Open access peer-reviewed chapter

Genetic Interaction and Inheritance of Physiobiochemical Traits Can Predict Tolerance of Maize to Water-Deficit Stress

Written By

Mozhgan Shirinpour, Ehsan Atazadeh, Ahmad Bybordi, Ashkboos Amini and Hassan Monirifar

Submitted: 28 December 2022 Reviewed: 13 April 2023 Published: 06 December 2023

DOI: 10.5772/intechopen.111599

From the Edited Volume

Climate Change - Recent Observations

Edited by Terence Epule Epule

Chapter metrics overview

31 Chapter Downloads

View Full Metrics

Abstract

One of the most critical environmental factors for plant growth is water deficiency and it can be anticipated that climate change will exacerbate this problem in the future. Plants have evolved a variety of different mechanisms at morphological, physiological, cellular, and biochemical levels to overcome water stress conditions. Maize is one of the three leading global cereals, which helps to feed the world. Several biometrical techniques, that is, North Carolina Model, generation mean analysis, diallel and line × tester, are available for genetic analysis. An effective breeding strategy for developing water-deficit tolerant varieties considerably depends on knowledge of the inheritance mechanism of the stress tolerance in maize, high broad-sense heritability and additive genetic variance for the characters which are contributing to drought tolerance. Thus, this study aims toward to explore the inheritance of physio-biochemical traits that lead to increase stress tolerance in maize under the water deficit conditions. This also exhibited a differential pattern of gene action for these traits, suggesting that genotypes possess significant differences for physio-biochemical traits that help to resistance of maize against water deficit stress. Our findings open a door to achieve higher yield of maize under drought stress. These insights might be useful to the plant breeders and farmers for developing water-deficit tolerant maize varieties, and morphological and physio-biochemical markers.

Keywords

  • gene action
  • heritability
  • maize (Zea mays L.)
  • physiobiochemical traits
  • water deficit

1. Introduction

The simulation results suggest that climate variability including storms, flooding, and other extreme weather with increases of temperature may ultimately disrupt crop yield [1]. By century’s end, climate change with temperature increases could reduce 11–25% global crop productions [2]. Growth in the temperature and global population can result in shortage of water reserves [3]. Moreover, weather forecast uncertainty will result in decrease of precipitation and increase of evapotranspiration relatively [4]. These factors can lead to drought and reductions in growth and crops yield. One of the main economic solution to increase stability in the production of agricultural products is the genetic modification of plants to withstand abiotic stresses [5]. Therefore, improving crops productivity under deficit irrigation is crucial and needed to ensure food security [6, 7].

As staple food, maize is an important cereal crop and main source of food security which plays a major role in the diets of millions of individuals, fodder, and bioenergy production in the world [8]. Drought stress as the most limitations to productivity of crops than any other abiotic stresses, substantially determines the maize production [9]. Maize is extremely sensitive and vulnerable to water-deficit stress at different growth and development stages that cause great yield reductions during grain fill [10]. Annually, 15–20% of maize production decreases due to climate change and drought. According to FAO statistics [11], maize production in 2016 decreased by 31% in comparison to 2015 due to drought stress and because of many problems of the global climate change and the expansion of maize yield under drought stress conditions. The development of drought-tolerant maize varieties are of high priority in plant breeding and crop science [12].

The knowledge inheritance of various morphological, biochemical, molecular, and physiological mechanisms of the drought maize tolerance is a key breeding strategy and helps the resistance of maize varieties against water-deficit stress [1314]. Water-stress tolerance is a complex quantitative trait that is controlled by many microeffective genes [15]. Relevant physiological traits include chlorophyll concentration, relative water content, leaf chlorophyll index, photosynthetic pigments, as well as biochemical traits such as protein content, synthesis of osmolytes, various enzymatic antioxidants, polyphenol oxidase which alters in response to drought and helps resistance of crops against stress [16, 17]. Breeders estimate the effects of genes controlling inheritance of traits in breeding populations, using different mating designs. According to the types of genetic material, the power of estimating additive, dominance, and epistasis gene effects are different [18]. Estimation of variance components of traits (additive, dominance, and epistasis) is important to determine which breeding method can optimize gene action more efficiently to recognize the need to produce hybrids or pure-line varieties [19, 20]. Additionally, levels of the additive effect and dominance degree are very important in designing a plant breeding for improving the trait of interest. Efficiency of selection majority depends on additive genetic variance, the environment, and the genotype × environment interaction effects and this encourages the breeders to understand to what extent the variation is heritable and how much of this variation is usable genetically. Knowledge of interact and gene act determine which breeding system can improve gene action and illustrate the role of this system in the crop plants evolution.

The main objective of this chapter was to determine the genetic control of various physiobiochemical traits which alter in response to water deficit and help the resistance of maize against stress. The knowledge of the physiobiochemical traits can be used to explore new genotypes of maize to increase grain yield under water stress conditions. The genetic component studies, inheritance pattern, and involvement of nonadditive, additive, and maternal genetic effects about various physiobiochemical traits were observed under water-deficit stress conditions. The obtained results will provide a source of potential genetic resources and inheritance patterns, which may be further studied to develop water-deficit tolerance maize varieties and, morphological and physiobiochemical markers.

