Percentage of total yield of dry matter at first cut, occupied by leaf, edible stem, nonedible stem, and edible/nonedible ratio, of four accessions of
Pastures in the coast of the Gulf of Mexico are characterized by native species (Paspalum spp., Axonopus spp., etc.). These, are limited by productivity due to their low nutritional quality and poor persistence on grazing. The adaptation of new grass and legume species is essential to improve the productivity of animal production. An initial assessment should include the climatic and edaphic adaptation to the region. Species, such as Andropogon gayanus, Pueraria phaseoloides, Centrosema spp., Arachis pintoi, and Cratylia argentea, were evaluated, showing encouraging results compared to native species; our efforts were focused on C. argentea. Several research methods were applied to meet the objectives outlined for each experiment, including methodologies for the establishment of new species. All these trials were subject to rigorous experimental designs, and data were analyzed statistically, using the most adequate programs. These experiences allow us to visualize the most promising materials for the specific conditions of climate and soil. The potential results of this new forage species stand out. Also, these experiments allowed the development of new management practices to improve the productivity of the animal production systems of the region. C. argentea demonstrated its high forage value as a species suitable for silvopastoral systems.
- tropical pastures
- edaphic and climatic adaptation
- Cratylia argentea
Livestock in the tropical region of Mexico has pastures composed of
Due to this problem, it is necessary to find forages that adapt to these critical times. There are some legume species adapted to the conditions of the dry season, which have already been tested in other tropical regions of Latin America , so it is possible that some of them could be established in the central region in the state of Veracruz (Mexico).
Tropical forage legumes could be alternative solutions to these problems, since they present high nutritional quality and can also fix N to the soil, which, over time, becomes available to the associated grasses, increasing the production of pastures. Moreover, legumes in association with grasses can increase the amount of charcoal sequestered by pastures [5, 6]. Therefore, these plants can contribute to diminish the negative impact that the pastoral industries have on the environment.
Species, such as
2. First evaluations of
C. argenteaunder cutting regime
2.1. Total dry matter and nutritive quality of four
C. argenteaaccessions after a year of the establishment period
For this reason, it is speculated that it is necessary to evaluate—in a first stage—the production of edible fodder as well as the secondary aspects, such as inedible biomass production, which could be an energy source.
2.1.2. Materials and methods
The objective of this experiment was to evaluate—under conditions of warm and humid climate and acid soils—the forage yield and the nutritive quality of the accessions of
The study was carried out at the F1 Heifer Production Unit of the Center for Teaching, Research and Extension in Tropical Livestock (CEIEGT, its acronym in Spanish), Faculty of Veterinary Medicine and Animal Husbandry, National Autonomous University of Mexico. The unit is located in the municipality of Atzalan, state of Veracruz (Mexico), at 20°02ʹ N latitude, 97°34ʹ W length and 111 m above sea level.
The minimum and maximum temperature averages, in addition to rain, during the experimental period were 20.0, 30.4°C, and 1.926 mm, respectively. The soil texture in the first 20 cm is 52, 28, and 20% clay, silt, and sand, respectively, with an acidity of pH 4.7 and with low total N (0.983 g⋅kg−1), extractable P (0.04 cmol⋅kg−1), extractable K (1.45 cmol⋅kg−1), and cation exchange capacity (11.95 cmol⋅kg−1).
The experimental area was cultivated in a conventional manner, and sowing, using seed, was performed on September 1, 2006. The spacing between furrows and sowing sites was 1 m each. The first harvest of forage was made from August 23–27, 2007 at a cutting height of 70 cm. The experimental design was a randomized complete blocks, using the slope as criteria to block, with three blocks as repetitions.
The plant parts analyzed were leaves (L), edible stems (ES, <3 mm diameter), and nonedible stems (NES, >3 mm diameter). Plants were dried at 60°C, and milled at 2 mm. Samples used for gas in vitro methodology were milled at 1 mm.
