Morpho-Nutritional Status of Micronutrient Efficient Wheat (Triticum aestivum L.) Genotypes under Changing Environments

Introduction

Micronutrient malnutrition, sometimes known as “hidden hunger,” is a global problem that results in low birth weight, anemia, learning difficulties, higher rates of morbidity and mortality, low job productivity, and high healthcare expenditures [20,3]. Lack of iron (Fe) and zinc (Zn) affects several metabolic processes in humans, including oxygen transport, cell development and differentiation, DNA replication, protein synthesis, reduction of oxidative stress, and defense against brain cancers [17]. The importance of micronutrients in the formation of a well-functioning immune system is well established during the COVID-19 pandemic (WHO 2020) and the efforts to increase Zn and Fe bioavailability through dietary supplementation, food fortification, and dietary diversification have been made to reduce micronutrient malnutrition but the potential methods for reducing global micronutrient deficiency has been anticipated through the production of staple food crop cultivars fortified with micronutrients [16]. The Harvest Plus programme of the CGIAR was conceptualized at mitigating the nutritional deficit targeting high-value crops across the globe. Wheat being a major food crop grown across the world was focused on biofortification [9]  and the project’s major goal is to generate nutritionally enhanced cultivars of common wheat (Triticum aestivum L.) to increase people’s intake of zinc (Zn) and iron (Fe), two micronutrients that are considered to be vital for human health [21]. Advanced elite lines developed through this programme are being utilized by the location-specific breeding programmes in wheat. The genetic improvement towards biofortification necessitates studies on genetic variability for Fe and Zn content in the seed, their inheritance in the plant, and their sinking into the progeny seed. The International Maize and Wheat Improvement Center (CIMMYT, International), with funding from the Harvest Plus Challenge Program and the CGIAR Research Program on Agriculture for Nutrition and Health, oversees a global initiative to create and spread to partners in South Asia high-yielding wheat varieties that contain high levels of grain Zn and Iron [8] According to [16,10]

there is substantial genetic variation across wheat germplasm for several micronutrients, and genetic x environmental interactions play a key role in the inheritance of Fe and Zn content in wheat and other crops. Breeding cultivars with high Fe and Zn content in their seeds is complicated by environmental factors such as soil fertility, soil type, seed characteristics, seed composition, and climate influences [17]. G x E interactions have been viewed as a barrier to crop development for nutritional features [13] because it reduces trait heritability estimates, which may lead to less genetic gain through selection [4].

Thus, it is essential to study the impact of the environment on Fe and Zn content to utilize them to make genetic improvement toward biofortification effective. With this background, preliminary investigation on the study to determine the genetic variability for Fe and Zn content among exotic micronutrient enriched elite genotypes and adapted commercial varieties was undertaken and the impact of seasons/years with the varying environment on the Fe and Zn content in the wheat thus identifying stable genotypes for utilization in hybridization.

Material and Methods

The experimental material comprised of forty-nine zinc and/or iron-enriched Harvest plus genotypes and along with three adapted varieties viz, HD 3086, JAUW 683, RSP 561 were assayed for grain iron and zinc (Table 1).

The experiment was conducted at the geographical location of SKUAST-Jammu, India, during the Rabi season for two consecutive years, 2019-20 and 2020–21, with three replications laid down with randomized complete block design. The site of experiments and conditions are presented in Table 2 & Fig. 1. In the experiment, the size of the plot was 1.0 square meters and agronomic practices followed standard practices used by the breeding program in both year. The soil was subsequently irrigated at 21-25 days after sowing (DAS), 45-60 DAS, 60-70 DAS, 90-95 DAS, 100-105 DAS, and 120-125 DAS respectively. Off this irrigation at CRI stage is most important. On full maturation, randomly five plants were selected from each accession for recording morpho-metric and yield attributing data in march (130 DAS) in both years: 2019-2020 and 2020-2021 involving eight economical traits viz., plant height, number of tillers per plant, days to 50per cent flowering, flag leaf area (cm²), spikelets per spike, days to maturity, 1000 grain weight (g) and grain yield per plant (g).