Advertisement

2. Methods

Various biometrical techniques, that is, North Carolina Model, generation mean analysis, diallel, and line × tester design could be used for understanding of gene action controlling of different plant traits. These methods give information on the importance of average additive and dominance gene effects in determining genotypic values of the generations. Among these, generation mean analysis is the one which determines the type of epistasis (nonallelic gene actions) at digenic level using scaling test, accurately and efficiently [20]. In other words, generation mean analysis model in addition to estimating the genetic parameters viz. mean, additive gene effects, and dominance gene effects, determines three types of nonallelic gene interactions viz. additive × additive, additive × dominance, and dominance × dominance [19]. In this method, the overall average for each trait is shown as follows:

Y=m+α[d]+β[h]+α2[i]+αβ2[j]+β2[l]E1

where Y: the generation means, m: F∞ metric, d: additive effects, h: dominance effects, i: additive × additive interaction, j: additive × dominance interaction, 1: dominance × dominance interaction, and α, 2αβ and β2: coefficients of genetic parameters. All genetic parameters are tested using a t-test for significance. Then additive variance (VA), dominance variance (VD), and environmental variance (VE) are obtained as follows [19]:

VA=2VF2-VBC1-VBC2E2
VD=4(VBC1+VBC2-VF2-VE)E3
VE=0.25(VP1+VP2+2VF1)E4

Broad sense (hbs2) and narrow sense (hns2) heritability are estimated using the following equations:

hbs2=(VA+VD)/(VA+VD+VE);hns2=(VA)/(VA+VD+VE)E5

The North Carolina (NC) mating designs permit determination and/or estimation of variance components (additive and dominance components) by using the information from half-sib families. The experimental material of North Carolina designs I, II, and III is developed from F2 generation as a base material. The design III (NCIII) involves backcrossing the F2 plants to the two parental inbred lines from which the F2 were derived. The NCIII design was extended to include a third tester. This third tester is the F1 from the two parental inbred lines: in this extended form, this design is known as the triple test cross [21]. Line x Tester mating design uses inbred lines as the base population. The design is useful in deciding the relative ability of a number of female and male inbreds to produce desirable hybrid combinations [22]. When the same parents are used as females and males in breeding, the mating design is called diallel. Parents used the range from inbred lines to broad genetic base varieties to clones. The design is the most commonly used in crop plants to estimate general combining ability (GCA) and specific combining ability (SCA) and variances. Analysis of the diallel for GCA and SCA are based on the Model I, which is proposed by Griffing [23]. The GCA/SCA ratio reveals that different characteristics show an additive or nonadditive gene action. AGCA/SCA ratio with a value greater than one indicates additive gene action, whereas a GCA/SCA ratio with a value lower than one indicates dominant gene action. Furthermore, high additive gene action indicates higher heritability and fewer environmental influences [24].

Advertisement

3. Water deficit as the most serious abiotic stress

Among all other abiotic stresses (such as floods, salinity, temperature extremes, heavy metals), water deficit or drought is a significant restricting factor for global agricultural production. Additionally, drought stress is a primary limitation effecting crop yield due to complexity of fresh water limiting and climate change [2526]. Water stress occurs when turgor and water potential are reduced to the point where they disorder normal metabolic functions and reproductive capacity of plants [27]. Drought severity depends on several variables, for example, precipitation rate and distribution, evaporative demands and water-maintaining ability of soils [28]. Drought is predicted to become severe owing to global warming, low precipitation, and high evaporation particularly in arid and semiarid regions due to climate change [29]. Moreover, depletion of available water resources, growing world population rise, increasing food demand and climate changes cause water availability less predictable in many areas that exacerbate impacts of drought on global agriculture [30]. Therefore, water scarcity has become a great concern and brought more and more investigations on the drought-resistant crops and knowledge of the water-saving mechanisms of plants under water limitation conditions, especially in arid and semiarid environments [31]. Variety of physiological, biochemical, morphological, and molecular traits of the plants are impaired in water-limiting environments [32].

Water deficit significantly reduces development, grain yield, and yield components of maize at vegetative and reproductive growth stages [33]. Since the heritability of grain yield is low and strongly influenced by the environment, direct selection for it in the different generations is unreliable. Taking this matter into consideration, it is essential for breeders to identify traits that have high heritability, high correlation with grain yield, and low-cost measurement. Then, in the breeding programs, indirect selection for grain yield using these traits could be easier than selection based on direct grain yield [34, 35].

Advertisement

4. Genetic variation of the water-deficit tolerance-associated traits

Understanding about the genetic variation for traits relating to water stress tolerance has great importance in developing breeding program strategies. Depending on the stress duration and severity and the stage of plant development and plant species, water stress causes many morphological, physiological, biochemical, and molecular changes in plants [36]. Plants respond to survive under water deficit condition through the induction of both regulatory and functional sets of genes [37]. The selection of drought-tolerant genotypes and associated traits is globally recognized as an effective strategy to maintain the growth and survival of agricultural crops exposed to future drought periods. A better knowledge of the physiobiochemical traits can be used to create new varieties of crops to increase productivity in water scarcity conditions [38]. Due to the complex genetic basis of water deficit tolerance and poor heritability of the crop yield trait, individual trait components, is more frequently identified and characterized due to its better heritability in replicated experiments [39]. Crop yield becomes especially vulnerable when water deficit stress occurs during the reproductive phase of plant development. Correlated secondary traits are generally easier to measure and show a higher heritability and thus may represent a more suitable target for improving maize response to water stress [40, 41].

4.1 Physiological traits of water-deficit tolerance

Chlorophyll fluorescence is a fast and noninvasive tool used for probing the activity of photosynthesis that can be successfully used for discriminating tolerance of plants to drought stress without damaging the plants [42]. One of the most-often applied chlorophyll fluorescence parameters is Fv/Fm that gives the information about the amount of the light absorbed by photosystem II via chlorophyll [43]. A decrease in the Fv/Fm parameter under water-stress conditions indicates the possibility of inhibiting or destroying the photochemical reaction centers due to the reduction of the electron acceptance and transfer capacity from the chlorophyll complex to photosystem II [44]. This parameter is reliable as a stress indicator in crops which has been documented for photochemical processes [45]. Kalaji et al. [46] concluded that in several studies, fluorescence parameters have been considered as selection tools in plant breeding. They also emphasized the importance of measuring traits related to fluorescence that have a high correlation with yield and especially stress resistance. The previous studies with the genetic analysis of wheat [47] and maize [48, 49] indicated low additive gene effect and high broad sense heritability for FV/Fm (quantum efficiency of PS II). Contrary, with genome analysis in soybean, moderate magnitude of broad sense heritability has been documented for FV/Fm [50].

