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Pearl millet [Pennisetum glaucum (L.) R. Br.] is one of the world’s hardiest warmseason cereal crop cultivated for food and animal feed in the semi-arid tropics of Asia and Africa. This crop faces terminal drought during rainy and flowering-stage heat stress during summer seasons. Blast is emerging as a serious threat affecting its production and productivity in India. Using wild P. violaceum (Lam) Rich. and pearl millet cultivars, prebreeding populations were developed following backcross method. These populations were evaluated in target ecologies in India at three locations during the 2018 summer season for flowering-stage heat stress and at two locations during the 2018 rainy season for terminal drought stress.Atotal 18 introgression lines (ILs) from Population (Pop) 3 exhibited improved seed set under high heat stress vs. the cultivated parent, whereas no IL was better than the cultivated parent in Pop 4. Under rainfed conditions at Hisar and Bawal, India, 19 ILs from Pop 3 and 16 ILs from Pop 4 showed significantly higher dry fodder yield than the cultivated parents. Further, screening of ILs for five diverse pathotype isolates—Pg 45, Pg 138, Pg 186, Pg 204, and Pg 232—of blast resulted in the identification of resistant ILs. Use of these promising ILs in breeding programs will assist in developing new varieties and hybrids with improved tolerance to biotic and abiotic stresses. The study indicated the genetic differences between the parents involved in crossing and also highlighted the importance of precise phenotyping of wild species for target trait prior to use in prebreeding work.

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a staple food crop of arid and semi-arid regions of Asia and Africa. Forty-five pearl millet populations of Asian and African origin were assessed for genetic diversity using 29 simple sequence repeat (SSR) markers. The SSR-based clustering and structure analyses showed that Asian origin–Asian bred (As-As) and African origin–African bred (Af-Af) populations were distributed across seven clusters, indicating no strong relationship among populations with their geographical origin. Most of the African origin–Asian bred (Af-As) populations had a higher average number of alleles per locus than As-As or Af-Af populations, and the majority of them clustered separately from As-As or Af-Af populations, indicating that introgression of African origin breeding materials led to the development of new gene pools adapted to the Asian region. Fourteen populations representing seven clusters were crossed according to a diallel mating design to generate 91 population hybrids (seeds of direct and reciprocal crossesweremixed) and evaluated at three locations in 2016. All the 91 hybrids when partitioned into three groups based on genetic distance (GD) between parental combinations (low,moderate, and high), revealed no correlation between GD and panmictic midparent heterosis in any of the groups, indicating that grain yield heterosis cannot be predicted based on GD. Two population hybrids (GB 8735 × ICMP 87307 and Sudan I × Ugandi) exhibited high levels of yield heterosis over standard checks and can be further utilized using different breeding schemes to develop high-yielding pearl millet cultivars.

Iron deficiency chlorosis is an important abiotic stress affecting groundnut production worldwide in calcareous and alkaline soils with a pH of 7.5–8.5. To identify genomic regions controlling iron deficiency chlorosis resistance in groundnut, the recombinant inbred line population from the cross TAG 24 × ICGV 86031 was evaluated for associated traits like visual chlorosis rating and SPAD chlorophyll meter reading across three crop growth stages for two consecutive years. Thirty-two QTLs were identified for visual chlorosis rating (3.9%–31.8% phenotypic variance explained [PVE]) and SPAD chlorophyll meter reading [3.8%–11% PVE] across three stages over 2 years. This is the first report of identification of QTLs for iron deficiency chlorosis resistance- associated traits in groundnut. Three major QTLs (>10% PVE) were identified at severe stage, while majority of other QTLs were having small effects. Interestingly, two major QTLs for visual chlorosis rating at 60 days (2013) and 90 days (2014) were located at same position on LG AhXIII. The identified QTLs/markers after validation across diverse genetic material could be used in genomics-assisted breeding.

Pearl millet breeding programs can use this heterotic group information on seed and restorer parents to generate new series of pearl millet hybrids having higher yields than the existing hybrids. Five hundred and eighty hybrid parents, 320 R- and 260 B-lines, derived from 6 pearl millet breeding programs in India, genotyped following RAD-GBS (about 0.9 million SNPs) clustered into 12 R- and 7 B-line groups. With few exceptions, hybrid parents of all the breeding programs were found distributed across all the marker-based groups suggesting good diversity in these programs. Three hundred and twenty hybrids generated using 37 (22 R and 15 B) representative parents, evaluated for grain yield at four locations in India, showed significant differences in yield, heterosis, and combining ability. Across all the hybrids, mean mid- and better-parent heterosis for grain yield was 84.0% and 60.5%, respectively. Groups G12 B × G12 R and G10 B × G12 R had highest heterosis of about 10% over best check hybrid Pioneer 86M86. The parents involved in heterotic hybrids were mainly from the groups G4R, G10B, G12B, G12R, and G13B. Based on the heterotic performance and combining ability of groups, 2 B-line (HGB-1 and HGB-2) and 2 R-line (HGR-1 and HGR-2) heterotic groups were identified. Hybrids from HGB-1 × HGR-1 and HGB-2 × HGR-1 showed grain yield heterosis of 10.6 and 9.3%, respectively, over best hybrid check. Results indicated that parental groups can be formed first by molecular markers, which may not predict the best hybrid combination, but it can reveal a practical value of assigning existing and new hybrid pearl millet parental lines into heterotic groups to develop high-yielding hybrids from the different heterotic groups.