 Micronutrients Profiling for Zinc and Iron

A combination of tap water, diluted HCl (0.01 N), and distilled water was used to wash the grain samples. Samples were dried in a hot air oven at 60°C for five minutes. Grain was processed and used for future chemical analysis after reaching consistent weight. Grain samples were microwave-digested with HNO₃ by placing 0.5 g of the sample into a PTFE-TFM jar, adding 7 ml of suprapure HNO₃, and predigesting the mixture overnight. The vessel was then sealed and placed in microwave digestion. The heating programme (Multiwave ECO, Anton Paar) was configured with operational parameters of a ramp period of 25 minutes to reach 180 to 190 ^oC and a hold time of 25 minutes at 180 to 190 ^oC [6]  

To ensure the full transfer of content, the samples were thoroughly shaken after being cooled to room temperature and added Milli-Q water. The resulting mixture was passed through a Whatman No. 42 filter before being diluted to a final amount of 100 ml in a volumetric flask using Milli-Q water that contained 1% suprapure HNO3. A spectrophotometer for atomic absorption was used to measure the total Zn and Fe in the digest (AAS). To prepare a reagent blank, a similar process was used but without a sample.

Statistical analysis

The pooled mean analysis of variance (ANOVA) and the year-wise analysis of variance (ANOVA), and the mean performance of ten traits in the fifty-two accessions for the two consecutive years (2019-20 and 2020-21) considered as environments and correlation were done using R software ver. 4.1. K Cluster and Dendrogram Euclideanwere analyzed using Windostat software ver. 9.3.   

Results and Discussion

Analysis of variance revealed the mean sum of squares due to genotype to be highly significant for all traits during both years (Tables 3a and 3b). The pooled ANOVA for genotype and year was found significant (p<0.01) for all the traits while interactions were found significant (p<0.01) for only 1000 grain weight (g) and at p<0.05 for grain yield per plant (Table 3c). Table 4 summarizes the results on environmental variations for yield and yield contributing traits and micronutrient content (Zn & Fe) in fifty-two wheat genotypes grown under Jammu agro-climatic conditions. Significant genetic variation among genotypes is a prerequisite to increasing the concentration of Zn and Fe content in wheat grain through conventional breeding.

Significant differences between treatments at the genotypic level may result from genetic variation of genotypes, whereas significant variations at the annual level and genotype x-year interactions may result from changes in humidity, precipitation, climate, soil conditions, or other cultivation practices used throughout the cropping season [11]. The environment has a big impact on yield and the qualities that make up that yield. Table 4 summarizes the mean data of the morpho-metric characteristics and micronutrient (Zn & Fe) content of 52 accessions for the two following years, 2019-2020 and 2020-2021.