Leaf chlorophyll content as an important physiological parameter plays a major role in evaluating photosynthetic efficiency, crop stresses, and nutritional status for breeding programs [51]. Chlorophyll is an essential pigment for photosynthesis and growth of plants where it converts light energy to chemical energy. In the stress conditions, chlorophyll content of leaves decreases in plants; therefore, it is a useful indicator of plant health [52]. The previous research provided that total chlorophyll content in plants such as wheat, rice, and cotton was controlled by dominance gene effects [53, 54, 55]. It is revealed by Said [56] and Shirinpour et al. [57] who reported that generation mean analysis in wheat and maize showed dominance effects for chlorophyll content and chlorophyll index under drought stress, respectively. Whereas in the other research, genetic analysis of chlorophyll index in rapeseed was observed to be under the control of additive gene effects as the main genetic effects for this trait [58]. Meanwhile, Akbari et al. [59] observed the high amount of narrow-sense heritability in the expression of total chlorophyll content and indicated the additive effects that play an important role in the control of this trait. Therefore, selection method could be an effective method to improve the mentioned trait in breeding programs.

The relative water content (RWC) of leaves is a key indicator for the degree of plant cell and tissue wilting and has been suggested as a selection criterion of cultivars for drought stress tolerance [60, 61]. The photosynthetic activity of resistant cultivars to water-deficit stress is higher than sensitive cultivars in high RWC and low-osmotic potential [62]. The reason for this is the ability of most plants to be tolerant to drought stress to reduce water loss through the epidermis of the leaves after closing the stomata or minimizing the open stomata [63]. In addition, the positive and significant correlation of RWC with photosynthesis and grain yield and its high heritability under water stress has made measuring this trait an important indicator in determining the water status of the plant and identifying cultivars resistant to low stress [64, 65]. The relative water content of leaves is one of the traits that lead to increase the stability of yield under drought stress [66]. Under water-deficit stress, a decrease in RWC occurs due to the lack of cell turgor pressure in the leaf and leads to stomatal closure and reduced photosynthetic rate [67]. In fact, the reduction of RWC is the usual response of plants to stress [68]. In some studies, it has been reported that the high percentage of RWC in plants that are exposed to water stress is associated with stress tolerance in plants, and it is considered as an index to determine the difference between cultivars in terms of water-deficit stress tolerance [69, 70]. Moradi et al. [71] by evaluating six lines of maize under normal and drought stress conditions reported that RWC is controlled by the over-dominance effects of genes under both the conditions. In another research by the generation mean analysis of maize, it has been stated that both gene effects of dominance and epistasis play an important role in the genetic control of RWC under control and water-deficit-stress conditions [72]. By studying the gene effect of RWC in sunflower, the main role of additive gene effects in controlling the heritability of this trait has been expressed under water-deficit stress [73, 74]. Naroui Rad et al. [75] observed the importance of both additive and nonadditive gene effects in controlling the inheritance of this trait.

4.2 Biochemical traits of water-deficit tolerance

Plants needed to evolve different mechanisms including osmotic adjustment and antioxidant defense systems, which enhance their capacity to adjust and adapt to water-stress conditions. Water-deficit stress leads to the overproduction of reactive oxygen species (ROS), such as hydrogen peroxide (H2O2) and superoxide anion radicals (O) which result in plant growth and productivity inhibition [76]. Various enzymatic antioxidants, such as superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase, can be activated to balance between ROS generation and scavenging [77]. Furthermore, accumulation of soluble sugars and proline and changes in protein expression have been reported in maize to increase plant resistance under water-deficit conditions [78]. High narrow-sense heritability (0.53–0.71) has been observed for protein, proline, and soluble sugar concentrations under severe stress conditions. These results indicated that the selection in the parents’ inbred lines or early segregating generations could be useful to improve these characters in the maize [79]. Gorji et al. [80] reported that there is moderate and low value of narrow-sense heritability for antioxidant enzymes activities under drought stress and normal condition, respectively. According to Shirinpour et al. [79], the values of narrow-sense heritability for antioxidant enzymes activities of catalase, peroxidases, and polyphenol oxidase were between low to moderate and expressed the major role of dominance variance in the inheritance of these enzymes. For improvement of the antioxidant enzymes, selection in the later generation and utilization of heterosis will facilitate the breeding program.

In corn, proline accumulation due to drought has been reported in the different growth stages for the maintenance of cell turgor and protection of cell structures for improvement under limited water [81]. Under stress conditions, genotypes with high proline content are mainly considered to be tolerant to a number of abiotic stresses suggesting the use of this trait as an index for indirect selection [82, 83]. According to Rahimi [84], proline content displayed over-dominance gene effects by using Haymen’s graphical approach in lines of maize. The narrow-sense heritability was 0.14, and this causes the use of heterozygosis and the production of hybrid varieties can be used to breeding of this trait. The same result was reported by Naroui Rad et al. [75] in bread wheat and Khalil et al. [83] in sunflower who found that nonadditive gene effects were predominant for the proline concentration. This result disagrees with Pourmohammad et al. [74] who inferred the presence of additive gene effects for this trait in sunflower. They suggested that selection of proline concentration should be made in the early generations.

