 0.862 | ||||
P | 0.350 | 0.367 | 0.629 | 0.361 | ||
Ba | 0.300 | 0.843 | ||||
Pb | 0.518 | 0.754 | ||||
Y | 0.737 | 0.569 | ||||
Mn | 0.483 | 0.663 | 0.443 | |||
La | 0.342 | 0.620 | 0.511 | |||
Cd | 0.455 | 0.521 | 0.381 | |||
Hg | 0.838 | |||||
Ag | −0.575 | |||||
Au | −0.500 |
Rotated component matrix.
3D component plot for soil factor analysis in rotated space.
Factor 1 of the principal component analysis of the soil was related to the weathering of the hydrothermal sulphide ore and silicate-rich banded iron formation [16, 17], while factor 2 was the product of weathered chert-rich magnetite and ores that are rich in terrigenous materials. The inclusion of elements, like Sn and Mo, indicates weathering of granitic rocks like pegmatite that had protore of some sulphide minerals [18]. The presence of Pd, Ce and Sb in this factor group attested to the presence of these minerals [16].
Factor 3 was related to the rocks and minerals such as phosphate REE-Nb deposits in an evaporite environment, while factor 4 was interpreted as the product of weathered manganese ore. Factor 5 was related to the weathered precious metals that were originally formed from hydrothermal sulphide ore [18]. Factor 6 had the second loading value of Mn, Sb and Co. This factor though not having the highest loading factor of any of the elements showed the weathering of Co-bearing manganese ore [19] and incompleteness or leakages in the system. These leakages typified by factor 6 were pronounced by the mobility of some of the elements. Factors 1–5 were strongly related to mineralization. The presence of the country rock in the factor groups as accounted for by the principal component analysis decreases from factor 1 to factor 5. Factor 6 does not have the highest loading of any element but had the second highest loading of Mn, Sb and Co. This factor group was interpreted to imply the presence of minor or protore of Co-bearing manganite and also accounts for very strong leakages in the system during weathering of the rocks and ores in the area.
The depressions in the isograde plots were interpreted to be the zones of negative anomaly, while the positive anomalous zones were the peaks in the plots. The brown-coloured area defines the regional threshold, while the pinkish sky blue-coloured zones on the plots were interpreted as the local aureole. Deep blue zones were interpreted as the anomalous regions. The values of these zones were estimated from the corresponding values in the colour scale that is beside each plot.
From the plots, Ag had three positive anomalies that are defined by long. 4.13°E and lat. 11.125°N, long. 4.0°E and lat. 11.075°N and long. 3.35°E and 11.1°N, while its negative anomalies were defined by long. 4.09°E and lat. 11.07°N, long 4.05°E and lat. 11.07°N and long. 4.075°E and long. 11.09°N. Its regional threshold was ≤55 ppm, while the local aureole and anomaly had 70 ppm and >90 ppm, respectively. The positive anomalies of Au were defined by long. 11.225°E and lat. 4.0°N, while its negative anomaly was defined by long. 4.05°E and lat. 11.1°N. Its regional aureole had ≤4ppb, while its local aureole is 5.5 ppb. Its anomalous area had a concentration value of ≥6.5 ppb. Ba had its positive anomaly on the spot defined by long. 3.975°E and lat. 11.13°N. Its regional threshold had a concentration value of ≤150 ppm, while its local threshold and anomalous values were 230 ppm and ≥240 ppm, respectively.
Al had its positive anomaly defined by long. 4.05°E and lat. 11.09°N, while the negative anomaly was defined by long. 3.92°E and lat. 11.09°N. Its regional aureole, local aureole and anomalous value were ≤1.2 ppm, 1.5 ppm and >1.6 ppm, respectively. As (Figure 3) had its positive anomalous zone defined by long. 4.05°E and lat. 11.1°N and long. 4.15°E and lat. 11.12°N. Its negative anomalies were defined by long. 4.075°E and lat. 11.075°N and long. 4.0°E and lat. 11.1°N. As had regional aureole, local aureole and anomaly with concentration values of ≤0.8 ppm, 1.0 ppm and ≥1.2 ppm, respectively.
3D isograde plot of As.
The positive anomalous zone of Be was defined by long. 4.06°E and lat. 11.12°N (Figure 4). Its negative anomaly was defined by long. 4.1°E and lat. 11.11°N. The concentration of Ba described as regional threshold is ≤0.8 ppm and its local and anomalous concentrations were 1.2 ppm and ≥1.3 ppm, respectively. The positive anomaly of Bi is on long. 4.04°E and lat. 11.075°N, while long. 3.93°E and lat. 11.1°N define the negative anomaly (Figure 5). The regional threshold, local threshold and anomaly values were ≤0.13 ppm, 0.18 ppm and ≥0.21 ppm, respectively. Ca has its positive anomaly defined by long. 4.04°E and lat. 11.075°N, while its negative anomaly is defined by long. 4.05°E and lat. 11.06°N. The regional threshold value of Ca is ≤0.45 ppm while its local aureole and anomalous values were 0.6 ppm and ≥0.65 ppm. Cd positive anomaly was on the spot defined by long. 4.075°E and lat. 11.1°N. Its regional threshold, local threshold and anomalous values were ≤0.013 ppm, 0.017 and ≥0.019 ppm, respectively.
3D isograde plot of Be.
3D isograde plot of Bi.
The positive anomaly of Co was defined by long. 4.04°E and lat. 11.05°N (Figure 6). Its negative anomaly was defined by long. 3.97°E and lat. 11.16°N, while its regional threshold, local aureole and anomalous values were ≤10 ppm, 14 ppm and ≥15 ppm, respectively. Cs has no negative anomaly but its positive anomalous point is defined by long. 4.04°E and lat. 11.06°N (Figure 7). Its regional threshold value was ≤2.8 ppm, while its local threshold and anomalous values were 4 ppm and ≤4.2 ppm, respectively. The positive anomaly of K was on the spot defined by long. 4.04°E and lat. 11.07°N. Its regional threshold value was ≤0.3 ppm, while its local aureole and anomaly had values 0.44 ppm and ≥0.48 ppm, respectively. Li had its positive anomaly defined by long. 4.04°E and lat. 11.07°N. Its regional threshold, local aureole and anomalous values were ≤8 ppm, 26 ppm and ≥30 ppm, respectively. Mg also had its positive anomaly defined by lat. 11.07°N but long. 4.035°E, while its negative anomaly was defined by long. 4.06°E and lat.11.025°N. Its regional threshold value, local aureole and anomaly had a concentration value of ≤0.012 ppm, 0.42 ppm and ≥0.48 ppm respectively. Mn had two positive anomalies that were defined by long. 3.36°E and lat. 11.12°N and long. 4.04°E and lat. 11.06°N (Figure 8). Its negative anomaly was defined by long. 4.07°E and lat. 11.05°E. Its regional threshold value, local aureole and anomalous values were ≤550 ppm, 800 ppm and ≥850 ppm, respectively.
3D isograde plot of Co.
3D isograde plot of Cs.
3D isograde plot of Mn.
The positive anomaly of Nb was on the spot defined by long. 4.04°E and lat.11.075°N (Figure 9). Its negative anomaly was defined by long. 4.05°E and lat. 11.075°N. Its regional threshold value was ≤0.6 ppm, while the local aureole was 2.2 ppm. Its anomaly had a value of ≥2.5 ppm. Ni had its positive anomaly on long. 4.03°E and lat. 11.075°N (Figure 10). Its regional threshold value and local and anomalous values were ≤6 ppm, 22 ppm and ≥25 ppm, respectively. P had its positive and negative anomalies defined by long. 4.04°E and lat. 11.1°N and long. 4.1°E and lat. 11.125°N, respectively. Its regional threshold, local aureole and anomalous values were ≤0.005 ppm, 0.017 ppm and ≥0.019 ppm, respectively. Rb has long. 4.05°E and lat. 11.1°N defining its positive anomaly. Its regional threshold, local aureole and anomalous values are ≤13 ppm, 47 ppm and ≥55 ppm, respectively. The positive anomaly of Sr was defined by long. 4.03°E and lat. 11.075°N, while its negative anomaly was defined by long. 4.07°E and lat. 11.05°N. Its regional threshold, local aureole and anomalous values were ≤12 ppm, 44 ppm and ≥48 ppm, respectively. Zn had its positive anomaly on the spot defined by long. 4.05°E and lat. 11.1°N (Figure 11). Its regional threshold, local aureole and anomalous values were ≤12 ppm, 42 ppm and ≥48 ppm, respectively. Ce had three positive anomalies defined by long. 3.97°E and lat. 11.15°N, long. 4.075°E and lat. 11.05°N and long. 4.16°E and lat. 11.1°N (Figure 12). Its regional threshold and local aureole had a concentration value of ≤55 ppm and 75 ppm, respectively, while the anomalous concentration is ≥80 ppm. Similarly, Cr had its positive anomaly defined by the same longitude and latitude that defined that of Co, but its negative anomaly was defined by long. 4.05°E and lat. 11.075°N (Figure 13). Its regional threshold value, local aureole and anomalous value were ≤28 ppm, 36 ppm and ≥40 ppm, respectively.
3D isograde plot of Nb.
3D isograde plot of Ni.
3D isograde plot of Zn.
3D isograde plot of Ce.
3D isograde plot of Cr.
Fe had its highest concentration value on the spot defined by long. 4.16°E and lat. 11.1°N (Figure 14). Its regional threshold value was ≤2.4%, while its local aureole and anomalous values were 3.2% and ≥3.4%, respectively. The positive anomalies of Ga and Hf were defined by the same longitude and latitude that defined the anomalous point of Fe. The regional threshold, local aureole and anomalous value of Ga are ≤6 ppm, 8 ppm and ≥8.5 ppm, respectively, but the regional threshold value, local aureole and anomalous value of Hf were ≤0.22 ppm, 0.3 ppm and ≥0.32 ppm, respectively.
3D isograde plot of Fe.