Chemical analyses were performed for crude protein (CP, %); Kjeldahl . The methodology of Van Soest et al.  was used for determining neutral detergent fiber (NDF, %), acid detergent fiber (ADF, %), and lignin (LIG, %).
The in situ disappearance (ISD, %) of leaves at 3, 6, 9, 12, 24, 48, and 72 h of ruminal incubation was done in triplicate in three rumen-fistulated cows using the nylon bag technique , without pretreatment with pepsin in acid medium. The time-out disappearance was estimated in duplicate, washing with water at 38°C for 30 min.
The data were adjusted to the model proposed by these same authors: y = a + b (1 − e (−c * t)), where “y” is the dry matter (%) degraded at time t, “a” is the highly soluble dry matter when t = 0, “b” is the slowly degradable (%) dry matter, “a + b” is the extent of digestion (%), “c” is the fractional rate of degradation of “b” (fraction/h), and “t” is the incubation time in the rumen (h).
The kinetics of in vitro gas production of edible leaves and stems was evaluated . The generated data were adjusted to the exponential equation of Krishnamoorthy et al. : y = b (1−e−c * (x−L)), where “y” (ml) is the accumulated gas production at time “x” (h), “B” is the asymptote or potential gas production accumulated as “x” → J (ml), “C” is the fractional rate at which gas production accumulates at time “x”, and “L” is the lag time (the time h, that takes the ruminal microbes to colonize and initiate gas production from the NDF of slow degradability).
In order to meet the assumptions of the analysis of variance, the percentage units were transformed to “arcsin √%/100” and the consumable material ratio (L + ES) 84 to nonconsumable stems (NES), which is dimensionless, was transformed to values of “natural log of y + 1”. The model of analysis of variance had the effects of block as a repetition (the cow confused with the block in the case of ISD), accession, component of the plant, and the interaction accession × plant component. Proc GLM of SAS was used to perform analyses. LS means option was used to generate minimum squares means and comparisons between them .
The accession had no significant effect on the dry matter yield at the first cut of the L, ES, and NES components, which showed mean ± standard errors of 2580 ± 212, 33 ± 5, and 2444 ± 233 kg/ha, respectively. In contrast, the proportions of nonedible leaves and stems were significantly affected by the accession ( Table 1 ). CIAT 18668 showed the highest HO ratio, which was not statistically different from CIAT 18516 and 18676, but statistically superior to CIAT 18666, which was the lowest of all accessions.
|CIAT accession||Leaf||Edible stem||Nonedible stem||Edible/onedible|
|18516||48.96 ab||0.78 a||50.25 ab||0.99 ab|
|18666||45.92 b||0.66 a||53.40 a||0.88 b|
|18668||56.35 a||0.59 a||43.03 b||1.32 a|
|18676||54.65 ab||0.45 a||44.89 ab||1.23 ab|
From the effects of the model, only the component of the plant was significant (
With respect to the ISD of the leaf component, the effect of the block was not significant on “a” and “b”, but it was on the “c” fractional rate. The effect of the accession was significant only on “a”, but not on the other parameters. Likewise, neither the effect of the cow or the accession × cow interaction affected the parameters.
The average coefficient of determination of the individual curves was 0.8970 with a standard error of ± 0.0222. Therefore, the accessions only differed in the proportion of the highly soluble component of the dry matter: 29.97, 30.06, 33.15, and 31.32% for CIAT 18516, 18666, 18668, and 18676, respectively; 18668 being significantly higher than the others, which did not differ from each other; while all had a common fractional degradation rate (0.0488 ± 0.0192 per hour) of the slowly degradable dry matter component (30.60% ± 4.52%), as shown in Figure 1 .
The parameters of this model  were not affected by the block, accession, or the interaction accession × component of the plant. The fit of the individual curves was quite good, given that the average of the determination coefficients was 0.9907 with a standard error of ± 0.0070. Therefore, a single curve could be used to describe the dynamics of in vitro gas production of the four accessions, which is presented in Figure 2 , where it is also shown that the effect of the plant component was significant on all the parameters.