Sugars are known as carbon suppliers; therefore, they are considered as an energy source not only for plants but also for most other organisms. Sugar plays a decisive role in the negative osmotic potential in the cytoplasm and, as a result, control the osmotic regulation. Also, they act as osmotic protectors of membranes and proteins and detoxify oxygen-free radicals [85, 86]. They also maintain and stabilize cell membranes under stress conditions [87]. The change in the amount of soluble sugars depends on the type of plant species, and the duration and severity of the drought stress [88]. An increase in the amount of soluble sugars in corn plants has been observed with an increase in the duration and intensity of stress during the low-water period [79, 89]. Accumulation of high amount of sugars such as trehalose, mannitol, sorbitol [90], sucrose, hexose, and raffinose helps the stability of dehydrated membranes and tissues and increases plant tolerance against water stress [91, 92]. In the QTL study for the content of seed-soluble sugars in sweet corn, the importance of both additive and dominance main effects in controlling the inheritance of this trait [93] and the effective role of dominance variance in controlling soluble sugars by examining the genetic analysis of chickpea seeds [94] has been reported.

One of the major biochemical changes that occur due to the decrease in soil moisture in agricultural plants is the change in the amount of production of plant proteins in order to degrade or prevent the synthesis of some of them, as well as the production of stress-specific proteins [95, 96]. The synthesis of stress proteins is the response of the plant to water-deficit-stress conditions. These proteins are soluble in water and therefore, by hydrating the plant's cellular structures, they help to withstand the stress. The synthesis of various transcription factors and stress proteins plays a significant role in the tolerance of plants to stress [97, 98]. Water-deficit stress causes oxidation of carbohydrates, proteins, lipids, and even DNA [99, 100]. In general, water stress reduces the number of cell polysomes in tissues that have less water content, depending on different plant species, and ultimately leads to a reduction in the production of proteins. In addition, the reduction of photosynthesis under drought stress causes a reduction or even a stop of protein production [101, 102]. Enzymes are an important group of intracellular proteins whose activity is inhibited under the influence of water-deficit stress. While some enzymes are stable and their activity may even increase under drought stress [103], Shirinpour et al. [79] using generations mean analysis of hybrids maize SC704 revealed that the high narrow sense heritability and the presence of additive variance for protein content under normal irrigation and water-deficit stress conditions. The authors concluded that the additive gene effects have a major role in controlling of this trait. Then, for improving of the protein content in both normal and water stress conditions, selection in the early segregating generations will be effective. Similar results were observed in the study of Akram et al. [104] and reported the genetic control of protein content by additive and partial dominance effects using bread wheat genetic analysis. These researchers also stated the effectiveness of selection in the early generations for this trait. Meanwhile, Abid et al. [100] indicated the nonadditive gene effects and low narrow sense heritability in the genetic control of protein content in cotton under water-deficit stress.

Advertisement

5. Conclusion

Under recent climatic changes, both the biotic and abiotic stresses are a serious threat for global food security and plant production sustainability. Among the abiotic stresses, water-deficit stress is gaining attention due to its adverse effect on plant growth and development and significant reduction in plant yield causing global food insecurity. Various morphological, biochemical, and physiological mechanisms are affected by water-deficit stress that hampers plant productivity. To tackle the adverse effect of the water stress on plants, certain mechanisms are adopted by the plants which enhance drought tolerance. Genetic improvement of maize for various traits which are contributing to drought tolerance relies primarily on understanding the genetic control of the traits. Knowledge of genetics or genetic control of these traits enables breeders to formulate techniques and strategies for trait selection to bring out the desired genetic improvement in the target traits. Therefore, understanding the genetics of important traits is of paramount importance for rapid and efficient improvement in any crop. This chapter deals with the genetic control of physiobiochemical traits so that effective breeding strategies and selection can be employed to achieve greater progress in maize genetic improvement programs. It can be stated that the genotypes which are maintaining high various physiobiochemical traits such as chlorophyll fluorescence, leaf chlorophyll content, relative water content, various enzymatic antioxidants activities, proline, and sugars accumulation under water-deficit stress are considered tolerant genotypes under deficit moisture stress and used for the selection process. Therefore, these findings might be useful to the maize breeders and farmers for future phenotypic and genotypic association studies. Also, it may be further studied to develop morphological and physiobiochemical markers and will encourage to develop water-deficit tolerance maize varieties. Genetic components depict the involvement of nonadditive and additive genetic effects in the inheritance of various physiobiochemical traits, suggesting that genotypes possess significant differences for these traits. Clearly, additional attention and research on molecular findings of response and resistance of maize generations are needed to identify most resistant crop varieties in field conditions particularly under water-deficit stress.

