Sorghum [Sorghum bicolor (L.) Moench] is a widely adaptable cereal crop cultivated in tropical, subtropical, and temperate regions of the world. It is the fifth most important cereal crop next to wheat, rice, maize, and barley, and it is a staple food for millions of people in the semiarid regions of Asia and Africa (Mundia et al., 2019). Sorghum grew globally in over 40.07 Mha with a production of 57.89 million tons and productivity of 1,444 kg/ha (FAOSTAT, 2019). In India, it is the third most important food grain next to rice and wheat cultivated in an area of 4.09 Mha (FAOSTAT, 2019) in the rainy (Kharif) season as a rainfed crop and in the post-rainy (Rabi) season under residual soil moisture. More than 90% of the sorghum area and 85% of the production are concentrated in the warm semiarid tracts of central and south India (Davis et al., 2019). The productivity of sorghum in India is still considered to be low at 849 kg/ha compared to the average global productivity of 1,444 kg/ha (FAOSTAT, 2019). This can be attributed to poor soils (marginal lands), unreliable rainfall, incidence of insect pests and diseases, and poor crop input management. The water deficit is significantly increased due to irregularities in rainfall distribution exacerbated by climate change (Eggen et al., 2019; Ocheing et al., 2020). While the rainy season is predominated by the sorghum hybrids, the post-rainy season is dominated by open-pollinated varieties that contribute to low sorghum productivity (Patil et al., 2014). This indicates that a greater emphasis is required for separating and strengthening the focus of rainy and post-rainy breeding on the cultivars' genetic enhancement and their adaptability.

Sorghum has an inherent ability to adapt to a harsh climate. The crop can grow well in dry conditions and can also tolerate water logging, thus making it ideal for cultivation in the arid and semiarid regions of the world (Hadebe et al., 2017). These factors change in relation to climate change, which is predicted to make sorghum production riskier, especially under rainfed agriculture and more so for smallholder farmers (McCarthy and Vlek, 2012). A feasible approach of modifying management practices through a deliberate choice between an improved sorghum variety and local landraces accompanied by an appropriate time of sowing will enhance the adaptive capacity of many resource-poor sorghum farmers and ultimately increase sorghum production ensuring food and livelihood security (Akinseye et al., 2020).

Grain mold is one of the most important diseases in sorghum, which is caused by a complex of fungal species. The genera Fusarium, Curvularia, and Alternaria are mainly responsible for 80–90% of the infection in India (Das et al., 2020). Species of Bipolaris, Phoma, Drechslera, Exserohilum, Aspergillus, Cladosporium, Penicillium, Olpitrichum, Gonatobotrytis, and Aspergillus are also detected sporadically in low frequency (Das et al., 2020). The disease can cause yield losses ranging from 30 to 100% depending on the cultivars and weather conditions (Kalaria et al., 2020). Losses in seed weight, grain density, germination, and seed viability due to grain mold lead to a significant decline in seed quality parameters in the rainy season (Nida et al., 2019). Toxins and secondary metabolites produced by the fungi on infected grains render sorghum unfit for human consumption and for cattle and poultry feed (Das et al., 2020). Host-plant resistance is the most cost-effective, efficient, and eco-friendly management practice (Mofokeng et al., 2017). In sorghum, properties such as panicle compactness, glume cover, glume pigmentation, grain hardness, polyphenols (tannins), flavonoids (flavan-4-ols), and antifungal proteins (chitinases, glucanases, sormatin, PR-10, and RIPs) confer a resistance to grain mold disease. There is a need to avoid dependency on a few sources of grain mold-resistant genes and alleles that are currently available, and in this context, crop wild relatives and landraces offer a tremendous scope acting as reservoirs of useful genes for sorghum improvement (Brar and Khush, 2018; Kyratzis et al., 2019). With an increase in the effect of climate change, there is a need to collect, screen, and identify novel sorghum germplasm harboring the grain mold-resistant trait that can be harnessed for adaptation to rainfed agroecologies of India.