The positive anomaly of Hg was defined by long. 4.16°E and lat. 11.25°N, while its negative anomaly was defined by long. 4.1°E and lat. 11.1°N. Its regional threshold value was ≤22 ppm, while its local aureole and anomalous values were 26 ppm and ≥30 ppm, respectively. Like Fe, Ga and Hf, the positive anomaly of In was defined by long. 4.16°E and lat. 11.11°N (Figure 15). Its regional threshold value, local aureole and anomaly had values ≤0.03 ppm, 0.044 and ≥0.046 ppm, respectively. The positive anomaly of Mo was on the spot defined by long. 4.05°E and lat. 11.07°N (Figure 16). Its regional threshold had ≤0.25 ppm concentration, while its local aureole and anomalous value were 0.5 ppm and ≥0.9 ppm, respectively.
3D isograde plot of In.
3D isograde plot of Mo.
The positive anomaly of Pb is defined by long. 3.35°E and lat. 11.125°N. Its regional threshold, local threshold and anomalous values were ≤5 ppm, 17 ppm and ≥19 ppm, respectively. Pd anomaly was on the spot defined by long. 4.16°E and lat. 11.1°N (Figure 17). Its regional threshold value, local aureole and anomalous concentrations are ≤3 ppm, 12.5 ppm and ≥13.5 ppm. Sb, Sc and Sn (Figure 18) all have their positive anomalies defined by long. 4.16°E and lat. 11.1°N. The negative anomaly of Sc was defined by long. 3.95°E and lat. 11.1°N, while its regional threshold value, local aureole and anomalous values were ≤2 ppm, 6.5 ppm and ≥7.5 ppm, respectively. The regional threshold value, local aureole and anomalous values for Sb were ≤0.015 ppm, 0.06 ppm and ≥0.065 ppm. The negative anomaly of Sn was defined by long. 4.05°E and lat. 11.075°N. Its regional threshold value, local threshold and anomalous values were ≤0.4 ppm, 1.3 ppm and ≥1.5 ppm, respectively.
3D isograde plot of Pd.
3D isograde plot of Sn.
The anomalous value of Th is on the spot defined by long. 4.16°E and lat. 11.09°N (Figure 19). Its regional threshold value was ≤3 ppm, while its local aureole and anomalous values are 12 ppm and ≥13.5 ppm, respectively. Long. 4.05°E and lat. 11.05°N define Ti positive anomaly. Its regional threshold, local aureole and anomalous values were ≤0.025 ppm, 0.08 ppm and ≥0.095 ppm, respectively. Tl positive anomaly was defined by long. 4.04°E and lat. 11.1°N. Its regional threshold value, local aureole and anomalous value were ≤0.08 ppm, 0.28 ppm and ≥0.32 ppm, respectively. U had its positive and negative anomalies defined by long. 4.05°E and lat. 11.05°N and long. 4.1°E and lat. 11.1°N. Its regional threshold value, local aureole and anomaly were ≤0.6 ppm, 2.1 ppm and ≥2.4 ppm, respectively.
3D isograde plot of Th.
Long. 4.16°E and lat. 11.1°N defined the positive anomaly of V (Figure 20), while its regional threshold, local aureole and anomalous values were ≤18 ppm, 60 ppm and ≥70 ppm, respectively. Y had its positive and negative anomaly defined by long. 3.92°E and lat. 11.17°N and long. 4.03°E and lat. 11.075°N. Its regional threshold, local aureole and anomalous values are ≤6 ppm, 22 ppm and ≥24 ppm, respectively. Long. 4.16°E and lat. 11.11°N defined the Zr positive anomaly (Figure 21). Its regional threshold, local aureole and anomalous values were ≤5 ppm, 17 ppm and ≥19 ppm, respectively. La had its positive anomaly defined by long. 3.98°E and lat. 11.15°N. Its regional threshold, local aureole and anomalous values were ≤18 ppm, 26 ppm and ≥28 ppm, respectively. Na had its own positive anomalies defined by long. 3.96°E and lat. 11.12°N and long. 4.05°E and lat. 11.1°N, while its regional threshold value is ≤0.0008 ppm. Its local and anomalous values were 0.0026 ppm and ≥0.0028 ppm. Te had its positive anomaly defined by long. 4.06°E and lat. 11.05°N. Its regional threshold value, local aureole and anomalous value were ≤0.012 ppm, 0.044 ppm and ≥0.048 ppm, respectively.
3D isograde plot of V.
3D isograde plot of Zr.
Factor 1 of the soil factor analysis is predominated by the lithophile, chalcophile and siderophile elements. The distribution in this group is similar to the corresponding factor 1 in the ore factor analysis. In this factor group, most of the elements have mobilities which vary from low mobility to immobile [20]. Some of them, for example, Cu and Zn have varying mobilities between high to very low depending on the condition as against most of the elements that are immobile in the varying conditions. The association though related to weathered hydrothermal sulphide ore and sulphide-rich BIF is also aided by the mobility of the elements in fluctuating environmental conditions. The fluctuation in the condition is inferred from the inconsequential position occupied by the three types of elements that form the factor group. This scene is also repeated in factor 2 of the soil factor analysis. Most of the elements in this group are mainly transition metals. Their varying oxidation states coupled with the varying component of the materials that are coming together down the slope as the material is transported could account for the association in this group. At the beginning of this phase, the environmental condition favoured the lithophile element then followed by the condition that favoured the chalcophile. Midway into the phase, the condition became inconsistent before the condition that favoured the siderophile prevailed and capped by the chalcophile.
Factor 3 is typically of the lithophile elements with trapped single chalcophile element. The mobility of the chalcophile is similar to the mobility of the lithophile, thereby making it easy to be transported down the slope through the weathering path despite the differences in their chemical affinities and chemical properties. Factor 4 is also formed under relatively unstable environmental conditions that fluctuated between the condition that favoured the siderophile, chalcophile and lithophile elements. The conditions that favoured the lithophile existed over a relatively long period especially towards the end of the phase and thereafter changed to the condition that favoured the chalcophile elements and then capped by the condition favouring siderophile. Factor 5 with Hg, Ag and Au is related to the weathered precious metals that were originally formed from hydrothermal sulphide ore [16]. Factor 6 with no highest loading of any element but has Co, Sb and Mn with fair loading implies the presence of minute Co-bearing manganese ore in the area.
Ag has three positive anomalies. These are in the eastern and southwestern parts of the study area. The local aureoles are aligned in NW-SE and NE-SW towards the southern part of Kaoje and its environs. Closely associated with these aureoles are negative anomalies that trend parallel to the positive anomalies. Al has its anomaly at long. 4.05°E and lat. 11.09°N. There are other positive anomalies in the NW (long. 3.95°E and lat. 11.2°N) and at the eastern end (long. 3.92°E and lat. 11.2°N). The negative anomaly of Al is well-defined at the western part of the mapped area (long. 3.92°E, lat. 11.09°N). These anomalies trend in NW-SE. Another spot of negative anomaly is to the right of the positive anomaly that extends from the southern part of the area towards the central part. As has its positive anomaly in almost the same place with Al. Though there are three peaks described as anomaly having the highest values, two of these peaks are twinned towards the centre of the area, while the third one is at the eastern end of the study area. The negative anomaly that is closely associated with the twinned anomalies towards the centre is also similarly positioned like the negative anomaly in Al. At the western end of this twinned peaks are two of each positive and negative anomalies. While the positives trend in NE-SW, the negative anomalies trend perpendicular to them in NW-SE direction.
Au has relative different distribution patterns from Ag, Al and As. Its negative anomaly is positioned where the three elements (Ag, Al and As) have their positive anomalies. This relationship in the position of the negative anomaly of Au indicates its depletion in the minerals formed or path-found by the three elements. Other peaks of anomaly of Au are in the SE corner and eastern and western parts of the area. These peaks like the negative anomalies are aligned in almost east-west direction with the exception of the peak in the northern part. The three positive anomaly peaks in Ba trend essentially in NW-SE with its highest concentration point defined by lat. 11.13°N and long. 3.975°E. This point of highest concentration of Ba corresponds to local aureole of elements like As, Al, Ag and Au. There is no negative anomaly except sharp decrease to the background value within the area of study. These slopes flank the peaks and also separate the peaks from each other.
Like As, Be has its anomaly in the southern part extending towards the central part of the study area. There are positive anomalies that are similarly positioned in the western half of the area except that while the positive anomalies in this half trend in NE-SW for As, those in Be trend in NW-SE. In like manner, the negative anomalies in Be trend in NE-SW, but those in As trend in NW-SE. Be also has a twin peak of anomaly like As, but one of it is not well-defined. Their distribution pattern is not identical but has similar position of their anomalies. Bi has a distribution pattern that is closely similar to that of As in terms of their positive and negative anomalies. Its anomalous point is defined by lat. 11.075°N and long. 4.04°E. These peaks slope towards the north. There are few negative anomalies that are evenly distributed in the four quadrants of the area studied. Ca has a point of positive anomaly towards the centre of the area. This area is defined by long. 4.05°E and lat. 11.1°N. The negative anomaly is poorly defined in the NE and SE parts of Kaoje and its environs.
Cd has ridge of anomaly that trend in NW-SE. The other anomaly is almost perpendicular to the broad NW-SE trending anomaly. Ce has its aureole in the western and SE part essentially. The extreme NE and SW part are relatively depleted in Ce. The Ce anomaly defines an arc curving back at the southern part. Cr has its anomaly at lat. 4.05°E and long. 11.075°N. Its negative anomalies trend in almost E-W direction. It shares some point of anomaly with elements like As and Bi. With the exception of slightly elevated concentration at the western part of the area (lat. 3.965°E and long. 11.120°N) essentially, the distribution of Co is almost identical with that of Cr. They (Cr and Co) have their anomaly in the same spot, while the distribution pattern of Cs and K is identical and similar with that of Ca. Their anomaly point is defined by lat. 4.05°E and long. 11.06°E. This anomaly trends in N-S direction. The anomaly of Ca does not cover larger area; the anomaly of Cs, K, Li and Mg covers relatively larger area compared with that of Ca, Bi and Cr. Their distribution pattern is also identical sharing the same point of anomalous concentration. There are passive zones of depletion which fall generally under regional threshold. Fe has its highest concentration in the eastern part of the study area and an anomaly that is described as local aureole in the southern part of the study area. These two peaks of anomalies are also observed in the isograde plot of As. With little variations, its distribution pattern is closely related to the distribution pattern of Cr and As.