The average dry matter yield of leaves, edible stems, and nonedible stems were statistically the same. The proportion of leaves was higher in CIAT 18668 than in CIAT 18666, which showed the lowest leaves ratio. The average dry matter yield of leaves, edible stems, and nonedible stems were statistically the same. On the other hand, CIAT 18516 and CIAT 18676 were similar to CIAT 18668, implying that the first two would be as good candidates to be selected as the latter ( Table 1 ). In summary, the dry matter yield variables and the derived variables were only useful in selecting the least productive accession.
After nearly 12 months of uninterrupted growth, 51.50% of the aerial biomass were leaves, which resulted in a ratio of 1.1:1 with respect to edible material:nonedible stems. In Costa Rica,
In the present study, the chemical composition of
|Botanical component||Chemical variables, %|
The accessions were statistically similar with respect to their contents of crude protein, neutral detergent fiber, acid detergent fiber, and lignin. The leaves in this aspect exceeded the edible stems. In fact, since the contribution of the edible stems to the total dry matter yield was so small, only leaf yield should be considered to select the best accession.
Regarding the in situ dry matter degradability, of leaves and young stems, no statistical effect of the age of harvest on this variable was found. An experiment  reported that the parameter values model  for 2, 3, and 4 months of age were, respectively: for “a”, 31.30, 28.20, and 24%; for “b”, 30.30, 24.40, and 26.50%; for “c”, 0.08, 0.08, and 0.07 per hour. The values of “a” and “b” are very similar to those of the present study ( Figure 1 ), whereas those of “c” are higher by about 0.03 units; the difference may have been due to the higher proportion of mature leaves in the present experiment, in which the plants were harvested at an advanced stage of maturity.
The gas production dynamics were different between leaves and edible stems, the former having a lower gas production potential and fractional rate than the latter. Leaf tannins are known to interfere with the amount and rate of gas production . Therefore, the leaves are digested at a slower rate and to a lesser extent than the young stems.
On the other hand, the two bioassays made in the edible material did not show any practical or statistical differences between accessions in terms of the in situ degradation of the dry matter or the in vitro gas production dynamics ( Figures 1 , 2 ).
None of the accessions was superior to the others. The four accessions of
2.2. Performance of
C. argenteaduring three climatic seasons and several ages of cutting2
The use of shrub legumes with high nutritional quality that can thrive at the time of year when most grasses do not becomes an alternative to address the shortage of food in the dry period. However, not all the forage trees or shrubs yield enough amounts of biomass to feed cattle. The age of regrowth and climatic seasons are documented to affect the yield and forage quality of woody forage species .
Cutting forage trees at different seasons of the year (dry season vs. wet season) and at different stages of development (flowering vs. vegetative) may also influence subsequent regrowth. Many studies have reported that the highest total biomass yield is obtained in the longer harvest intervals. Accessions CIAT 18674 and CIAT 22406 were identified as promising for DM production, particularly in the dry season. In Quintana Roo, Mexico, an experiment  was carried out, evaluating several legumes. Among them
2.2.2. Materials and methods
This experiment was carried out at the same site as that described previously, and the climatic conditions are shown in Figure 3 .
On September 1, 2006, four forage accessions of
To analyze the harvested material in the laboratory, leaves (leaflets and petiole) and stems up to 3 mm were separated. These parts of the plant are considered the consumable material by cattle. Samples of these materials were analyzed to determine the percent dry matter (DM), crude protein , neutral detergent fiber (NDF), acid detergent fiber (ADF), and lignin (LIG) . Also, DM yield was calculated . In situ dry matter digestion was estimated, with incubation times of 3, 6, 9, 12, 24, 48, and 72 h ; degradation parameters were obtained by fitting the data to a model where, y = a + b (1 − e − ct), where y = DM degraded at time “t” (%), a = rapidly degradable fraction (intercept) (%), b = slowly degradable fraction (%), a + b = potentially degradable DM (extent of degradation) (%), c = rate of degradation (degradable fraction per hour), t = time of incubation in the rumen (h), and e = base of the natural logarithms .