Sorghum is a significant source of dietary energy, protein, and micronutrients for the vast majority of the population in sub-Saharan Africa and India (Awika, 2017). It is a good source of phytochemicals including phenolic acid, flavonoids, anthocyanins, phytosterols, plicosanols, tannins, and carotenoids, which make the grain suitable for developing the functional food and nutraceuticals (Balcerek et al., 2020). Additionally, high antioxidant levels in pigmented and tannin sorghum varieties offer many health benefits including slow digestability, cholesterol-lowering, antioxidant, anti-inflammatory, and anticarcinogenic properties (Abdelhalim et al., 2021). The presence of tannins in the testa, which is a layer beneath the pericarp, improves a resistance to grain mold in sorghum (Cuevas et al., 2018). However, red-pigmented testa and high tannin content are less desired in India where red grain sorghum varieties are rarely used for human consumption. Yellow pericarp sorghum is rich in flavanones and has slightly higher total phenolic contents than white sorghum (Dykes et al., 2011). There is a great demand for sorghum with a yellow pericarp owing to high nutritional and good flatbread making and keeping qualities (Jaisimha, 2019). Biofortification of sorghum through genetic approaches and an increased intake of nutrition-rich sorghum grains can help in improving the nutritional security in the developing world (Kumar et al., 2015).

Keeping in view of a narrow genetic diversity for grain minerals in modern sorghum cultivars, the identification and utilization of valuable alleles in wild ancestors of crop plants are considered as a sustainable approach for enhancing sorghum nutrition (Mofokeng et al., 2018; Abdelhalim et al., 2019). India is considered as the secondary center of sorghum diversity next to East Africa (Ananda et al., 2020). High levels of within- and between-population variability among the sorghum landrace collections indicate a high germplasm diversity and a traits-based genetic novelty, which contribute to sorghum yield and adaptation improvement (Ghebru et al., 2002). However, adaptability and stability in yield are often challenged by the presence of a genotype × environment (G × E) interaction, which is a number one factor responsible for changing the genotype performance in different environments. Hence, it is important that multi-environment trials are conducted periodically to investigate the G × E interaction for selecting stable genotypes for yield and other important traits. The additive main effects and multiplicative interaction (AMMI) analysis proposed by Gauch (2013) and the genotype and G × E interaction (GGE) biplot model developed by Yan et al. (2000) are powerful tools used by plant breeders, geneticists, and agronomists for the identification of genotypes with high yield and wide adaptability.

These methods were also used to identify the landraces with yield stability and adaptability in sorghum (Admas and Tesfaye, 2017), chickpea (Pouresmael et al., 2018), wheat (Bavandpori et al., 2018), common bean (Philipo et al., 2020), etc. for further use in breeding programs for the development of new varieties. In sorghum, the high genetic and phenotypic diversity were reported from the landraces collected from India (Elangovan et al., 2009, 2012; Vara Prasad and Sridhar, 2019), Ethiopia (Adugna, 2014; Amelework et al., 2015; Derese et al., 2018; Wondimu et al., 2020), Eritrea (Tesfamichael et al., 2014), and Sudan (Abdelhalim et al., 2021). These landraces are the indispensable sources of genetic variation that can be utilized by plant breeders in the development of improved varieties with higher productivity, nutrients, grain mold tolerance, and climate resilience (Dwivedi et al., 2016; Godwin et al., 2019).

An attempt was made in this study to utilize the sources of variation for grain mold tolerance and a protein content present in sorghum landraces, which were evolved under vulnerable conditions with low inputs after the continuous selection by the farmers. To our knowledge, this is the first study to identify stable, high-yielding, drought- and grain mold-tolerant, and nutritionally rich sorghum varieties that were developed from the landraces in the Indian subcontinent. The objectives of the study were to (1) collect the landraces from the southern and central parts of India and identify agronomically superior landraces with a resistance to grain mold disease; (2) develop potential sorghum varieties from the superior landraces; (3) identify high-yielding, grain mold-tolerant genotypes with a stable performance using AMMI and GGE analyses; and (4) determine the nutrient composition [starch, sugar, protein, iron (Fe), and zinc (Zn)] of the developed sorghum varieties.