Ga and Hf have different distribution patterns, but their zones of anomaly are similarly positioned in the eastern part of the area. This part is similarly shared by Fe, As and Cr essentially. While the negative anomaly in Ga trends in NW-SE direction essentially, the negative anomaly in Hf is randomly oriented. Hg has its peaks trending in NW-SE and at the extreme NE. This aureole is closely associated with negative anomaly that trends also in NW-SE. The anomaly at the extreme NE end is similarly positioned like the one in Cd, while the aligned NW-SE aureoles are similar to those in Cd. In is enriched in the eastern half of the study area. There is an aureole in the NW part, while the remaining area is relatively depleted in In. this depleted zone coincide with the boundary between the sedimentary rocks and the basement rock exposures. It zones of highest concentration are in the extreme eastern part where Fe, Cd, etc. also have theirs. No negative anomaly is seen as the values of depression are relatively higher than the values in the extreme NW and SW part of the area.
The distribution pattern of La is similar to that of Hg. Its point of highest aureole is defined by lat. 11.15°N and long. 3.98°E. The aureoles in La form a poorly defined curve shape that trends mainly in NW-SE direction. The extreme SE part is also slightly enriched in La but not as high as the central to NW part of the study area; the depleted zones flank the aureoles. Mn plot is identical with that of Co; it shares the same spot of anomalous concentration with Co and one of Cr anomalous concentration area. The aureole trends in NW-SE and decreases from the SW half towards the extreme NE part. Though not identical, other elements like Cs, K, Li, Mg, Ca, Bi, Cr, etc. have their anomalous point in either point of the anomalous concentration of Mn and Co. Like Mn, Mo has its highest point of concentration in the southern part of the area. There is also a relatively high concentration in the eastern part where Fe has one of its aureoles. Other slightly enriched zone of Mo is the western part. The positive aureole of Mo trends almost perpendicular to the positive aureole of Mn. With the exception of two well-defined peaks of aureoles, other patterns of distribution of these elements are alike.
Na has two peaks of positive anomaly. These peaks are located in the western and central parts of the area study. The western aureole is related to the western aureole of Mn though the Mn aureole is not as broad as that of Na but is more steep sided than that of Na. The area study is slightly more enriched in Na except the extreme four corners of the area. Nb has similar distribution pattern with Ca. The study area is slightly more enriched in Nb relative to Ca, although they both have their positive aureole defined by the same latitude and longitude. The SW part of the area is more depleted in Nb, while the central part is enriched and trends perfectly in NW-SE direction. At the SE end of the positive anomaly, there is a zone of negative anomaly. This zone of Nb negative anomaly coincides with the zone of the most pronounced Au negative anomaly. Other elements with their positive anomaly or one of their positive anomalies defined by lat. 11.075°N and long. 4.05°E or closely related to that of Nb include Ca, Mg, K, Cs, Li, Be and As. Ni has its distribution pattern identical with that of Mg but the western part of the area is slightly depleted in Ni. The southern part of the study area is more enriched in Ni relative to the rest of the area. The aureole has >23 ppm concentration, while its local aureole has a concentration value of 21 ppm. Besides the fact that Li, Cs and K have primitive peaks closely associated with their aureoles, their distribution patterns and the distribution pattern of Ni are alike when their zones of anomaly are compared together. Ni also has its positive anomaly similarly positioned like the aureole of elements like Co, Bi and Al even though their distribution pattern is different. The positive aureole of Ni coincides with one of the positive aureoles in As while it is within the enriched zone of Be that trend NE-SW from the southern part. Au has its negative anomaly where Ni has its positive anomaly. This implies that Au depletion indicate the present of mineralization that is indicated by anomalous high concentration of Ni in this area.
Like Nb, P has its positive aureole defined by lat. 11.1°N and long. 4.05°E. The spot is shared or closely related to by the aureole of other elements like Li, Al, As, Be, Ca, Cs, K, etc. Its distribution pattern is similar to the distribution pattern of Mo, La, Hg, Ga, Fe and Ce essentially. Though with relatively lower concentration values and in rare cases slightly high concentration, the zones of positive enrichment and depletion of these elements are closely related. Cr has relatively high enrichment in all the areas where P also has its high enrichment but the zone of P depletion in the eastern part is not seen in Cr isograde plot. Pb has its highest concentration (>19 ppm) in the western part of the area defined by long. 3.35°E and lat. 11.125°N. Like P, La, Fe, Ce, etc., its distribution pattern forms a poorly defined U-shape. The zone of its highest positive anomaly has negative anomalies closely associated with it in the SW and NE parts. Other peaks of positive anomalies are in the southern and extreme eastern parts of the area. Its zone of highest concentration is related to the zone of highest concentration of elements like La, Ce, Cd and Ba. The peaks of positive anomaly in the western and southern parts relate very well with the two peaks of positive anomaly in Mn, while the peaks of positive anomaly of Pb in the southern and eastern parts are closely associated with the peaks of highest Fe concentration. Fe also has slightly elevated value in the western part where Pb has its highest concentration value. Other elements have their positive anomalies in one or more zone of Pb enrichment even though their distribution patterns are not the same.
Pd has its aureole in the western end of the study area. Its concentration decreases gradually towards the western end of the area. The zones of its highest concentration in the eastern part of the area coincide perfectly with one of the positive aureoles of Fe, Mo, In, Ga, Hf, etc. The Rb style of distribution is identical with the distribution pattern of Li, K and Cs. Its zone of highest concentration is wholly or partly shared besides the aforementioned elements by Al, As, Be, Bi, Ca, Cd, Co, Mg, Mn, Mo, Nb, Ni, P, etc. The peaks of its aureoles trend essentially in NE-SW direction. The negative anomalies are not well-defined but are closely associated with positive anomaly in the eastern part of the area.
Sb has its zones of highest concentration in the extreme eastern and western end of the area. Other zones of enrichment are closely associated with these two peaks defining a slightly different NE-SW trending direction. The distribution pattern is relatively unique, but its zone of highest concentration in the eastern end is related to the zones of highest concentration of Fe, Mo, In, Ga and Hf. The extreme NW and SW are the most depleted zones of Sb. Other areas have slightly elevated value relative to other elements.
With the exception of break in the ridge of positive anomaly of Sc in the western part of the area, the distribution pattern of Sc and Sn is identical. They both have a ridge of positive anomaly that rises in the NW going through the southern part and turning through the eastern part to end in the NE part of the area study. They have two peaks of positive aureoles. One of the aureoles is situated in the eastern part where elements like Fe, Mo, In, Ga and Hf have their or one of their positive anomalies. The second positive aureole of Sc is in the southern part of the area, while that of Sn shifts slightly to the SE part of the area. They have their negative anomalies trending essentially NW-SE in the western end and NE-SW in the eastern end. Sr has slight enrichment in the western part. These enrichments trend in NW-SE terminating in the central part. Its zone of highest concentration is in the centre. This centre where it has its highest concentration is defined by long. 4.05°E and lat. 11.075°N. Its zone of highest concentration is similarly shared by Rb, Al, As, Be, Bi, Ca, Cd, Co, Mg, Mn, Mo, Nb, Ni, P, etc. Its distribution pattern is identical with the distribution pattern of Ca.
The distribution pattern of Te is similar to the distribution pattern of Na. Its peak (positive anomaly) is in the central to SE part of the area. Its anomaly trends in NW-SE but generally decreases to the background value of ≤0.028 ppm. Th has its highest concentration in the eastern part. Other area with relatively high concentration of Th is in the SE and is closely associated with the zone of Th positive anomaly. The concentration of Th in the western half is also relatively high but not as high as the concentration in the eastern part. The western aureole trends in N-S direction with about three alternations in its concentration with about three alternations in its concentration. The extreme NW and SW corners of the area are relatively the most depleted zone for Th. The position of the positive anomaly of Th is the same with the position of positive anomaly of Fe, Sn, Sc, Sb, Pd, In, Hf and As. Mo and Ce has one of their positive anomaly in this eastern part, but the zone of highest concentration of Ag is just slightly off the zone of Th highest concentration to the west.
Ti, Tl and U have their positive anomalies defined by lat. 11.075°N and long. 4.04°E and lat. 11.08°N and long. 4.04°E and lat. 11.07°N and long. 4.04°E, respectively. Though with slight variation, these elements have their positive anomalies where elements like Sr, Rb, Ni, P, Nb, Li, K, Cs, Co, Cd, Ca, Bi, Be, As and Al have theirs or one of their positive anomalies. This zone is also though not exactly but similarly positioned like one of the Mn positive anomaly. Ti and Tl have their highest concentration within the central part of the area. Ti concentration is slightly high in the eastern and extreme NE part, but Tl has its own concentration decreasing gradually towards the extreme west, thereby making the western half slightly more enriched than the eastern half. Both Ti and Tl have sharp depression to the background value. These depressions are similarly oriented in poorly defined NWW-SEE in the western half of the area. Unlike Ti and Tl, U has its concentration in the central part which forms a ridge of positive anomaly extending from the central area to the NW of the area where it forms a twin peak. The peak to the east among these two peaks has slightly higher concentration than that in the western part. There are negative anomalies in the western half and eastern part of the area. The negative anomalies in the western half that are well-defined trend in NE-SW. The poorly defined negative anomaly trends with one of the well-defined in NW-SE. The U negative anomalies in the eastern half of the area trend mainly in NE-SW.