References

  1. 1. Khan A, Pan X, Najeeb U, Tan DKY, Fahad S, Zahoor R, et al. Coping with drought: Stress and adaptive mechanisms, and management through cultural and molecular alternatives in cotton as vital constituents for plant stress resilience and fitness. Biological Research. 2018;51(1):47
  2. 2. Wing IS, De Cian E, Mistry MN. Global vulnerability of crop yields to climate change. Journal of Environmental Economics and Management. 2021;109:102462
  3. 3. Chartres C. Is water scarcity a constraint to feeding Asia's growing population? International Journal of Water Resources Development. 2014;30(1):28-36
  4. 4. Abtew W, Melesse A. Climate Change and Evapotranspiration. In: Evaporation and Evapotranspiration. Dordrecht: Springer; 2013. pp. 197-202
  5. 5. Nevo E, Chen G. Drought and salt tolerances in wild relatives for wheat and barley improvement. Plant, Cell and Environment. 2010;33(4):670-685
  6. 6. Toumi J, Er-Raki S, Ezzahar J, Khabba S, Jarlan L, Chehbouni A. Performance assessment of AquaCrop model for estimating evapotranspiration, soil water content and grain yield of winter wheat in Tensift Al Haouz (Morocco): Application to irrigation management. Agricultural Water Management. 2016;163:219-235
  7. 7. Ket P, Garré S, Oeurng C, Hok L, Degré A. Simulation of crop growth and water-saving irrigation scenarios for lettuce: A monsoon-climate case study in kampong Chhnang, Cambodia. Water. 2018;10(5):666
  8. 8. Grote U, Fasse A, Nguyen TT, Erenstein O. Food security and the dynamics of wheat and maize value chains in Africa and Asia. Frontiers in Sustainable Food Systems. 2021;4:617009
  9. 9. Aslam M, Maqbool MA, Cengiz R. Drought Stress in Maize (Zea mays L.): Effects, Resistance Mechanisms, Global Achievements and Biological Strategies for Improvement. Cham: Springer; 2015
  10. 10. Wang B, Liu C, Zhang D, He C, Zhang J, Li Z. Effects of maize organ-specific drought stress response on yields from transcriptome analysis. BMC Plant Biology. 2019;19(1):335
  11. 11. FAOSTAT. Food and Agricultural Organization Statistical Database. Rome, Italy: FAO; 2016. Available from: http://faostatfao.org
  12. 12. Boomsma CR, Vyn TJ. Maize drought tolerance: Potential improvements through arbuscular mycorrhizal symbiosis? Field Crops Research. 2008;108(1):14-31
  13. 13. Mittal S, Banduni P, Mallikarjuna MG, Rao AR, Jain PA, Dash PK, et al. Structural, functional, and evolutionary characterization of major drought transcription factors families in maize. Frontiers in Chemistry. 2018;6:177
  14. 14. Oosten MJV, Costa A, Punzo P, Landi S, Ruggiero A, Batelli G, et al. Genetics of drought stress tolerance in crop plants. In: Drought Stress Tolerance in Plants. Vol. 2. 2016. pp. 39-70
  15. 15. Blum A. Drought resistance—Is it really a complex trait? Functional Plant Biology. 2011;38(10):753-757
  16. 16. Hasibuzzaman ASM, Akter F, Bagum SA, Hossain N, Akter T, Uddin MS. Morpho-physiological mechanisms of maize for drought tolerance. In: Plant Stress Physiology. London, UK: IntechOpen; 2021
  17. 17. Fang Y, Xiong L. General mechanisms of drought response and their application in drought resistance improvement in plants. Cellular and Molecular Life Sciences. 2015;72(4):673-689
  18. 18. Muthoni J, Shimelis H. Mating designs commonly used in plant breeding: A review. Australian Journal of Crop Science. 2020;14(12):1855-1869
  19. 19. Mather K, Jinks JL. Biometrical Genetics: The Study of Continuous Variation. Chapman and Hall, London : Springer; 1982
  20. 20. Kearsey MJ, Pooni HS. The Genetical Analysis of Quantitative Traits. 2nd ed. London: Chapman and Hall; 2004
  21. 21. Le Clerg E. Significance of Experimental Design in Plant Breeding. Ames: Iowa State University Press; 1966. pp. 243-313
  22. 22. Comstock R, Robinson H. Estimation of average dominance of genes. Heterosis. 1952;2:494-516
  23. 23. Griffing B. Concept of general and specific combining ability in relation to diallel crossing systems. Australian Journal of Biological Sciences. 1956;9(4):463-493
  24. 24. Hallauer AR, Carena MJ, Miranda Filho J. Quantitative Genetics in Maize Breeding. 3rd ed. New York: Springer-Verlag; 2010. pp. 1-22
  25. 25. Farooq M, Wahid A, Kobayashi N, Fujita D, Basra S. Plant drought stress: Effects, mechanisms and management. Agronomy for Sustainable Development. 2009;29(1):185-212
  26. 26. Zhang H, Zhu J, Gong Z, Zhu J-K. Abiotic stress responses in plants. Nature Reviews. Genetics. 2022;23(2):104-119
  27. 27. Bijalwan P, Sharma M, Kaushik P. Review of the Effects of Drought Stress on Plants: A Systematic Approach. Switzerland: Preprints.org; 2022
  28. 28. Diatta AA, Fike JH, Battaglia ML, Galbraith JM, Baig MB. Effects of biochar on soil fertility and crop productivity in arid regions: A review. Arabian Journal of Geosciences. 2020;13(14):1-17
  29. 29. Badr A, El-Shazly HH, Tarawneh RA, Börner A. Screening for drought tolerance in maize (Zea mays L.) germplasm using germination and seedling traits under simulated drought conditions. Plants. 2020;9(5):565
  30. 30. Gray SB, Brady SM. Plant developmental responses to climate change. Developmental Biology. 2016;419(1):64-77