It prominently elucidated the significant variation among the genotype, year, and genotype x year interactions studied. The most stable plant height was recorded in the genotype RSP-561 (100 cm in 2019-20 and 99.67 cm in 2020-21) followed by HP-02 (93.33 cm in 2019-20 and 92.67 cm in 2020-21), HP-29 (87.00 cm in 2019-20 and 86.33 cm in 2020-21) and HP-39 (86.33 cm in 2019-20 and 87.00 cm in 2020-21) whereas the highest plant height was recorded for JAUW-683 (105 cm in 2020-21). For the number of tillers per plant, the most superior and stable performance was attained by the genotype HP-02 (9.33 in 2019-2020 and 10.00 in 2020-21) and HP-48 (8.00 in 2019-2020 and 9.33 in 2020-21). Plant height and number of tillers per plant are the most sensitive to environmental fluctuations. It is indicated that the relatively inconsistent performance of other genotypes was marked due to genotype and environment interaction. For days to 50 per cent of flowering, the genotype HP-04 (94.33 in 2019-2020 and 95.67 in 2020-21) and HD 3086 (94.00 in 2019-2020 and 96.00 in 2020-21) projected the lowest days to 50per cent of flowering which could be directly correlated with early maturity. While the sable genotype was achieved by HP-03 (95.67) and HP-08 (97.33). Plant heights, flag leaves, days to 50 percent of flowering, and seed morphological variation are the primary descriptor for the characterization of germplasm. The leaf morphological traits of the wheat germplasm (9HPYT) under study showed a wide range of variability. Regarding the flag leaf, it was found that RSP-561 (30.23 cm) showed the most consistent trait during the two years investigated, followed by HP-22 (26.23 cm for 2019–20 and 26.57 cm for 2020–21), HP–09 (27.70 cm for 2019–20 and 28.23 cm for 2020–21), and HD 3086. (27.73 cm for 2019-20 and 28.37 cm for 2020-21). While about spikelets per spike, the stable performance was presented by HP-39 (18.67) followed by HP-15 (18.00) and HP-03 (16.33) while in the case of days to maturity, genotype HP-14 (137.67) and lowest days to maturity was recorded in genotype, HP-04 (133.67 in 2019-20) and RSP-561 (133.67 in 2020-21). 1000 grain weight (g) and grain yield per plant (g) are the major economic traits and are important for successful agronomic practices and global demand. Thus, exploiting the highest 1000 grain weight (g) was observed for both the years in genotype HP-47 (46.40g in 2019-20 and 43.63g in 2020-21) followed by HP-21  (43.67 in 2019-20g and 8.87g in 2019-20), whereas for grain yield per plant (g), genotype HP-09 (24.40 g in 2020-21) followed by HP-02 (24.33g in 2020-21) and HP-40 (23.30g in 2020-21) was recorded highest. While the most stable genotype for 1000 grain weight (g) was recorded in HP-06 (37.40) followed by HP-19 (42.33 gm in 2019-20 and 42.50 gm in 2020-21), HP-13 (39.00 gm in 2019-20 and 38.83 gm in 2020-21),  and grain yield per plant (g), was revealed by genotype HP-08 (14.13) followed by HP-26 (14.37 gm), HP-27 (10.47 gm)  and HP-28 (16.03) in 2019-20 and 2020-21, respectively. Highly significant differences among the genotype were observed for both grain Fe and Zn concentration indicating the presence of the sufficient amount of genetic variability for grain Fe and Zn concentration among the genotypes studied. The pooled mean percentage of Zn and Fe in a grain of the fifty-two accessions ranged from 8.00 ppm to 40.67 ppm and 27.33 ppm to 41.67 ppm in Zn and from 9.67 ppm to 88.33 ppm and 28.67 ppm to 72.33 in Fe for 2019-20 and 2020-21, respectively (Fig. 2). The accession HP-45 (41.67 ppm in 2020-21) was recorded to establish the highest Zn content followed by accession HP-41 (40.67 ppm in 2019-20) and HP-02 (40.33 ppm in 2020-21), while the highest Fe content was depicted by HP-49 (88.33ppm in 2019-20 and 72.33 ppm 2020-21) Followed by HP-44 (71 ppm in 2019-20 68.67ppm in 2019-20) and HP-45 (55.00 ppm in 2019-20 and 51.67 in 2020-21). Since grain contains higher amounts of Zn and Fe, harvesting plant may assist in the sustainable exploitation of natural conservation. As a result of polygenic control, environmental or nongenetic factors, and their interaction, few accessions, on the other hand, showed inconsistent Zn and Fe content over two years (G x E interaction). When the performance of the traits was compared between the two years, it was evident that the accessions performed better in the first year for many morpho-metric and yield-attributing variables, including plant height, days to 50% of flowering, flag leaf, spikelets per plants, and Zinc (ppm) (2019-20). The accessions performed superior for a number of  tillers per plant, 1000 grain weight (g), grain yield per plant (g), and iron (ppm)characters in the second consecutive year (2020-21), Overall based on the ten morpho-matric attributes, Zn and Fe content, the accessions HP-08, HP-26, HP-27, HP-28, HP-33, HP-41, and HP-49 displayed a comparable consistent performances pattern in the agro-climatic conditions of the North Western Himalayan region for the two consecutive years studied. HP-33, HP-41, HP-45, and HP-49 had higher Zn and Fe content.