The distribution pattern of V is similar to the distribution pattern of Th, Sc, Sn, Pb, P, Mo, La, Hg, Ga, Fe, Cr and Ce. Its zone of highest concentration (>65 ppm) is in the extreme eastern part, while it is also enriched in the southern part. These two zones of highest concentration are similar to the zone of highest concentration of Fe, Sc and Mo. The enrichment in the western half is almost identical with that of Fe when the position of the zones of highest enrichment and depletion are compared. The central part of the area is the most depleted zone of V. Like some other elements, e.g. Hf, its distribution pattern has poorly defined U-shape. The zone of highest concentration of Y (>23 ppm) is in the NW part of the area. This area is flanked by negative anomaly in the SW and NE part. The zone of relative high concentration of the anomaly, usually ≥16 ppm, is restricted to the western half of the study area and trends in NW-SE direction. The extreme SW and SE corner is relatively depleted of Y (≤5 ppm), while other areas have elevated value that range between 5 and 16 ppm. The positive anomalous zone of Y is similarly enriched in Pb, La, Hg, Cd, Ce, Ba and Mn.
The distribution pattern of Zn is identical with the distribution pattern of Rb and almost identical with the distribution pattern of Li, K and Cs. Both Zn and Rb have two peaks at the crest of their anomalous zone in the central part of the study area. The peak in the northern part out of these two peaks is slightly more prominent than the one in the south. These two peaks are also present in the same position in the isograde plot of Tl despite the fact that its style of distribution is slightly different from that of Zn and Rb. Other similarities in the distribution pattern of Zn and Rb include the twin slightly enriched area in the NW part of the area and also the negative anomaly in their isograde plot. Other elements that have their positive anomaly where Zn has its own and with similar distribution pattern include Ti, Mg, Cs, etc. Cs and K have the two peaks, but their peak in the southern part is more prominent than the one in the northern part. The zone of Zn anomaly is shared by the anomaly of Al, As, Be, Bi, Ca, Cd, Co, Mn, Nb, P and Ni essentially. Zr highest concentration is ≥19 ppm. This concentration is in the eastern part of the area. With the exception of elevated value (≤9 ppm) in the NW part of the area, the enrichment of Zr is restricted to the eastern half of the area especially where Fe, Th and Pd have their highest concentration.
From integrated field observation, geochemical study, statistical analysis and isograde plottings, it was concluded that the area investigated is mineralized with goethite and manganite ores, while there are minor enrichments of tourmaline and silicate minerals like chalcedony. It was also concluded that the eastern and southern parts of the study area is mineralized with goethite, while the western and southern parts are mineralized with manganite. Furthermore, in exploring for iron-manganite mineralization in this area, manganite has as its pathfinder the following associations Zn + As + Be + Bi + Co + Nb + Ni + Cs ± P + Al + Ca + Cd + Rb + Li + K, while Zr + Th + Pd + Mo + V + Sn + Cr + Ce + In ± Sc + P + Pb associations are related to iron mineralization.
The sugarcane production systems addressed in this chapter were recommended by the authors for small farms of the Zona da Mata region of the state of Minas Gerais, Brazil. These small rural properties are located at geographical coordinates ranging from 20°45′14″ to 21°11′39″ South and 42°52′55″ and 43°01′04″ West. The altitude ranges from 330 to 650 m. The climate of the region is humid subtropical and varies from Aw to Cwa with rainy summers, according to Köppen classification. The average precipitation of the last 30 years is approximately 1200 mm. There is water surplus from November to March, precipitation is below potential evapotranspiration from April to September (causing water deficit), and precipitation is again higher than evapotranspiration in October. Therefore, the dry and rainy seasons are well defined in the region.
\nThe predominant soils in the region are Distrophic Red-Yellow Latossol, Ultisol Red-Yellow Dystrophic and Latossolic Cambisol [1]. Although soils have low fertility, their physical composition allows for agricultural activity provided that appropriate techniques are used. The main agricultural techniques recommended to these small farmers are aimed at improving the physical and chemical properties of the soil by lime and gypsum application, chemical fertilization, green fertilization, using organic compost, planting of sugarcane varieties with greater yield potential, chemical weed control, and biological pest control. The sugarcane produced in these properties is intended for animal feed and the production of
Several technologies can be used in setting up and managing sugarcane plantations in small farms. Those selected and recommended by the authors are focused on maximizing the use of inputs, land and human resources to reduce operating costs and increase crop yields, in addition to helping preserve the environment. The main cost items for setting up 1 ha of sugarcane in the region are shown in Table 1. In sugarcane, it is common to evaluate the results obtained by quantifying the production of culms, sugars, or total shoot biomass. In analyzing the production costs, one can use the exchange ratio, which is an economic indicator that shows the exchange capacity of a certain product in relation to the inputs used in production (product/input).
\nCost item | \nUnit*\n | \nUnit price | \nQuantity | \nTotal price | \nParticipation | \n
---|---|---|---|---|---|
(US$) | \n(US$) | \n% | \n|||
\n | \n | \n | \n | \n | |
Limestone | \nt | \n\n | \n | \n | \n |
Gypsum | \nt | \n\n | \n | \n | \n |
Seeds of | \nkg/ha | \n\n | \n | \n | \n |
Fertilizer | \nkg | \n\n | \n | \n | \n |
Sugarcane seedlings | \nt | \n\n | \n | \n | \n |
Chemical insecticide | \nL or kg | \n\n | \n | \n | \n |
Herbicide | \nL or kg | \n\n | \n | \n | \n |
Formicide | \nL or kg | \n\n | \n | \n | \n |
Biological insecticide | \nL | \n\n | \n | \n | \n |
\n | \n | \n | \n | \n | |
\n | \n | \n | \n | \n | |
Land rent | \nha | \n\n | \n | \n | \n |
Soil analysis | \nsample | \n\n | \n | \n | \n |
Plowing | \nh/m | \n\n | \n | \n | \n |
Harrowing | \nh/m | \n\n | \n | \n | \n |
Sowing of | \nh/m | \n\n | \n | \n | \n |
Incorporation of | \nh/m | \n\n | \n | \n | \n |
Furrowing for planting sugarcane | \nh/m | \n\n | \n | \n | \n |
Fertilizer application in the planting furrow | \nh/m or d/H | \n\n | \n | \n | \n |
Seedling distribution and pruning | \nd/H | \n\n | \n | \n | \n |
Insecticide application on the seedlings | \nh/h or d/H | \n\n | \n | \n | \n |
Covering of seedlings | \nh/m or d/H | \n\n | \n | \n | \n |
Herbicide application | \nh/m or d/H | \n\n | \n | \n | \n |
Formicide application | \nd/H | \n\n | \n | \n | \n |
Insecticide application | \nd/H | \n\n | \n | \n | \n |
\n | \n | \n | \n | \n | |
Main cost items for the implantation one hectare of sugarcane in small farms of the Zona da Mata region.
\n
The great advantage of exchange ratio analysis over price analysis is that agricultural products represent the weighted average of several inputs and goods used by the farmer. Thus, it is easier to calculate the variation in producer purchasing power or production system efficiency. If possible, this analysis should cover a long period of time, so that the extent of the variation in results can be measured. The use of spreadsheets (e.g., Excel) is helpful in analyzing simulation results, as well as budgeting and managing sugarcane production costs. The authors have guided farmers to adopt practices that recover and maintain soil fertility, recycle nutrients, and reduce compaction and sealing of the topsoil, combined with activities that enable increased yields in plant-cane and small decreases in subsequent cycles. Table 2 shows a simulation of sugarcane yield in 14 scenarios, which combine high and medium yields in the plant-cane cycle to low, medium, or high decreases in yield over seven cycles (seven cuts).
\nSimulation of a sugarcane plantation area needed to feed 25 dairy cows (20 kg of natural matter per cow/day) for 365 days and plant-cane yield and yield stability in seven succeeding cuts.
\nTable 2 shows that to feed 25 cows for 365 days (20 kg of natural matter per cow/day), an area of 1.63 ha of a sugarcane plantation with high yield in the plant-cane cycle and 10% decrease in subsequent cycles would be necessary (Scenario 1). On the other hand, an area of about 3.3 ha would be needed for a sugarcane plantation with medium yield in the plant-cane cycle and large decreases in subsequent cycles (Scenario 14). In sugarcane plantations with yields of less than 60 tons of natural matter per ha (about 50 tons of industrializable culms), in addition to decreasing the use of land and labor resources, chemical weed control is generally inefficient, as the crop does not completely cover (shade) the soil, allowing the emergence and growth of invasive species (Figure 1). Also, in cases where sugarcane is cut by hand, the worker will be more exposed to snakes and scorpions.
\nContrast between a sugarcane plantation with high yields and excellent weed control, and a plantation with low yields and poor weed control.
Choosing the right variety is an important and low-cost technology for the producer. Currently, there are several sugarcane cultivars with proper agronomic and zootechnical characteristics, such as high response to improved soil fertility, erect growth, and resistance to falling, which facilitates harvesting, high culm and sucrose yield, regrowth vigor, resistance to pests and diseases, and good dry matter digestibility.
\nThe authors of this chapter do not recommend planting one variety of sugarcane in more than 33% of the total area, even if it has a large number of desirable characteristics. This is because sugarcane production will be greatly compromised in cases of possible breakdown of resistance to disease or sudden decline of the cultivar. Thus, in order to obtain a good quality product, ensure vigorous regrowth and consequently increase the longevity of the sugarcane plantation, the authors recommend that farmers use at least four varieties of sugarcane and adopt measures to maintain soil fertility and cut the sugarcane at the most suitable time for each variety. Once the varieties have been selected, it is necessary to check the quality of the seedlings. It is also important to confirm the health of the seedlings in terms of diseases, pests, and mixture of other cultivars. Table 3 shows characteristics of the varieties currently most planted in small farms of the Zona da Mata region.
\nRB867515 has been the variety of sugarcane most cultivated by small producers due to its high yield potential in different edaphoclimatic conditions. As mentioned in Table 3, RB867515 is a medium maturing variety with high sucrose content in industrializable culms. It has a low requirement for soil fertility, but it is very responsive to fertilization. Its detrashing is easy and it has no pilosity. Figure 2 shows dry matter accumulation rate in shoots of three sugarcane varieties (RB855536, RB867515, and SP801816). The study was conducted in soil of medium texture in the city of Mercês, state of Minas Gerais (MG) (latitude 21.260232, longitude 43.298827, and altitude 503 m).