In this study, a total of 108 landraces were collected, and 36 superior landraces of 108 landraces were identified. About 11 of these landraces were used to develop 19 sorghum varieties. Previous reports (Tesso et al., 2008; Adugna, 2014; Abraha et al., 2015; Amelework et al., 2016; Wondimu et al., 2020) have identified sorghum landraces with a wide range of variations that could provide new sources of tolerance and highly contrasting lines for use in future breeding programs. The landraces used in the present study were collected from the interior parts of central and southern India where they might have evolved in response to diverse agroecological zones and farming systems practiced in those regions and were better adapted to the low input and marginal cultivation conditions of these areas coupled with a frequent occurrence of grain mold disease. The 13 rainfed locations tested in this study represented the rainfed dryland conditions and were characterized by a complex climate that is largely semiarid and dry subhumid, with a short wet season followed by a long dry season. Sorghum cultivated in these regions is prone to highly erratic rainfall (spatially and temporally), with a strong risk of dry spells at critical growth stages and heavy rains at the grain maturity stage. The present study identified 36 superior performing landraces, cultivated in water-stress conditions and had a tolerance to grain mold due to an indirect selection for associated traits such as panicle shape, grain color, seed compactness, etc. over the years, which could be utilized to develop elite lines in sorghum breeding programs.

In the present study, the evaluation of 19 sorghum varieties derived from the superior landraces using AMMI and GGE biplots has demonstrated a higher contribution by the G × E interaction to the total variation than the genotypes suggesting that the environment had a high impact on the performance of the sorghum varieties for both grain yield and fodder yield. Even though the proportion of the environment is the largest for both grain and fodder yields, the genotypes and G × E interaction have a paramount importance for the genotype evaluation (Yan and Kang, 2003). These findings are in agreement with Reddy et al. (2014) and Al-Naggar et al. (2018) who reported the predominance of the environment's main effect as the source of variation in the multi-environment trials in sweet sorghum and grain sorghum, respectively. Abiotic factors such as soil moisture, pH, mineral availability along with the weather and biotic factors including natural pest and disease occurrence might have contributed to large variations in the yield performance of the genotypes. The potential of the genotypes could be more exploited if the best performing genotypes were identified for the specific environments.

The total variations (56.6, 66.8%) contributed by IPCA1 and IPCA2 explained the differential performance of genotypes for grain yield and fodder yield across the 13 environments. Because of their maximum contribution, IPCA1 and IPCA2 were used to plot a two-dimensional GGE biplot. Gauch (2013) suggested that the most accurate model for AMMI can be predicted by using the first two IPCAs. Several researchers used the first two IPCAs for the GGE biplot analysis because they explained a greater percentage of the G × E interaction for sorghum (Al-Naggar et al., 2018), barley (Vaezi et al., 2017), pigeonpea (Rao et al., 2020; Kumar et al., 2021), wheat (Verma et al., 2015), and maize (Solomon et al., 2008).

AMMI stability value, which is the quantitative stability value developed through the AMMI model by Purchase et al. (2000), has been considered as the most appropriate single method of describing the stability of genotypes (Naroui et al., 2020). Several studies have identified the genotypes with smaller ASV and better stability and those with high ASV but higher yields for specific adaptability in crops including bread wheat (Farshadfar, 2008), grain sorghum (Adugna, 2014), and finger millet (Lule et al., 2014). In the present study, the high yields and stability (low ASV) of varieties such as PYPS 2, PYPS 5, PYPS 8, and PYPS 13 might be attributed to the 11 parental landraces, which could offer potential new sources of genes for higher grain and fodder yields and stability. These genotypes merit further genetic studies for adaptation and physiological traits for dissecting the traits contributing to stability.

In this study, several stable sorghum varieties were identified for grain yield and fodder yield. For example, PYPS 8 was stable and high in yield for grain yield. However, most of the stable genotypes need not necessarily have the best yield performance (Mohammadi and Amri, 2007). Hence, GSI was used as a single criterion to classify stable genotypes. To our knowledge, this is the first study incorporating grain and fodder yields' mean, protein content, grain mold reaction, and stability index to identify high-yielding, high protein, grain mold tolerant, and stable sorghum varieties such as PYPS 1, PYPS 2, PYPS 8, PYPS 13, etc. In wheat, Singh et al. (2019) have used GSI to identify stable high-yielding genotypes in India.