Regarding qualities that contribute to yield, other genotypes behaved differently in both years. The findings showed that genotype-by-environment interactions complicate crop variety development and decrease the efficacy of breeding programmes aimed at improving yield [1]. When the experimental materials for the current study were evaluated during the two years (2019–20 and 2020–21), different patterns of minimum and maximum temperature and rainfall were observed (Fig. 1). This gave researchers the chance to examine how genetic make-up and/or environmental factors affect the level of Fe and Zn [13]. The development of breeding techniques for creating biofortified wheat cultivars is aided by knowledge of the interplay between genotype and environment. Given that genotype x year interactions were significant in the current study for both Fe and Zn content, likely, a sizeable amount of the Fe and Zn content in wheat seed depends on soil conditions, crop management techniques, temperature, precipitation, and these factors (moisture, aeration, and soil pH). In contrast, substantial genotype x location interactions for Zn and Fe concentrations in both wild and cultivated cultivars of wheat were found [7,14,18]. Year-to-year changes in Fe and Zn content were likewise extremely significant in the current investigation, showing that the environmental conditions depicted in Fig. 1 were present. Fifty-two genotypes were divided into eight clusters based on the K mean cluster. The distribution pattern of genotypes in the different cluster is presented in Fig 3.  Cluster VI was the largest cluster consisting of 15 genotypes followed by cluster I (10 genotypes), cluster III 8 genotypes, cluster VII having 7 genotypes, cluster IV (6 genotypes), cluster VIII (3 genotypes), cluster V (2 genotype) and cluster II having 1 genotype.  It is pertinent to mention that all the zinc and iron enrich genotypes were obtained from the Harvest Plus breeding programme and are likely to have some part of common ancestry and thus fall in the same cluster. Similar results have been reported by [2, 15]. The clustering of genotypes from different ecogeographic region into one cluster could be due to the exchange of breeding material among global partners. Dendrogram was achieved from cluster analysis of fifty-two genotypes based on two micronutrients (Zn & Fe) content (Fig 4). According to this grouping, under-study wheat genotypes are divided into seven clusters. Clusters II and VI will can consider the most desirable clusters for selecting the genotype for use in hybridization.

It is possible to simultaneously increase the concentration of zinc and iron in grains by selection because the genotypic and phenotypic correlations between zinc and iron were highly positive (Table 5). By [19,5] similar associations between grain iron and zinc concentration were reported. The genotypic connection between the iron and days to maturity was highly positive, and [19] observed a similar finding. Similar results were found by [20] and the zinc yield had a significantly favorable phenotypic connection with days to maturity. Spikelets per spike and grain weight revealed a substantial positive genotypic connection with grain yield (Table 5). According to [12] the number of effective tillers and grains per spike are the most important traits for grain yield in wheat. From this research, genotypic correlation between grain yield with days to 50 percent flowering and flag leaf area was found significantly negative (-0.158**) and (-0.170*) respectively.

Conclusion

Wide adaptation and consistent performance in a range of circumstances are admirable objectives for resource conservation. To have more success, scientists have concentrated on the phenomenon of genotype environments (G x E) interaction, which enables them to distinguish between genotype performance in various environments and to selectively target suitable genotypes for commercial cultivation to specific environmental niches. Using 10 morpho-nutrient (Zn and Fe content) properties, it was determined that HP-03, HP-06, HP-08, and HP-27 were the consistently performing biofortified wheat accessions. These genotypes might be used for hybridization under the Jammu agro-climatic of the North Western Himalayan region and HP-06, HP-22, HP-33, HP-34, HP-41, HP-44, HP-45, and HP-49 which have high Zn and Fe Concentration. This study showed that the environment and its interaction with genotypes have significant and higher effects than the effects due to genotypes per se on the grain Zn and Fe concentration in wheat. It is, therefore, concluded that improvement of grain Zn and Fe concentration is possible but potentially slow due to substantial influence by the environment.

Acknowledgments

This work was financially supported by the Division of Plant Breeding and Genetics, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Main Campus, Chatha Jammu (J&K).

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