\nCharacteristic | \nVariety | \n||||||
---|---|---|---|---|---|---|---|
RB835054 | \nRB855536 | \nRB867515 | \nRB928064 | \nRB975201 | \nSP80-1816 | \nSP80-3280 | \n|
Yield\n1\n\n | \nHigh | \nHigh | \nHigh | \nHigh | \nHigh | \nHigh | \nHigh | \n
Maturation | \nEarly | \nMedium | \nMedium | \nLate | \nLate | \nMedium | \nMedium | \n
Sucrose content | \nHigh | \nHigh | \nHigh | \nMedium | \nMedium | \nHigh | \nHigh | \n
Harvest \n2\n\n | \nApr-Nov | \nJun-Nov | \nJun-Sep | \nSep-Nov | \nAgo-Nov | \nJun-Sep | \nJun-Sep | \n
Soil\n3\n\n | \nMedium | \nMedium | \nLow | \nHigh | \nMedium | \nMedium | \nMedium | \n
Regrowth\n4\n\n | \nGood | \nExcellent | \nGood | \nGood | \nGood | \nExcellent | \nGood | \n
Tillering\n5\n\n | \nAverage | \nExcellent | \nAverage | \nVery good | \nAverage | \nVery good | \nVery good | \n
Toppling\n6\n\n | \nFrequent | \nLittle | \nLittle | \nLittle | \nFrequent | \nLittle | \nRare | \n
Detrashing\n7\n\n | \nEasy | \nMedium | \nEasy | \nMedium | \nEasy | \nMedium | \nEasy | \n
Pilosity | \nNo | \nNo | \nNo | \nYes | \nNo | \nYes | \nNo | \n
Flowering | \nAbsent | \nAbsent | \nMedium | \nAbsent | \nAbsent | \nAbsent | \nPresent | \n
Wilting | \nNo | \nNo | \nMedium | \nNo | \nNo | \nLittle | \nYes | \n
Sensitivity to Herbicides\n8\n\n | \nHigh | \nMedium | \nLow | \nLow | \nLow | \nMedium | \nMedium | \n
Coal\n9\n\n | \nResistant | \nIntermediate | \nResistant | \nResistant | \nResistant | \nIntermediate | \nIntermediate | \n
Rust9\n | \nResistant | \nResistant | \nResistant | \nResistant | \nResistant | \nResistant | \nResistant | \n
Red Streak9\n | \nResistant | \nIntermediate | \nSusceptible | \nResistant | \nIntermediate | \nResistant | \nResistant | \n
Leaf scalding9\n | \nResistant | \nIntermediate | \nResistant | \nResistant | \nResistant | \nResistant | \nResistant | \n
Agroindustrial, morphological, and tolerance characteristics of seven varieties of sugarcane recommended for cultivation in the small farms of the Zona da Mata region.
Yield: Yield per ha of industrializable culms and biomass (High, Medium or Low)
Harvest: Recommended months for the harvest of sugarcane for brown sugar and rapadura
Soils: Soil fertility requirement (High, Medium or Low)
Regrowth: sprout vigor of regrowth under conditions of trampling by machines or animal traction vehicles
Tillering: growth speed and soil shading, thus minimizing weed competition
Toppling: plant growth habit, which varies from erect to decumbent. Even cultivars with upright culms may topple under high-yield conditions
Detrashing: removal of dry leaves or attachment of the sheath to the culm
Sensitivity to certain herbicides
Diseases of the plant shoot.
Source: Silveira, L. C. I. (unpublished data).
Dry matter accumulation rate in shoots of three sugarcane varieties planted in February and harvested in July of the following year. Study carried out in the city of Mercês, located in the Zona da Mata region. Source: Oliveira MW (unpublished data).
Sugarcane was planted in the first half of February. Following the recommendation of Ref. [1], 5.0 t of dolomitic limestone and 1.5 t of gypsum were applied per ha in September of the year prior to the planting of sugarcane. The soil was plowed and harrowed, followed by the sowing of
Similarly to South Central Brazil, the planting of sugarcane without irrigation in small farms of the Zona da Mata region is essentially done at the beginning of the rainy season (September and October) and at end of the rainy season (February to March). The sugarcane planted at the beginning of the rainy season can be harvested from April to May of the following year (known as “one-year sugarcane”). However, for sugarcane planted from February to March, the harvest will take place about 15–18 months after (known as “one-and-a-half-year sugarcane”).
\nThe authors have recommended the planting of “one-year sugarcane” in more fertile soils with smoother and less erosive relief, because there is heavy rainfall during this period. Because sugarcane starts the maximum growth phase in January (when water and thermal availability begin to decrease), nutrient supply should not be a limiting factor to plant development. Therefore, biomass yields exceeding 120 t of natural matter per ha should be reached. However, planting “one-and-a-half-year sugarcane” has been recommended for the more rugged and less fertile soils, since sugarcane will continue to grow in the field for a longer period. Also, the maximum growth phase (Figure 2) coincides with the times of greater water and light availability, which results in higher vegetation cover by sugarcane foliage as well as in higher photosynthetic rate and dry matter accumulation. One other great advantage of planting the “one-and-a-half-year sugarcane” is the possibility of growing
Sugarcane extracts and accumulates large amounts of nutrients from the soil because it produces large amounts of biomass. In evaluations carried out in small properties of the Zona da Mata region, the authors found that to produce 120 tons of natural matter per ha (about 100 t of industrializable culms), the accumulation of nutrients in shoots is approximately 150, 40, 180, 90, 50, and 40 kg of N, P, K, Ca, Mg, and S, respectively. In the case of iron, manganese, zinc, copper, and boron, accumulation in shoot biomass for a production of 120 t is around 8.0, 3.0, 0.6, 0.4, and, 0.3 kg, respectively [1]. Because of this high nutrient removal, it is necessary to know the nutrient supply capacity of the soil to complement it with fertilization if necessary. On the other hand, if toxic levels are found, the concentration of these elements is reduced by applying limestone and gypsum. The availability and presence of toxic levels of nutrients in soil are typically evaluated by chemical analysis of the topsoil. Knowledge of the history of the area is also of great value, especially fertilization and whether or not there were symptoms of deficiency or toxicity in previous crops.
\nSoil samples are typically collected at depths of 0–20 and 20–40 cm. The results of the analysis at 0–20 cm have been used to calculate the need for fertilization and liming, while those at 20–40 cm to calculate the need for gypsum. Because these are small areas, the authors have advised producers to collect soil samples using a hole digger and straight shovel, as the use of a straight shovel decreases the variability of soil fertility indexes. Further details on sampling procedures, sample variability, sample drying, and comparison between chemical extractors can be found in Ref. [1]. As previously mentioned, most of the soils of the region are naturally acidic and present low saturation by basic cations such as calcium, magnesium, and potassium. Deficiency of these basic cations combined with high levels of aluminum, iron, and manganese has been detrimental to the growth of the root system and the entire plant. For these reasons, limestone and gypsum applications are recommended by the authors. Several materials have been used as soil acidity correctors, of which the most commonly used is dolomitic limestone. However, calcitic and magnesium limestone, as well as calcium and magnesium silicates (referred to as steel slags) are also used. Magnesium oxide content is around 8% in steel slag, while it is less than 5% in calcitic limestone, between 6 and 12% in magnesium limestone, and above 12% in dolomitic limestone. The efficiency of these products in correcting soil acidity depends on particle size, uniform distribution in the field, and soil water availability.
\nThe most used soil analysis method in the region is the one that uses calcium acetate to determine H+ + Al+3. This extractor greatly underestimates the amount of H+ + Al+3, and results in underestimating the cation exchange capacity at pH 7.0 and the limestone dose. For these reasons, the authors have recommended raising the dose of limestone by 1.5–2.0 times. For sugarcane grown in small farms, the recommendation is to increase base saturation (V) to 60%. The limestone dose (LD) when using the base saturation method is calculated by the following equation (Eq. (1)):
\nwhere V is the current base saturation of the soil, T is the cation exchange capacity at pH 7.0, and RTNP is the relative total neutralizing power of the corrective used.
\nDolomitic limestone is recommended when magnesium content at 0–20 cm is less than 0.40 cmolc/dm3 of soil. On the other hand, if magnesium content at 0–20 cm is greater than 0.40 cmolc/dm3 of soil, the recommendation is to use the corrective that has the lowest price per ton of RTNP in the crop. Thus, an economic factor is included in the decision making regarding the type of limestone to be used. The use of gypsum has been recommend based on the results of chemical analysis of the 20–40 cm layer. Gypsum has been applied when calcium content is less than 0.40 cmolc/dm3 of soil or aluminum saturation (m%) is higher than 20%. The usual recommended dose is one-third of the limestone dose (e.g., assuming that the limestone dose is 4.5 t per ha, then gypsum will be 1.5 t per ha). Limestone and gypsum are mixed for subsequent application to the soil. The application of gypsum will lead to the improvement of the root environment of the layers below the topsoil. This effect lasts for several years, which is the reason annual gypsum application is not necessary [1].
\nIn small properties, the application of limestone + gypsum is typically done by hand. A recommended method for these small producers has been to delimit a square or rectangle with the mixture of limestone + gypsum and apply a volume corresponding to the recommended dose in the area. For instance, if the recommended dose was 6000 kg (4500 kg of limestone +1500 kg of gypsum per ha) and the density of the limestone + gypsum mixture is 1.25 kg/L, then 4800 L per ha or 0.48 L per m2 should be applied. Another alternative for small producers to apply limestone + gypsum by hand would be to demarcate areas of 25 m2 with the mixture itself and apply 12.0 L of limestone + gypsum.
\nPlowing and harrowing is typically done after the application of limestone + gypsum to incorporate the products into the soil. In most small farms, subsoiling (decompacting soils or breaking compacted layers) has been recommended after plowing and harrowing. This recommendation is based on the land use history of the area, the traffic of machines, implements and animals, the presence of crusts on the surface of the land, and the shallow root system of the natural vegetation. Although it may be an additional burden for the producer, the presence of densified or compacted layers has harmful consequences on water absorption, mineral nutrition, crop development, and longevity of the sugarcane plantation.