  31. 31. Sobhanian H, Pahlavan S, Meyfour A. How does proteomics target plant environmental stresses in a semi-arid area? Molecular Biology Reports. 2020;47(4):3181-3194
  32. 32. Seleiman MF, Al-Suhaibani N, Ali N, Akmal M, Alotaibi M, Refay Y, et al. Drought stress impacts on plants and different approaches to alleviate its adverse effects. Plants. 2021;10(2):259
  33. 33. Cheng M, Wang H, Fan J, Zhang F, Wang X. Effects of soil water deficit at different growth stages on maize growth, yield, and water use efficiency under alternate partial root-zone irrigation. Water. 2021;13(2):148
  34. 34. Mwadzingeni L, Shimelis H, Tsilo TJ. Variance components and heritability of yield and yield components of wheat under drought-stressed and non-stressed conditions. Australian Journal of Crop Science. 2017;11(11):1425
  35. 35. Gebregergs G, Mekbib F. Estimation of genetic variability, heritability, and genetic advance in advanced lines for grain yield and yield components of sorghum [Sorghum bicolor (L.) Moench] at Humera, Western Tigray, Ethiopia. Cogent Food & Agriculture. 2020;6(1):1764181
  36. 36. Chaves MM, Pereira JS, Maroco J, Rodrigues ML, Ricardo CPP, Osório ML, et al. How plants cope with water stress in the field? Photosynthesis and growth. Annals of Botany. 2002;89(7):907-916
  37. 37. Bartels D, Sunkar R. Drought and salt tolerance in plants. Critical Reviews in Plant Sciences. 2005;24(1):23-58
  38. 38. Yadav S, Sharma KD. Molecular and morphophysiological analysis of drought stress in plants. Plant Growth. Croatia: InTech; 2016. pp. 150-173
  39. 39. Xue Y, Warburton ML, Sawkins M, Zhang X, Setter T, Xu Y, et al. Genome-wide association analysis for nine agronomic traits in maize under well-watered and water-stressed conditions. Theoretical and Applied Genetics. 2013;126(10):2587-2596
  40. 40. Liu S, Qin F. Genetic dissection of maize drought tolerance for trait improvement. Molecular Breeding. 2021;41(2):1-13
  41. 41. Thirunavukkarasu N, Hossain F, Arora K, Sharma R, Shiriga K, Mittal S, et al. Functional mechanisms of drought tolerance in subtropical maize (Zea mays L.) identified using genome-wide association mapping. BMC Genomics. 2014;15(1):1-12
  42. 42. Ajigboye OO, Ray RV, Murchie EH. chlorophyll fluorescence on the fast timescale. In: Photosynthesis. Springer; 2018. pp. 95-104
  43. 43. Oukarroum A, El Madidi S, Schansker G, Strasser RJ. Probing the responses of barley cultivars (Hordeum vulgare L.) by chlorophyll a fluorescence OLKJIP under drought stress and re-watering. Environmental. Experimental Botany. 2007;60(3):438-446
  44. 44. Ahmed IM, Dai H, Zheng W, Cao F, Zhang G, Sun D, et al. Genotypic differences in physiological characteristics in the tolerance to drought and salinity combined stress between Tibetan wild and cultivated barley. Plant Physiology and Biochemistry. 2013;63:49-60
  45. 45. Galic V, Franic M, Jambrovic A, Ledencan T, Brkic A, Zdunic Z, et al. Genetic correlations between photosynthetic and yield performance in maize are different under two heat scenarios during flowering. Frontiers in Plant Science. 2019;10:566
  46. 46. Kalaji HM, Schansker G, Brestic M, Bussotti F, Calatayud A, Ferroni L, et al. Frequently asked questions about chlorophyll fluorescence, the sequel. Photosynthesis Research. 2017;132(1):13-66
  47. 47. Vijayalakshmi K, Fritz AK, Paulsen GM, Bai G, Pandravada S, Gill BS. Modeling and mapping QTL for senescence-related traits in winter wheat under high temperature. Molecular Breeding. 2010;26(2):163-175
  48. 48. Šimić D, Lepeduš H, Jurković V, Antunović J, Cesar V. Quantitative genetic analysis of chlorophyll a fluorescence parameters in maize in the field environments. Journal of Integrative Plant Biology. 2014;56(7):695-708
  49. 49. Shirinpour M, Asghari A, Aharizad S, Rasoulzadeh A, Khavari KS. Generation mean analysis of some physiological traits in the hybrid maize cv. SC704 under different water regimes. Journal of Plant Physiology and Breeding. 2020;10(1):141-148
  50. 50. Hao D, Chao M, Yin Z, Yu D. Genome-wide association analysis detecting significant single nucleotide polymorphisms for chlorophyll and chlorophyll fluorescence parameters in soybean (Glycine max) landraces. Euphytica. 2012;186(3):919-931
  51. 51. Fernández-Marín B, Artetxe U, Barrutia O, Esteban R, Hernández A, García-Plazaola JI. Opening Pandora's box: Cause and impact of errors on plant pigment studies. Frontiers in Plant Science. 2015;6:148
  52. 52. Zhang H, Ge Y, Xie X, Atefi A, Wijewardane NK, Thapa S. High throughput analysis of leaf chlorophyll content in sorghum using RGB, hyperspectral, and fluorescence imaging and sensor fusion. Plant Methods. 2022;18(1):1-17
  53. 53. Naroui Rad MR, Kadir MA, Yusop MR. Genetic behaviour for plant capacity to produce chlorophyll in wheat (Triticum aestivum) under drought stress. Australian Journal of Crop Science. 2012;6(3):415-420
  54. 54. Song M, Fan S, Pang C, Wei H, Yu S. Genetic analysis of the antioxidant enzymes, methane dicarboxylic aldehyde (MDA) and chlorophyll content in leaves of the short season cotton (Gossypium hirsutum L.). Euphytica. 2014;198(1):153-162