Genotypic stability is crucial to grain yield and the best genotype needs to combine good yield and stable performance across a range of production environments. Based on the AMMI1 biplot, the current study identified the sorghum varieties with wide and specific adaptability for both grain yield and fodder yield. For example, sorghum variety PYPS 8 with a low absolute IPCA1 score and the above-average grain yield was stable, showing less-variable yield across the environments, thus making it a promising multilocation testing and validation. On the contrary, the varieties PYPS 1 and PYPS 10 performed consistently across locations but with below-average grain yields. The variety PYPS 2 showed specific adaptability to E1 and E10 for grain yield. Similarly, Al-Naggar et al. (2018) identified two grain sorghum B-lines with site-specific adaptability in Egypt.

Interestingly, the varieties differed in their grain yield and fodder yield performances across locations. For example, the variety PYPS 15 showed specific adaptation to environments E1 and E10 for high grain yield (3,432 kg/ha) but was the most widely adaptable variety for fodder yield (16,955 kg/ha). Sorghum varieties PYPS 2, PYPS 8, PYPS 13, and PYPS 15 were considered as the best dual purpose cultivars (Figure 9) due to their higher grain and fodder yields (3,698, 2,0586 kg/ha; 3,584, 18,632 kg/ha; 3,514, 18,122 kg/ha; 3,432, 16,955 kg/ha) whereas PYPS 16 and PYPS 11 were the best varieties exclusively for grain (3,268 kg/ha) and fodder (13,895 kg/ha).

The relationship between the testing environments was graphically evaluated by using the angles between the vectors. The presence of wide obtuse angles between E5 and E12 with E2 suggested a negative correlation or strong crossover G × E interaction for grain yield (Yan and Tinker, 2006). This indicated that the genotypes performing better in one environment would perform poorly in another environment. Closer relationships among the locations depicted by small cosine angles (<90°) indicated the non-existence of a crossover G × E interaction suggesting that the ranking of genotypes does not change from environment to environment. The environments E5 and E12 and the environments E3 and E7 fall under the latter. The present study indicated a mixture of crossover and non-crossover types of G × E interaction, which has been reported in various studies (Rakshit et al., 2012; Naroui et al., 2013; Aruna et al., 2015). Furthermore, eliminating similar environments from multilocation trials of sorghum will help in the optimal utilization of resources.

In the polygon view of the GGE biplot derived from the first two main PC, PC1 refers to the yield ratio, associated with genotypic characteristics and PC2 refers to the yield related to the G × E interaction (Yan et al., 2007; Yan and Holland, 2010). In the present study, the contribution of the first two PCs toward 99.9 and 95.9% of the variability for grain yield and fodder yield, respectively, justified the use of the GGE biplot to effectively interpret the variability in the multi-environment data. The 13 tested environments in this study contributed to 35.5% of the total variation in grain yield and 28.9% in fodder yield. Mushayi et al. (2020) reported as much as 63% of the variation being explained by location in grain yield for maize. In this study, the highest grain yielding variety PYPS 2 performed best at E2, E1, E11, E6, and E10. These environments are in complete contrast to the best yielding environments E3, E8, E12, and E13 for high fodder yield. Several authors identified high-yielding genotypes for grain sorghum (Rakshit et al., 2012; Al-Naggar et al., 2018), forage sorghum (Aruna et al., 2015), and sweet sorghum (Rono et al., 2016).

In the GGE biplot analysis, partitioning of the test locations into meaningful mega-environments is the best approach to exploit the positive G × E interaction (Yan and Tinker, 2006). In the present study, the test locations were divided into a total of four mega-environments for grain yield and four for fodder yield. The varieties performed differently across the mega-environments for grain yield and fodder yield. For example, the variety PYPS 2 was the best for the two mega-environments for high grain yield and fodder yield and PYPS 5 was not suitable for any mega-environment suggesting that different genotypes should be deployed for each mega-environment to achieve optimal adaptation.