\nAs previously mentioned in item 4 (implantation of sugarcane plantation), one of the advantages of planting the “one-and-a-half-year sugarcane” is the possibility of a green fertilization prior to the planting of sugarcane. Among the main desirable characteristics of plants used for green fertilization are the following: the possibility of using mechanization from sowing to the harvesting of seeds, the ability to associate with nitrogen-fixing bacteria, rapid growth to control weeds, having mechanisms, or being able to synthesize compounds that help control pests (e.g., nematodes) and diseases, no dormant seeds, and a vigorous and deep root system that assists in the recycling of nutrients from the deepest layers and in soil decompaction. Another aspect to be considered is the supply of organic and mineral substrate to soil microorganisms. Thus, green fertilization also contributes to the improvement of the biological quality of the soil [2–4]. Several legumes have these characteristics, but there is generally a preference for
In the studies conducted by the authors of this chapter in the Zona da Mata region, green fertilization with
DAE | \nPlant height | \nLAI | \nDM accumulation | \nDM accumulation rate | \n
---|---|---|---|---|
(cm) | \nm2/m2\n | \n(t/ha) | \n(kg/ha/day) | \n|
30 | \n84 | \n2.1 | \n2.2 | \n73 | \n
45 | \n178 | \n3.6 | \n4.1 | \n127 | \n
60 | \n192 | \n6.5 | \n7.8 | \n247 | \n
75 | \n247 | \n8.3 | \n11.9 | \n273 | \n
90 | \n313 | \n9.4 | \n14.2 | \n153 | \n
105 | \n328 | \n11.3 | \n15.5 | \n87 | \n
120 | \n342 | \n8.9 | \n16.2 | \n47 | \n
Plant height, leaf area index (LAI), dry matter accumulation (DM accumulation), and dry matter accumulation rate (DM accumulation rate) in shoot biomass of
\n
Ref. [6] reported excellent results with the use of
\n
\n
These reductions were around 6, 13, and 24% for plant height in comparison with that of the first sowing times (Table 5). The study was conducted in a Latossolo vermelho amarelo distrófico, which exhibited the following chemical characteristics at 0–20 cm: pH in H2O = 6.2; 6.0 mg/dm3 of phosphorus and 59 mg/dm3 of potassium, (extracted with Mehlich), no exchangeable aluminum and 45% of base saturation.
Due to the sensitivity of
The accumulation of nitrogen in the shoot biomass of
The inoculation of
Furrowing the soil for the planting of sugarcane is done after plowing and harrowing the land for the incorporation of limestone and gypsum or, after the incorporation of
The recommended fertilization of the plant-cane is based on the results of the soil analysis at 0–20 cm and the expected yield of the sugarcane plantation. For plant-cane, only phosphate and potassium fertilization are recommended, because studies conducted by the authors of the chapter showed a lack of response to nitrogen fertilization. This low or absent response of the plant-cane to fertilization is widespread for soils grown with sugarcane in Brazil [4]. For the typically low fertile soils of the Zona da Mata region, the recommendation is 100 kg of phosphorus and 200 kg of potassium per ha (equivalent to 229 of P2O5 and 240 kg of K2O per ha). If gypsum is applied to the soil, triple superphosphate should be used to reduce the planting costs, as it is less expensive. More information on fertilizer doses and soil fertility, as well as losses by leaching of both nitrogen and potassium can be found in Ref. [1].
\nSowing times | \nDM accumulation | \nN accumulation | \nPlant height | \n|||
---|---|---|---|---|---|---|
(kg/ha) | \n(kg/ha) | \n(cm) | \n||||
Year 1 | \nYear 2 | \nYear 1 | \nYear 2 | \nYear 1 | \nYear 2 | \n|
Early October | \n14,135 a | \n14,789 a | \n273 a | \n284 a | \n293 a | \n305 a | \n
Mid-October | \n14,768 a | \n14,845 a | \n297 a | \n275 a | \n311 a | \n298 a | \n
Early November | \n14,235 a | \n13,785 a | \n268 a | \n279 a | \n287a | \n293 a | \n
Mid-November | \n11,985 b | \n11,178 b | \n220 b | \n226 b | \n267 b | \n256 b | \n
Early December | \n9,123 c | \n9,545 c | \n198 bc | \n203 c | \n247 c | \n236 c | \n
Mid-December | \n8,523 d | \n8,037 d | \n174 c | \n168 d | \n217 d | \n208 d | \n
Accumulation of dry matter (DM accumulation) and nitrogen (N accumulation) in shoot biomass of
Means followed by the same letter in the column do not differ statistically from one another other by the Tukey test at 5%.
The lack of response of the plant-cane to nitrogen fertilization is due to the mineralization of soil organic matter and the greater nutritional efficiency of the plant-cane root system, compared to the regrowth [1, 4]. Studies conducted by Ref. [11] in the coastal plains of Pernambuco (Northeast Brazil) provide more information regarding the mineralization of soil organic matter. These authors measured carbon and nitrogen mineralization in a Red Yellow Podzolic during the plant-cane cycle. The soil was sampled at 0–20, 20–40, and 40–60 cm prior to planting and 3, 6, 11, and 16 months after planting. Total carbon contents were 6.7, 4.1, and 3.4 g kg−1, while total N contents were 0.7, 0.4, and 0.3 g kg−1 at 0–20, 20–40, and 40–60 cm, respectively. The estimated amounts of potentially mineralizable N were 139 and 132 kg per ha at 0–20 and 20–60 cm, respectively, with a mineralization constant of 0.074 per week. Ref. [11] also report that although the soil is considered of low fertility based on the results, the amounts of mineralized organic N would be enough to satisfy the needs of the plant-cane.
\nNitrogen uptake and metabolism are strongly influenced by the endogenous availability of phosphorus [1, 12, 13]. In plants with adequate P supply, there is an increase in nitrate uptake from the soil solution and greater nitrate translocation from roots to shoots, increasing the accumulation of amino acids in leaves and roots [4, 12, 14]. Ref. [4] reported research conducted in the state of Minas Gerais, in which the increase of the dose of phosphate fertilization applied in the planting furrow resulted in higher N accumulation in the biomass of the plant-cane. In this case, for each kg of P applied, there was an increase of about 1 kg of N in biomass. These results are caused by changes in N uptake and metabolism, as reported by Refs. [1, 12, 14].
\nIn relation to the planting of sugarcane, an average bud density of 12–15 per meter of furrow is recommended, which is approximately 12–14 t of seedlings per ha. As mentioned previously, one should select good quality sugarcane seedlings (preferably from healthy nurseries) and of first or second cutting at most. It is also important to confirm seedling health in terms of diseases, pests and mixture of other cultivars. The arrangement of the sugarcane within the furrow should preferably be upright with one culm next to the other. The culms are then cut into billets with two or three side branches, which are subsequently covered with soil layer ranging from 5.0 to 8.0 cm and should not exceed 10 cm in thickness. Then, the herbicide application for weed control typically follows the planting of sugarcane.
\nWeeds compete with sugarcane during the growth phase for water, light, nutrients, and may exude phytotoxic compounds (allelopathy) and host pests and diseases [4, 15]. Sugarcane exhibits C4 metabolism, which makes it relatively more competitive in CO2 assimilation and nutrient use. However, several weeds are from the same family as is sugarcane and therefore have the same metabolism. At the time of harvest, the presence of weeds continues to cause damage, because when sugarcane is cut by hand and without previous burning, the presence of weeds decreases the workers’ efficiency and makes them more vulnerable to snake and scorpion bites. The longevity of the sugarcane plantation also decreases when weed control is not effective. In most cases, keeping the crop free from competition with weeds until the vegetation closes the spacing between the rows ensures the harvest of sugarcane without the presence of weeds.
\nThere are several techniques used for weed management. However, the combined use of cultural, mechanical, and chemical methods is the most common [4, 15]. Cultural methods are practices that aim to make sugarcane crop more competitive in relation to weeds and include reducing planting space, intercropping or crop rotation with soybean, peanut, corn, and green manure, as well as the use of high-tillering varieties for faster shading of the soil [4, 15]. In research conducted by the authors in areas heavily infested with Brachiaria, the sowing of
Plows and harrows are used in the mechanical control during the renewal of the sugarcane plantation. This method is highly efficient, but depends on soil moisture, solar radiation and the predominant species in the area. For weed control between the rows of sugarcane, animal traction plows can be used. Manual weeding, once used, has now been restricted to experimental areas. Mechanical cultivation has limitations, especially because it does not control the weeds of crop rows. Its efficiency in controlling weeds between crop rows may also be greatly reduced depending on the climatic conditions and species, such as some grasses of the
The use of herbicides to maintain the crop free from weed competition until the space between rows is closed generally guarantees sugarcane harvest without the presence of weeds.
Below are some considerations about herbicides commonly used in sugarcane cultivation.