  55. 55. Makwana R, Patel V, Pandya M, Chaudhari B. Inferences on Magnitude and Nature of Gene Effects for Morpho-Physiological Traits in Rice [Oryza Sativa L.]. International Journal of Pure & Applied Bioscience. 2018;6(2):1488-1493
  56. 56. Said AA. Generation mean analysis in wheat (Triticum aestivum L.) under drought stress conditions. Annals of Agricultural Science. 2014;59(2):177-184
  57. 57. Shirinpour M, Asghari A, Atazadeh E, Aharizad S, Rasoulzadeh A. Genetic analysis of grain yield and physiological traits of hybrid maize cv. SC704 under full and water deficit irrigation conditions. Cereal Research Communications. 2021;49(2):199-206
  58. 58. Dai W, Girdthai T, Huang Z, Ketudat-Cairns M, Tang R, Wang S. Genetic analysis for anthocyanin and chlorophyll contents in rapeseed. Ciencia Rural. 2016;46(5):790-795
  59. 59. Akbari L, Bahraminejad S, Cheghamirza K. Genetic analysis of physiological traits in bread wheat under normal and terminal water-deficit stress conditions. Environmental Stresses in Crop Sciences. 2020;13(4):1031-1044
  60. 60. Dhanda S, Sethi G. Tolerance to drought stress among selected Indian wheat cultivars. The Journal of Agricultural Science. 2002;139(3):319-326
  61. 61. Chen J, Xu W, Velten J, Xin Z, Stout JJJos, conservation w. Characterization of maize inbred lines for drought and heat tolerance. Journal of Soil and Water Conservation. 2012;67(5):354-364
  62. 62. Kaymakanova M, Stoeva N, Mincheva T. Drought stress and its effect on physiological response of sunflower. Central Europe Agriculture. 2008;9:749-756
  63. 63. Pirasteh-Anosheh H, Saed-Moucheshi A, Pakniyat H, Pessarakli M. Stomatal responses to drought stress. Water Stress Crop Plants. United States: John Wiley & Sons, Ltd; 2016. pp. 24-40
  64. 64. Schonfeld MA, Johnson RC, Carver BF, Mornhinweg DW. Water relations in winter wheat as drought resistance indicators. Crop Science. 1988;28(3):526-531
  65. 65. Merah O. Potential importance of water status traits for durum wheat improvement under Mediterranean conditions. The Journal of Agricultural Science. 2001;137(2):139-145
  66. 66. Teulat B, Borries C, This D. New QTLs identified for plant water status, water-soluble carbohydrate and osmotic adjustment in a barley population grown in a growth-chamber under two water regimes. Theoretical and Applied Genetics. 2001;103(1):161-170
  67. 67. Kramer PJ, Boyer JS. Water Relations of Plants and Soils. 1st ed. San Diego, California: Academic Press; 1995. p. 495
  68. 68. Pérez-Pérez J, Syvertsen JP, Botía P, García-Sánchez F. Leaf water relations and net gas exchange responses of salinized Carrizo citrange seedlings during drought stress and recovery. Annals of Botany. 2007;100(2):335-345
  69. 69. Altinkut A, Kazan K, Ipekci Z, Gozukirmizi N. Tolerance to paraquat is correlated with the traits associated with water stress tolerance in segregating F2 populations of barley and wheat. Euphytica. 2001;121(1):81
  70. 70. Keles Y, Öncel I. Growth and solute composition in two wheat species experiencing combined influence of stress conditions. Russian Journal of Plant Physiology. 2004;51(2):203-209
  71. 71. Moradi M, Choukan R, Heravan EM, Bihamta MR. Genetic analysis of various morpho-physiological traits in Zea mays L. using graphical approach under normal and water stress conditions. Research on. Crops. 2014;15(1):62-70
  72. 72. Moharramnejad S, Valizadeh M, Emaratpardaz J. Generation mean analysis in maize (zea mays l.) under drought stress. Fresenius Environmental Bulletin. 2018;27(4):2518-2522
  73. 73. Rauf S, Sadaqat H, Khan I, Ahmed R. Genetic analysis of leaf hydraulics in sunflower (Helianthus annuus L.) under drought stress. Plant, Soil and Environment. 2009;55(2):62-69
  74. 74. Pourmohammad A, Toorchi M, Alavikia SS, Shakiba MR. Genetic analysis of yield and physiological traits in sunflower (Helianthus annuus L.) under irrigation and drought stress. Notulae Scientia Biologicae. 2014;6(2):207-213
  75. 75. Naroui Rad MR, Kadir MA, Yusop MR, Jaafar HZ, Danaee M. Gene action for physiological parameters and use of relative water content (RWC) for selection of tolerant and high yield genotypes in F2 population of wheat. Australian Journal of Crop Science. 2013;7(3):407-413
  76. 76. Sun Y, Wang C, Chen HY, Ruan H. Response of plants to water stress: A meta-analysis. Frontiers in Plant Science. 2020;11:978
  77. 77. Gill SS, Tuteja N. Reactive oxygen species and antioxidant machinery in abiotic stress tolerance in crop plants. Plant Physiology and Biochemistry. 2010;48(12):909-930
  78. 78. Per TS, Khan NA, Reddy PS, Masood A, Hasanuzzaman M, Khan MIR, et al. Approaches in modulating proline metabolism in plants for salt and drought stress tolerance: Phytohormones, mineral nutrients and transgenics. Plant Physiology and Biochemistry. 2017;115:126-140
  79. 79. Shirinpour M, Asghari A, Aharizad S, Rasoulzadeh A, Khavari KS. Genetic interaction and inheritance of biochemical traits can predict tolerance of hybrid maize cv. SC704 to drought. Acta Physiologiae Plantarum. 2020;42(7):124
  80. 80. Gorji A, Zonoori Z, Zolnoori M, Jamasbi A. Inheritance of antioxidant activity of triticale under drought stress. Asian Journal of Plant Sciences. 2011;10(3):220-226