A randomized complete block design and three replications (blocks) were applied as the experimental design for this experiment. We used the slope of the terrain as a criterion for blocking. Also, we assigned four plots (one per accession) to each one of the blocks. PROC MIXED of Statistical Analysis System  was performed for the ANOVA. The exponential growth model: y = aebx, where y = DMY (kg⋅ha−1), a = DMY when x = 0, b = rate constant expressed in inverse x units (1⋅x−1), x = age of regrowth in weeks, was used to adjust data. Also, for each season, a fitting process was done. Dry matter yield and quality variables were analyzed with PROC MIXED; and ANOVA with least squares means “t” test comparisons was performed. For ISDMD, a particular curve for each combination of accession and regrowth age was fit, so each parameter could be analyzed individually as the response variable in the analysis of variance.
2.2.3. Results and discussion
22.214.171.124. Estimations of dry matter yield for average age of regrowth corresponding to each season
For DMY, the analysis of variance resulted with statistical differences (
|Average 6–15 weeks|
|Rainy||2289 ± 374||3011 ± 358||2608 ± 278||2552 ± 486|
|Exponential growth model: Y = 842e0.1026, R2* = 0.50, RSE = 937, n = 48|
|Winter||1396 ± 245||2106 ± 411||1495 ± 298||1930 ± 314|
|Exponential growth model: Y = 440e0.1256, R2 = 0.45, RSE = 840, n = 46|
|Dry||3248 ± 544||4026 ± 721||3544 ± 620||3711 ± 610|
|Exponential growth model: Y = 873e0.1278, R2 = 0.56, RSE = 1415, n = 48|
In the dry season,
126.96.36.199. Crude protein content by season and age of regrowth
Levels of crude protein in
|Season||Cutting age (weeks)||18516||18666||18668||18676|
|Rainy||6||25.1±0.5 a||24.5±0.5 a||23.5±0.3 a||25.0±0.8 a|
|9||22.6±0.9 ab||22.9±0.5 a||23.2±0.6 a||22.9±0.8 a|
|12||20.7±0.3 b||21.9±0.4 a||21.5±0.2 a||20.7±1.1 b|
|15||20.6±0.4 b||21.0±0.2 a||20.7±0.2 a||21.9±1.1 a|
|Winter||6||24.5±1.3 a||24.2±0.9 a||24.6±0.5 a||25.1±0.3 a|
|9||27.7±0.5 a||27.5±0.5 a||28.3±0.4 a||27.8±0.3 a|
|12||26.3±0.4 a||25.6±0.5 a||27.9±0.3 a||26.3±0.7 a|
|15||25.7±1.0 a||26.7±1.2 a||26.1±1.7 a||26.6±0.6 a|
|Dry||6||23.5±0.1 ab||24.1±0.3 b||23.6±0.1 b||24.1±0.5 b|
|9||23.4±0.4 ab||22.4±0.5 b||21.7±0.3 b||21.8±0.5 b|
|12||20.0±0.7 b||31.5±1.5 a||26.0±2.3 ab||30.8±0.2 a|
|15||29.1±0.8 a||30.9±0.7 a||31.0±0.5 a||30.2±0.2 a|
The content of crude protein shown here are different or similar to those found by other researchers. In Colombia (Antioquia) researchers reported that during dry season, the height of cutting and age of regrowth did not affect the content of CP, resulting in a small range of values: 191–207 g⋅kg−1 .