\n\n
\n
\n
Action mechanism | \nApplication time | \nHerbicide (Brand) | \n
---|---|---|
\n | \n||
Oxyfluorfen | \nPre- or postemergence | \nGoal | \n
Sulfentrazone | \nPreemergence | \nBoral and Solara | \n
\n | \n||
Ametryn | \nPre- or postemergence | \nAmetryn, Gesapax, Herbipax, and Metrimex | \n
Atrazine | \nPre- or post-emergence | \nAtrazinex, Gesaprim, Atrazine, and Nortox | \n
Atrazine + Simazine | \nPre- or postemergence | \nExtrazin, Triamex, Primatop, and Herbimix | \n
Diuron | \nPre- or postemergence | \nKarmex, Diuron Nortox | \n
Ametryn + Diuron | \nPre- or postemergence | \nAmetron | \n
Hexazinone + Diuron | \nPre- or postemergence | \nVelpar K and Advance | \n
Metribuzin | \nPre- or postemergence | \nSencor | \n
Simazine | \nPreemergence | \nGesatop | \n
Tebuthiuron | \nPreemergence | \nCombine, Tebuthiuron | \n
\n | \n||
Alachlor | \nPreemergence | \nLaço | \n
Pendimethalin | \nPreemergence | \nHerbadox | \n
Trifluralin | \nPreemergence | \nTrifluralina Nortox, Treflan, and Premerlin | \n
\n | \n||
MSMA | \nPostemergence | \nDaconate, Dessecan | \n
\n | \n||
Flazasulfuron | \nPre- or postemergence | \nKatana | \n
Glyphosate | \nPostemergence | \nGlifosato, Roundup, and Trop | \n
Halosulfuron | \nPostemergence | \nSempra | \n
Imazapic | \nPre- or postemergence | \nPlateau | \n
Imazapyr | \nPre- or postemergence | \nArsenal, Contain e Chopper | \n
Trifloxysulfuron +Ametryn | \nPostemergence | \nKrismar | \n
\n | \n||
Clomazone | \nPreemergence | \nGamit | \n
Isoxaflutole | \nPreemergence | \nProvence | \n
Clomazone + Ametryn | \nPreemergence | \nSinerge, Ranger | \n
\n | \n||
2,4-D | \nPre- or postemergence | \nDMA | \n
Dicamba | \nPre- or postemergence | \nBanvel 480 | \n
Picloram +2,4-D | \nPre- or postemergence | \nDontor | \n
Main herbicides used in sugarcane and application times in relation to weed emergence.
\n
\n
\n
The fertilization of the regrowth of sugarcane recommended for small farmers is based on the recovery of nitrogen and potassium removed by harvesting the previous cut. In one ton of natural matter of sugarcane biomass (industrializable culms + dry leaves + green leaves + buds), there is 850 kg of industrializable culms on average. Thus, the average index of industrializable culms in biomass is 0.85. For each ton of sugarcane biomass exported from the plantation, 1.2 kg of nitrogen and 1.5 kg of potassium are removed [1, 4]. Assuming that the yield of the plant-cane was 150 t of biomass (about 120 t of industrializable culms), the application of 180 kg of nitrogen and 225 kg of potassium is recommended. There is no need to split fertilization for fear of leaching losses of both nitrogen and potassium [1].
\nIf sugarcane has been harvested for animal feed, the amount of dry leaves on the soil is small. Thus, burying the fertilizer between the crop rows is recommended. Urea can be used as the source of nitrogen in this case. If the fertilizer cannot be buried between the crop rows, ammoniacal or nitric sources should be used to fertilize the regrowth, because volatilization losses are very high when urea is applied over the straw. More detailed information on losses by volatilization and quantification of potassium in the profile of soil grown with sugarcane can be found in Ref. [1].
\nFeed | \n% de DM in manure | \nN | \nP | \nK | \nCa | \nM | \nS | \nK/N ratio | \n|
---|---|---|---|---|---|---|---|---|---|
Roughage | \nConcentrad feed (kg/cow/day) | \n. ------- g/kg of manure dry matter--------. | \n|||||||
Pasture | \n9.0 | \n14.1 | \n19.4 | \n14.4 | \n12.0 | \n13.9 | \n7.1 | \n3.5 | \n0,62 | \n
Corn silage | \n8.0 | \n13.9 | \n23.6 | \n10.0 | \n10.4 | \n10.5 | \n5.1 | \n3.1 | \n0,44 | \n
Corn silage | \n10.0 | \n11.7 | \n21.1 | \n10.9 | \n11.2 | \n11.6 | \n4.5 | \n3.4 | \n0,53 | \n
Corn silage | \n12.0 | \n12.9 | \n24.1 | \n11.2 | \n11.7 | \n12.3 | \n4.6 | \n3.6 | \n0,48 | \n
\n | Average | \n13.1 | \n22.0 | \n11.6 | \n11.3 | \n12.0 | \n5.3 | \n13.6 | \n0.52 | \n
Percentage of dry matter in dairy cattle manure (% DM in manure) and nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and sulfur (S) contents in manure of dairy cows fed with different roughage and quantities of concentrated feed.
The application of the fertilizer in regrowth using a walk-behind spreader has been traditional in small properties. It is of low cost and precise, which greatly increases the workers’ efficiency. A worker using a spreader covers more than 2.0 ha per day. The use of dairy cattle manure to fertilize sugarcane is a way to reduce production costs, recycle nutrients, and improve soil physical, chemical and biological properties. The efficiency of dairy cattle manure in the mineral nutrition of sugarcane depends on the chemical composition of the waste, the dose and environmental factors, especially temperature and soil moisture. The chemical analysis of cattle manure allows us to calculate the amounts that should be applied to the soil to restore the nutrients removed by harvesting. Table 7 shows the results of the chemical analysis of manure of dairy cattle fed with different roughage and amounts of concentrated feed. In harvesting 150 tons of forage (culms + side branches + leaves), 150, 45, and 225 kg of N, P, and K, respectively, were removed. The K/N ratio of forage is 1.5, which is much higher than that of cattle manure. Thus, if the sugarcane plantation is fertilized with cattle manure, it is necessary to supplement fertilization with potassium to replace nutrients removed with the harvest.
\nPoultry litter is another alternative for the organic fertilization of sugarcane. In recent years, this waste has had its demand and price reduced because of a ban on its use in cattle feed. The concentration of nutrients in poultry litter is influenced by the bedding material. Most poultry farmers of the Zona da Mata region use rice husk, coffee husk, napier grass, shavings, and corn cobs. Table 8 shows the nutrient contents of five poultry litters composed of different bedding materials collected after being used in a batch of broilers (48 days on average), at a density of 15 birds/m2.
\nThe authors evaluated the maturation and broth quality of the sugarcane variety RB867515, which were influenced by the fertilization with poultry litter. The study was conducted in three agricultural years: first, second, and third regrowth. The experiment was a randomized complete block design with four replicates. The treatments consisted of fertilization with three doses of poultry litter 7; 10 and 13 t of poultry litter dry matter/ha/yr), in addition to a control treatment (no chemical or organic fertilization), and chemical fertilization (180 kg N + 225 kg K/ha/yr). Sugarcane was harvested in early August in all 3 years. Fertilization of sugarcane with poultry litter did not interfere with maturation, nor did it affect broth quality, even at high doses. The difference in broth quality from 1 year to another was small. The average of the 3 years for soluble solid content, sucrose in the broth and broth purity were 22, 19, and 86%, respectively. Thus, the use of poultry litter is as an organic fertilizer is an alternative to chemical fertilization. Also, just as cattle manure, it should be supplemented with potassium, because the average K/N ration in poultry litter is 0.80.
\nPoultry litter | \nN | \nP | \nK | \nCa | \nMg | \nS | \n
---|---|---|---|---|---|---|
.------------------------ g/kg of DM-----------------------------. | \n||||||
Rice husk | \n34.7 a | \n15.9 b | \n26.8 b | \n25.7 a | \n6.2 a | \n16 ab | \n
Coffee husk | \n32.8 a | \n14.4 b | \n28.9 ab | \n25.0 a | \n5.5 b | \n15 b | \n
Napier grass | \n34.8 a | \n15.1 b | \n23.3 c | \n25.5 a | \n6.0 a | \n15 b | \n
Wood shavings | \n30.9 a | \n13.7 b | \n24.4 c | \n25.8 a | \n5.7 b | \n14 b | \n
Corn cob | \n34.2 a | \n18.6 a | \n29.7 a | \n28.3 a | \n6.7 a | \n18 a | \n
Average | \n33.5 | \n15.5 | \n26.6 | \n26.1 | \n6.0 | \n15.0 | \n
CV (%) | \n10.6 | \n12.2 | \n10.0 | \n6.6 | \n8.2 | \n10.1 | \n
Nutrients in dry matter (g/kg of DM) of poultry litter in which five different materials were used for bedding.
Means followed by the same letter in the column do not differ statistically from one another by the Tukey test at 5%. Source: Ref. [16].
The technologies recommended to the small farmers for the implantation and management of sugarcane plantations have resulted in high yields in the plant-cane cycle with small decreases in the subsequent cycles. Furthermore, the techniques proposed by the authors maximized the use of inputs, land, and human resources, thus reducing the operating costs.