  81. 81. Sinay H, Arumingtyas EL, Harijati N, Indriyani S. Proline content and yield components of local corn cultivars from Kisar Island, Maluku, Indonesia. International Journal of Plant Biology. 2016;6(1):6071
  82. 82. Abbas S, Ahmad S, Sabir S, Shah A. Detection of drought tolerant sugarcane genotypes (Saccharum officinarum) using lipid peroxidation, antioxidant activity, glycine-betaine and proline contents. Journal of Soil Science and Plant Nutrition. 2014;14(1):233-243
  83. 83. Khalil F, Rauf S, Monneveux P, Anwar S, Iqbal Z. Genetic analysis of proline concentration under osmotic stress in sunflower (Helianthus annuus L.). Breeding Science. 2016;66:463-470
  84. 84. Rahimi M. Genetic analysis of Biochemical and Physiological Traits using Haymen’s Graphical Approach in Lines and F2 Progenies of Maize (Zea mays L.). Plant Genetic Researches. 2021;7(2):1-12
  85. 85. Livingston DP, Hincha DK, Heyer AG. Fructan and its relationship to abiotic stress tolerance in plants. Cellular and Molecular Life Sciences. 2009;66(13):2007-2023
  86. 86. Van den Ende W, Valluru R. Sucrose, sucrosyl oligosaccharides, and oxidative stress: Scavenging and salvaging? Journal of Experimental Botany. 2009;60(1):9-18
  87. 87. Challabathula D, Bartels D. Desiccation tolerance in resurrection plants: New insights from transcriptome, proteome and metabolome analysis. Frontiers in Plant Science. 2013;4:482
  88. 88. Poonam RB, Handa N, Kaur H, Rattan A, Bali S, Gautam V, et al. Sugar signalling in plants: a novel mechanism for drought stress management. In: Ahmad P, editor. Water Stress Crop and Plants: A Sustainable Approach. 1st ed. New York: John Wiley and Sons; 2016. pp. 287-302
  89. 89. Mohammadkhani N, Heidari R. Drought-induced accumulation of soluble sugars and proline in two maize varieties. World Applied Sciences Journal. 2008;3(3):448-453
  90. 90. Sharma A, Shahzad B, Kumar V, Kohli SK, Sidhu GPS, Bali AS, et al. Phytohormones regulate accumulation of osmolytes under abiotic stress. Biomolecules. 2019;9(7):285
  91. 91. Parida AK, Dagaonkar VS, Phalak MS, Umalkar G, Aurangabadkar LP. Alterations in photosynthetic pigments, protein and osmotic components in cotton genotypes subjected to short-term drought stress followed by recovery. Plant Biotechnology Reports. 2007;1(1):37-48
  92. 92. Rosa M, Prado C, Podazza G, Interdonato R, González JA, Hilal M, et al. Soluble sugars: Metabolism, sensing and abiotic stress: A complex network in the life of plants. Plant Signaling & Behavior. 2009;4(5):388-393
  93. 93. Qi X, Zhao Y, Jiang L, Cui Y, Wang Y, Liu B. QTL analysis of kernel soluble sugar content in supersweet corn. African Journal of Biotechnology. 2009;8(24):6913-6917
  94. 94. Nassourou MA, Njintang YN, Noubissié TJ-B, Nguimbou RM, Bell JM. Genetics of seed flavonoid content and antioxidant activity in cowpea (Vigna unguiculata L. Walp.). The Crop Journal. 2017;4(5):391-397
  95. 95. Bewley JD, Larsen KM. Differences in the responses to water stress of growing and non-growing regions of maize mesocotyls: Protein synthesis on total, free and membrane-bound polyribosome fractions. Journal of Experimental Botany. 1982;33(3):406-415
  96. 96. Heikkila J, Papp JT, Schultz G, Bewley JD. Induction of heat shock protein messenger RNA in maize mesocotyls by water stress, abscisic acid, and wounding. Plant Physiology. 1984;76(1):270-274
  97. 97. Chen L, Wang X. Features and functions of plant moisture-induced protein. Biology Teaching. 2003;23(3):503-508
  98. 98. Wahid A, Gelani S, Ashraf M, Foolad MR. Heat tolerance in plants: An overview. Environmental and Experimental Botany. 2007;61(3):199-223
  99. 99. Apel K, Hirt H. Reactive oxygen species: Metabolism, oxidative stress, and signal transduction. Annual Review of Plant Biology. 2004;55:373-399
  100. 100. Abid MA, Malik W, Yasmeen A, Qayyum A, Zhang R, Liang C, et al. Mode of inheritance for biochemical traits in genetically engineered cotton under water stress. AoB Plants. 2016;8:plw008. Epub 2016/02/04
  101. 101. El-Beltagi HS, Mohamed HI, Sofy MR. Role of ascorbic acid, glutathione and proline applied as singly or in sequence combination in improving chickpea plant through physiological change and antioxidant defense under different levels of irrigation intervals. Molecules. 2020;25(7):1702
  102. 102. Tayyab N, Naz R, Yasmin H, Nosheen A, Keyani R, Sajjad M, et al. Combined seed and foliar pre-treatments with exogenous methyl jasmonate and salicylic acid mitigate drought-induced stress in maize. PLoS One. 2020;15(5):e0232269
  103. 103. Taiz L, Zeiger E. Stress physiology. In: Taiz L, Zeiger E, editors. Plant Physiology. 5th ed. Sunderland: Sinauer Associates, Inc.; 2010. pp. 671-681
  104. 104. Akram Z, Ajmal SU, Kiani AA, Jamil M. Genetic analysis of protein, lysine, gluten and flour yield in bread wheat (Triticum aestivum L.). Pakistan Journal of Biological Sciences. 2007;10(12):1990-1995

Written By

Mozhgan Shirinpour, Ehsan Atazadeh, Ahmad Bybordi, Ashkboos Amini and Hassan Monirifar

Submitted: 28 December 2022 Reviewed: 13 April 2023 Published: 06 December 2023