In the department of Cauca, Colombia (1800 mm annual rainfall), 38 accessions of
188.8.131.52. NDF, ADF, and lignin according to season and regrowth age
Mean contents of NDF, ADF, and LIG related to season and age of regrowth are shown in Table 5 . The responses of these variables to regrowth age were determined by the season. The NDF content at regrowth age from 6 to 12 weeks was similar; and an increase close to 6% units was registered at 15 weeks of regrowth. This variable showed ups and downs during the winter season: at the age of 3 weeks of regrowth, the NDF content was lower, followed by an increase of 7% units in 6 and 9 weeks of regrowth; after that, a decrease around 3% units at 15 weeks of regrowth was recorded. Neither ADF nor LIG increased, as expected, due to the effect of regrowth age pattern. This response is similar to the results found by other authors  during the rainy season, where NDF and ADF were lower (42 and 26%) with respect to the dry period (43 and 29%). These results indicated that the climatic season affected the quality of the plants.
|Season||Variable (%)||Harvesting age (weeks)|
|Rainy||NDF||56.7 ± 1.1b||55.5 ± 0.2b||55.9 ± 0.2b||61.8 ± 1.2a|
|ADF||35.7 ± 0.8b||35.5 ± 0.3b||36.9 ± 0.4b||41.8 ± 1.0a|
|LIG||14.8 ± 0.8b||18.5 ± 0.2a||18.0 ± 1.0ab||20.6 ± 0.5a|
|Winter||NDF||58.7 ± 0.7c||65.4 ± 0.9a||65.6 ± 0.5a||62.3 ± 1.1b|
|ADF||49.5 ± 0.6a||42.6 ± 0.6b||47.2 ± 1.0a||40.4 ± 0.8b|
|LIG||26.0 ± 1.0a||22.6 ± 0.4ab||26.9 ± 1.2a||19.2 ± 0.7b|
|Dry||NDF||65.5 ± 0.8bc||64.2 ± 0.6c||67.4 ± 1.0ab||69.3 ± 1.0a|
|ADF||46.5 ± 0.8a||48.8 ± 0.4a||48.6 ± 0.9a||47.4 ± 1.4a|
|LIG||24.3 ± 0.6a||24.7 ± 0.3a||23.3 ± 1.5a||23.8 ± 0.7a|
184.108.40.206. Degradation kinetics of dry matter of leaves and stems
In general, the model parameters of degradation , namely the rapidly degradable fraction (a), slowly degradable fraction (b), potentially degradable DM (a + b fractions), and the rate of degradation (c), were not affected by accession, week, or their interaction (
A value of 36% was reported by other authors for “a”, however, other legume species showed values from 29 to 60% . Other researchers have reported similar values in tropical native woody legumes . Also, degradation rate values (c) coincide with the range of 7–8%, reported by other authors .
Figure 4 shows the degradation kinetics of dry matter (leaves + stems < 3 mm) in the rumen, according to the described model , for accessions, harvest ages, and ages. During the rainy season, degradation per accession and per week has a very similar pattern, reaching for both cases a value of 66 and 65%, respectively, at 72 h. Considering the age of 9 weeks, a more accelerated degradation was observed during the first 6 h of incubation. A slight variation for accessions and age of regrowth was observed during the winter period. The accessions CIAT 18668 and 18676 highlighted over the rest, but the trend for regrowth age was as expected, and higher digestibility values were presented at 9 (R2 = 0.96) weeks. During the rainy and dry seasons, 48 h in situ DM degradability values for both accessions and regrowth ages were above 60%. Values lower than 35% in leaves of
- Data from this experiment were already published by: Castillo-Gallegos E., Estrada -Flores J.G., Valles-de la Mora B., Castellan-Ortega O.A., Ocaña-Zavaleta E., y Jarillo-Rodríguez J. 2013. Rendimiento total de materia seca y calidad nutritiva de hojas y tallos jóvenes de cuatro accesiones de Cratylia argentea en el trópico húmedo de Veracruz, México. Avances en Investigación Agropecuaria (México), 17(1):79-93. ISSN:0188789-0.
- Data presented here are taken from: Valles-De la Mora, B., Castillo-Gallegos, E., Ocaña-Zavaleta, E., & Jarillo-Rodríguez., J.2014. Cratylia argentea: A potential fodder shrub in silvopastoral systems. Yield and quality of accessions according to regrowth ages and climatic seasons, Revista Chapingo Serie Ciencias Forestales y del Ambiente, XX(2) 277-293. http://dx.doi.org/10.5154/r.rchscfa.2013.11.040.