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Furthermore, in this manner, understanding the systemic interaction between the cardiovascular and nervous systems has become more important than ever as human populations' life prolongation, aging and mechanisms of cellular oxidative signaling are utilised for sustaining life. \r\nAltogether, physiological research enables our identification of distinct and precise points of transition from health to the development of multimorbidity throughout the inevitable aging disorders (e.g., diabetes, hypertension, chronic kidney disease, heart failure, peptic ulcer, inflammatory bowel disease, age-related macular degeneration, cancer). 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Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,annualVolume:11411,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. 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He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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He has published research in Research Policy, Applied Economics, Review of Economic Philosophy, Strategic Change, International Journal of Logistics, Sustainability, Journal of Environmental Management, Journal of Global Information Management, Journal of Cleaner Production, M@N@GEMENT, and more. He is a member of CEDIMES Institut (France), Academy of International Business (AIB), Strategic Management Society (SMS), Academy of Management (AOM), Administrative Science Association of Canada (ASAC), and Canadian council of small business and entrepreneurship (CCSBE). He is currently the director of the Research Group on Contemporary Asia (GERAC) at Laval University. 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He is also a faculty member in the Molecular Oncology Program. He obtained his MSc and Ph.D. at Oregon State University and Texas Tech University, respectively. He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNVJQA4/Profile_Picture_2022-03-07T13:23:04.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals.",institutionString:null,institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Associate Prof.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. He has many national and international publications.",institutionString:"Integral University",institution:null},{id:"255360",title:"Dr.",name:"Usama",middleName:null,surname:"Ahmad",slug:"usama-ahmad",fullName:"Usama Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255360/images/system/255360.png",biography:"Dr. Usama Ahmad holds a specialization in Pharmaceutics from Amity University, Lucknow, India. He received his Ph.D. degree from Integral University. Currently, he’s working as an Assistant Professor of Pharmaceutics in the Faculty of Pharmacy, Integral University. From 2013 to 2014 he worked on a research project funded by SERB-DST, Government of India. He has a rich publication record with more than 32 original articles published in reputed journals, 3 edited books, 5 book chapters, and a number of scientific articles published in ‘Ingredients South Asia Magazine’ and ‘QualPharma Magazine’. He is a member of the American Association for Cancer Research, International Association for the Study of Lung Cancer, and the British Society for Nanomedicine. Dr. Ahmad’s research focus is on the development of nanoformulations to facilitate the delivery of drugs that aim to provide practical solutions to current healthcare problems.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. Dr. Khullar has a keen research interest in genetics of hypertension, and is currently studying pharmacogenetics of hypertension.",institutionString:"Post Graduate Institute of Medical Education and Research",institution:{name:"Post Graduate Institute of Medical Education and Research",country:{name:"India"}}},{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",biography:"Xianquan Zhan received his MD and Ph.D. in Preventive Medicine at West China University of Medical Sciences. He received his post-doctoral training in oncology and cancer proteomics at the Central South University, China, and the University of Tennessee Health Science Center (UTHSC), USA. He worked at UTHSC and the Cleveland Clinic in 2001–2012 and achieved the rank of associate professor at UTHSC. Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. He has published more than 148 articles, 28 book chapters, 6 books, and 2 US patents in the field of clinical proteomics and biomarkers.",institutionString:"Shandong First Medical University",institution:{name:"Affiliated Hospital of Shandong Academy of Medical Sciences",country:{name:"China"}}},{id:"297507",title:"Dr.",name:"Charles",middleName:"Elias",surname:"Assmann",slug:"charles-assmann",fullName:"Charles Assmann",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297507/images/system/297507.jpg",biography:"Charles Elias Assmann is a biologist from Federal University of Santa Maria (UFSM, Brazil), who spent some time abroad at the Ludwig-Maximilians-Universität München (LMU, Germany). He has Masters Degree in Biochemistry (UFSM), and is currently a PhD student at Biochemistry at the Department of Biochemistry and Molecular Biology of the UFSM. His areas of expertise include: Biochemistry, Molecular Biology, Enzymology, Genetics and Toxicology. He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. He has also been a reviewer of international journals and ad hoc reviewer of scientific committees from Brazilian Universities.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",country:{name:"Brazil"}}},{id:"217850",title:"Dr.",name:"Margarete Dulce",middleName:null,surname:"Bagatini",slug:"margarete-dulce-bagatini",fullName:"Margarete Dulce Bagatini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217850/images/system/217850.jpeg",biography:"Dr. Margarete Dulce Bagatini is an associate professor at the Federal University of Fronteira Sul/Brazil. She has a degree in Pharmacy and a PhD in Biological Sciences: Toxicological Biochemistry. She is a member of the UFFS Research Advisory Committee\nand a member of the Biovitta Research Institute. She is currently:\nthe leader of the research group: Biological and Clinical Studies\nin Human Pathologies, professor of postgraduate program in\nBiochemistry at UFSC and postgraduate program in Science and Food Technology at\nUFFS. She has experience in the area of pharmacy and clinical analysis, acting mainly\non the following topics: oxidative stress, the purinergic system and human pathologies, being a reviewer of several international journals and books.",institutionString:"Universidade Federal da Fronteira Sul",institution:{name:"Universidade Federal da Fronteira Sul",country:{name:"Brazil"}}},{id:"226275",title:"Ph.D.",name:"Metin",middleName:null,surname:"Budak",slug:"metin-budak",fullName:"Metin Budak",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226275/images/system/226275.jfif",biography:"Metin Budak, MSc, PhD is an Assistant Professor at Trakya University, Faculty of Medicine. He has been Head of the Molecular Research Lab at Prof. Mirko Tos Ear and Hearing Research Center since 2018. His specializations are biophysics, epigenetics, genetics, and methylation mechanisms. He has published around 25 peer-reviewed papers, 2 book chapters, and 28 abstracts. He is a member of the Clinical Research Ethics Committee and Quantification and Consideration Committee of Medicine Faculty. His research area is the role of methylation during gene transcription, chromatin packages DNA within the cell and DNA repair, replication, recombination, and gene transcription. His research focuses on how the cell overcomes chromatin structure and methylation to allow access to the underlying DNA and enable normal cellular function.",institutionString:"Trakya University",institution:{name:"Trakya University",country:{name:"Turkey"}}},{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",biography:"Anca Pantea Stoian is a specialist in diabetes, nutrition, and metabolic diseases as well as health food hygiene. She also has competency in general ultrasonography.\n\nShe is an associate professor in the Diabetes, Nutrition and Metabolic Diseases Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania. She has been chief of the Hygiene Department, Faculty of Dentistry, at the same university since 2019. Her interests include micro and macrovascular complications in diabetes and new therapies. Her research activities focus on nutritional intervention in chronic pathology, as well as cardio-renal-metabolic risk assessment, and diabetes in cancer. She is currently engaged in developing new therapies and technological tools for screening, prevention, and patient education in diabetes. \n\nShe is a member of the European Association for the Study of Diabetes, Cardiometabolic Academy, CEDA, Romanian Society of Diabetes, Nutrition and Metabolic Diseases, Romanian Diabetes Federation, and Association for Renal Metabolic and Nutrition studies. She has authored or co-authored 160 papers in national and international peer-reviewed journals.",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",country:{name:"Romania"}}},{id:"279792",title:"Dr.",name:"João",middleName:null,surname:"Cotas",slug:"joao-cotas",fullName:"João Cotas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279792/images/system/279792.jpg",biography:"Graduate and master in Biology from the University of Coimbra.\n\nI am a research fellow at the Macroalgae Laboratory Unit, in the MARE-UC – Marine and Environmental Sciences Centre of the University of Coimbra. My principal function is the collection, extraction and purification of macroalgae compounds, chemical and bioactive characterization of the compounds and algae extracts and development of new methodologies in marine biotechnology area. \nI am associated in two projects: one consists on discovery of natural compounds for oncobiology. The other project is the about the natural compounds/products for agricultural area.\n\nPublications:\nCotas, J.; Figueirinha, A.; Pereira, L.; Batista, T. 2018. An analysis of the effects of salinity on Fucus ceranoides (Ochrophyta, Phaeophyceae), in the Mondego River (Portugal). Journal of Oceanology and Limnology. in press. DOI: 10.1007/s00343-019-8111-3",institutionString:"Faculty of Sciences and Technology of University of Coimbra",institution:null},{id:"279788",title:"Dr.",name:"Leonel",middleName:null,surname:"Pereira",slug:"leonel-pereira",fullName:"Leonel Pereira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279788/images/system/279788.jpg",biography:"Leonel Pereira has an undergraduate degree in Biology, a Ph.D. in Biology (specialty in Cell Biology), and a Habilitation degree in Biosciences (specialization in Biotechnology) from the Faculty of Science and Technology, University of Coimbra, Portugal, where he is currently a professor. In addition to teaching at this university, he is an integrated researcher at the Marine and Environmental Sciences Center (MARE), Portugal. His interests include marine biodiversity (algae), marine biotechnology (algae bioactive compounds), and marine ecology (environmental assessment). Since 2008, he has been the author and editor of the electronic publication MACOI – Portuguese Seaweeds Website (www.seaweeds.uc.pt). He is also a member of the editorial boards of several scientific journals. Dr. Pereira has edited or authored more than 20 books, 100 journal articles, and 45 book chapters. He has given more than 100 lectures and oral communications at various national and international scientific events. He is the coordinator of several national and international research projects. In 1998, he received the Francisco de Holanda Award (Honorable Mention) and, more recently, the Mar Rei D. Carlos award (18th edition). He is also a winner of the 2016 CHOICE Award for an outstanding academic title for his book Edible Seaweeds of the World. In 2020, Dr. Pereira received an Honorable Mention for the Impact of International Publications from the Web of Science",institutionString:"University of Coimbra",institution:{name:"University of Coimbra",country:{name:"Portugal"}}},{id:"61946",title:"Dr.",name:"Carol",middleName:null,surname:"Bernstein",slug:"carol-bernstein",fullName:"Carol Bernstein",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/61946/images/system/61946.jpg",biography:"Carol Bernstein received her PhD in Genetics from the University of California (Davis). She was a faculty member at the University of Arizona College of Medicine for 43 years, retiring in 2011. Her research interests focus on DNA damage and its underlying role in sex, aging and in the early steps of initiation and progression to cancer. In her research, she had used organisms including bacteriophage T4, Neurospora crassa, Schizosaccharomyces pombe and mice, as well as human cells and tissues. She authored or co-authored more than 140 scientific publications, including articles in major peer reviewed journals, book chapters, invited reviews and one book.",institutionString:"University of Arizona",institution:{name:"University of Arizona",country:{name:"United States of America"}}},{id:"182258",title:"Dr.",name:"Ademar",middleName:"Pereira",surname:"Serra",slug:"ademar-serra",fullName:"Ademar Serra",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/182258/images/system/182258.jpeg",biography:"Dr. Serra studied Agronomy on Universidade Federal de Mato Grosso do Sul (UFMS) (2005). He received master degree in Agronomy, Crop Science (Soil fertility and plant nutrition) (2007) by Universidade Federal da Grande Dourados (UFGD), and PhD in agronomy (Soil fertility and plant nutrition) (2011) from Universidade Federal da Grande Dourados / Escola Superior de Agricultura Luiz de Queiroz (UFGD/ESALQ-USP). Dr. Serra is currently working at Brazilian Agricultural Research Corporation (EMBRAPA). His research focus is on mineral nutrition of plants, crop science and soil science. Dr. Serra\\'s current projects are soil organic matter, soil phosphorus fractions, compositional nutrient diagnosis (CND) and isometric log ratio (ilr) transformation in compositional data analysis.",institutionString:"Brazilian Agricultural Research Corporation",institution:{name:"Brazilian Agricultural Research Corporation",country:{name:"Brazil"}}}]}},subseries:{item:{id:"26",type:"subseries",title:"Machine Learning and Data Mining",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. 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