Based on the AMMI analysis, PYPS 8 and PYPS 13 were identified as the most stable sorghum varieties with a low grain mold incidence. The AMMI and GGE biplot methods were used to identify resistance sources to different diseases in multiple locations and also high-yielding stable genotypes in wheat, groundnut, mungbean, melon, etc. (Akcura et al., 2017; Chaudhari et al., 2019; Naroui et al., 2020; Tollo et al., 2020). In a previous study, Diatta et al. (2019) evaluated five sorghum hybrids along with their parental lines and reported a significant G × E interaction for grain yield. However, the G × E interaction was not significant for panicle mold infestation. Grain mold is a complex disease whose incidence is governed by a host resistance and an environment. Grain mold resistance was correlated with open panicles, long glumes, a greater glume coverage length, and area (Sharma et al., 2010). Loose panicle sorghum is more likely to be resistant to grain mold because the compact heads hold more moisture that favors disease development. Weather factors, particularly relative humidity play a dominant and determining role in grain mold severity. The wet weather condition following flowering is necessary for the grain mold development. The longer the duration of wetness on grain surface, the greater is the incidence of grain mold (Das et al., 2020). Photoperiod-sensitive cultivars that mature after the rains often escape grain mold infection (Patted et al., 2011). Sorghum cultivars with a white grain are more vulnerable to grain mold than those with a brown and red grain pericarp. In the present study, the varieties PYPS 8 and PYPS 13, which showed a low grain mold incidence, had a brown and yellow pericarp, respectively. Their parental lines viz., PSLRC 8, PSLCRC 9, PSLRC 2, and PSLRC 21 were characterized by a brown and yellow pericarp with high tannin levels, which might have contributed to grain mold tolerance. Furthermore, their panicles were semi-compact to loose a trait important for grain mold tolerance due to non-retention of moisture and better air circulation (Glueck et al., 1977; Rao et al., 1999; Patted et al., 2011). Glume length and area of coverage over the grain is related to the grain mold escape as the grains are protected from the exposure to rain. Patted et al. (2011) reported that sorghum progenies with a very long-to-long glume coverage escaped grain mold tolerance. They also reported that black- and red-colored glumes were moderately resistant to grain mold due to the presence of tannins, which inhibit the growth of saprophytic fungi, and thus reducing a grain mold incidence.

An analysis of nutrient composition revealed a mean starch content of 46.04% that is lower than the average content varying from 56 to 73% (Ratnavathi and Patil, 2013). The protein content ranging from 10.4 to 10.62% was reported in sorghum germplasm collections (Weckwerth et al., 2020). Other studies in sorghum have reported the protein content of 9–11% (Elbashir et al., 2008; Ahmed et al., 2014). Abdelhalim et al. (2021) reported the protein content ranging from 6.3 to 12.5% among the five landraces evaluated for their potential in biofortification. The protein content of the three varieties viz., PYPS 2 (14.52%), PYPS 9 (14.13), and PYPS 8 (13.26%) tested in this study is higher than that of sorghum landraces reported by Abdelhalim et al. (2021). The high protein content of the genotypes in this study suggested the possibility of a similar feature in the parent landraces PSLRC 2, PSLRC 3, PSLRC 4, PSLRC 8, PSLRC 9, and PSLRC 10. These landraces, in addition to the genotypes PYPS 2, PYPS 8, and PYPS 9, offer a significant source of new genetic materials, as well as fortified ingredients for enhancing the nutritional value of sorghum grains. One nutritional constraint to the use of sorghum as food is the poor digestibility of sorghum proteins in cooking (Tesso et al., 2008). Duressa et al. (2020) have reported sorghum accessions with a protein content as high as 15% but with different digestibility percentages (a measure of the susceptibility of protein to proteolysis). For example, the sorghum accession SC663 with a protein content of 15.5% had a high protein digestibility of 70.77%. On the contrary, the sorghum accession SC25 with a protein content of 14.8% had a protein digestibility of 49.73%. Hence, it is important that the sorghum varieties with a high protein content are evaluated for protein digestibility to identify the genotypes with high protein availability.

In the present study, the varieties varied in their grain Fe and Zn concentrations. Phuke et al. (2017) reported a highly significant G × E interaction for Fe and Zn levels in sorghum recombinant inbred lines. They found a significant variation in Fe and Zn across the environments and a significant positive correlation between the Fe and Zn concentrations. While the varied concentrations of Fe and Zn in the present study might be genetically controlled, the effect of the environment and the possible G × E interaction need to be investigated by multi-environment testing of the sorghum genotypes. Shegro et al. (2012) also reported a diversity in nutritional composition among the sorghum landraces and identified the accessions with high concentrations of proteins and minerals (Fe, Fe, Ca, K, Mn, P, and Mg). The variations in mineral contents of the 19 sorghum genotypes in this study may be due to genotype, mineral concentrations in the soil as well as translocation rates of the elements from the soil, as well as environmental factors such as temperature and rainfall or an inherent ability of the genotypes to absorb the nutrients from the soil (Shegro et al., 2012). The assessment of a phenotypic correlation among the protein, starch, sugar, and mineral compositions of the genotypes in this study might have implications for the sorghum crop improvement in relation to human nutrition and livestock feed. Weckwerth et al. (2020) have suggested the use of genomic selection (GS) using genome-wide DNA markers in crop breeding programs to target multiple and complex traits. This can be deployed in a sorghum breeding program to simultaneously target yield, drought tolerance, and nutritional composition including protein, starch, Fe, and Zn. Not just for sorghum, but such an approach integrating GS with an environment-dependent PANOMICS analysis can improve the productivity, biotic and abiotic stress tolerance, and nutritional value of several crops including pigeonpea, groundnut, chickpea, etc. (Weckwerth et al., 2020).

In cereals, the nutritional quality and end use properties are linked to arabinoxylans (AX) that are the major polymers present in the cell walls of grains (Saulnier et al., 2007). Though wheat AX has been extensively reviewed (Saulnier et al., 2007), limited information is available on sorghum AX concerning the amount, composition, and expression. Nandini and Salimath (2001) reported that the structural features of AX are linked with a good flatbread-making quality in sorghum. PYPS-2, the high yielding, protein-rich, and grain mold-tolerant genotype has a high consumer preference owing to good flatbread-making quality (Jaisimha, 2019), which might be linked to the structure and/or amount of AX. Though the expression is mainly genetically controlled, a positive relationship with the amount of AX and drought has been reported in wheat (Coles et al., 1997). As demonstrated in this study, the 36 landraces and the 19 genotypes were evaluated under rainfed situations where prolonged drought stress is a common occurrence, which may have influenced the AX expression vis-à-vis flat bread-making quality. The evaluation of sorghum genotypes for their AX amount and expression in different environments might help in identifying stable and adaptable cultivars with enhanced nutritional quality. To achieve this, research may first be reoriented toward the understanding of the AX biosynthesis, the identification of the candidate genes, and exploitation of the variation toward the development of new cultivars with improved nutritional quality and processing properties.

The present study reports the development of an elite sorghum breeding material using locally adapted landraces through pedigree breeding for the grain and fodder yield. The study has identified stable environments for grain yield (E5) and fodder yield (E11), which suggest that testing of initial hybrids and varietal trials in these two environments is more discriminating and rewarding to save resources in Telangana, India. The study showed the potential of the collected landraces for the development of high-yielding sorghum varieties suitable for rainfed cultivation in India and spill-over to African subcontinents. The study demonstrated a scope for the utilization of these diverse, locally adapted landraces that have been evolved through a continuous selection by the farmers in varied-agro-climatic zones under low input conditions to develop climate-resilient sorghum cultivars and ultimately contribute to healthy, global food, and feed security.

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

MN, RV, MG, and MP designed the experiment. MN and RV carried out the experiments. MN, RV, MG, and SG analyzed the data. CS, SM, SG, and HK conducted the field experiments with logistical support by MV, KA, and RJ. MS helped in nutrient analysis. MN, RV, and MG wrote the draft manuscript. All authors made contributions toward the compilation of the draft and approved the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.