Indian dill seed (Anethum sowa Roxb. ex Fleming) is an important member of family Apiaceae. It is a significant seed spice having many medicinal properties. But, this aromatic herb is still orphan from breeding and crop improvement perspective as no serious attention has been given by breeders. To swift the breeding program, molecular markers play the main role. But due to the paucity of markers, breeding is slower in dill seed. Therefore, an attempt was made to develop the genomic SSR markers in dill seed through next-generation sequencing. A total of 2119.51 Mbp of raw data were generated on the Miseq NGS platform during survey sequencing. In 2,25,956 contigs created by Spades assembler, a total 48,951 repeat motifs were identified. A set of 20,294 primer pairs (dimer to hexamer repeats) were produced. Among detected repeat motifs, 48.89% was mononucleotides. Of 12 primers, 10 (83%) primers could be successfully amplified in dill seed and produced 11 amplicons. During cross-genera amplification of markers, 9 out of 10 primers could be successfully amplified in related genera. Developed markers can also be used to initiate the molecular breeding program, association mapping and to assess the evolutionary relationship among seed spices. Keywords: Anethum, Seed spices, SSR, Transferability

Advancement of internal combustion engines has resulted in engines with increased power, ultimately which increases the loads imposed on the engine block. An engine block is a combination of “n” numbers of cylinder liners. A cylinder liner play’s a vital role by providing the boundaries in which piston reciprocates efficiently. These cylinder liners have capabilities to tolerate high pressure and temperature due to the chemical reactions occurring in the combustion chamber. Most commonly, cast iron and aluminum alloys are the favored materials that are used to manufacture conventional petrol and diesel engine blocks. Also, magnesium alloys are used for performance-oriented vehicles. In this paper, comparison between aluminum (Al-7Si) and magnesium (WE43A) alloy is done on the basis of thermal and stress analysis with help of ANYSIS software.

Forty-five African or Asian origin pearl millet populations bred either in Africa or Asia were investigated to generate information on heterotic pools. They were clustered into seven groups (G1 to G7) when genotyped, using 29 highly polymorphic SSRs. Fourteen parental populations representing these seven marker-based groups were crossed in diallel mating design to generate 91 population hybrids. The hybrids evaluated at three locations in India showed mean panmictic mid-parent heterosis (PMPH) and better-parent heterosis (PBPH) for grain yield ranging from − 21.7 to 62.08% and − 32.51 to 42.99%, respectively. Higher grain yield and heterosis were observed in G2 × G6 (2462 kg ha−1, 43.2%) and G2 × G5 (2455 kg ha−1, 42.8%) marker group crosses compared to the most popular Indian open-pollinated variety (OPV) ICTP 8203. Two heterotic groups, Pearl millet Population Heterotic Pool-1 (PMPHP-1) comprising G2 populations and Pearl millet Population Heterotic Pool-2 (PMPHP-2) comprising G5 and G6 populations, were identified based on hybrid performance, heterosis and combining ability among marker group crosses. Population hybrids from two heterotic groups, PMPHP-1 × PMPHP-2 demonstrated PMPH of 14.75% and PBPH of 6.8%. Populations of PMPHP-1 had linkages with either African or Asian origin populations, whereas PMPHP-2 composed of populations originating in Africa and later bred for Asian environments. Results indicated that parental populations from the two opposite heterotic groups can be used as base populations to derive superior inbred lines to develop high yielding hybrids/cultivars.

Exploring the natural genetic variability and its exploitation for improved Nitrogen Use Efficiency (NUE) in sorghum is one of the primary goals in the modern crop improvement programs. The integrated strategies include high-throughput phenotyping, next generation sequencing (NGS)-based genotyping technologies, and a priori selected candidate gene studies that help understand the detailed physiological and molecular mechanisms underpinning this complex trait. A set of sixty diverse sorghum genotypes was evaluated for different vegetative, reproductive, and yield traits related to NUE in the field (under three N regimes) for two seasons. Significant variations for different yield and related traits under 0 and 50% N confirmed the availability of native genetic variability in sorghum under low N regimes. Sorghum genotypes with distinct genetic background had interestingly similar NUE associated traits. The Genotyping-By-Sequencing based SNPs (>89 K) were used to study the population structure, and phylogenetic groupings identified three distinct groups. The information of grain N and stalk N content of the individuals covered on the phylogenetic groups indicated randomness in the distribution for adaptation under variable N regimes. This study identified promising sorghum genotypes with consistent performance under varying environments, with buffer capacity for yield under low N conditions. We also report better performing genotypes for varied production use—grain, stover, and dual-purpose sorghum having differential adaptation response to NUE traits. Expression profiling of NUE associated genes in shoot and root tissues of contrasting lines (PVK801 and HDW703) grown in varying N conditions revealed interesting outcomes. Root tissues of contrasting lines exhibited differential expression profiles for transporter genes [ammonium transporter (SbAMT), nitrate transporters (SbNRT)]; primary assimilatory (glutamine synthetase (SbGS), glutamate synthase (SbGOGAT[NADH], SbGOGAT[Fd]), assimilatory genes [nitrite reductase (SbNiR[NADH]3)]; and amino acid biosynthesis associated gene [glutamate dehydrogenase (SbGDH)]. Identification and expression profiling of contrasting sorghum genotypes in varying N dosages will provide new information to understand the response of NUE genes toward adaptation to the differential N regimes in sorghum. High NUE genotypes identified from this study could be potential candidates for in-depth molecular analysis and contribute toward the development of N efficient sorghum cultivars.

Exploitation of hybrid vigor using CMS technology has delivered nearly 50% yield gain in pigeonpea. Among various sterility-inducing cytoplasms (A1–A9) reported so far in pigeonpea, A2 and A4 are the two major sources that facilitate hybrid seed production. Recent evidence suggests involvement of micro RNA in vast array of biological processes including plant reproductive development. In pigeonpea, information about the miRNAs is insufficient. In view of this, we sequenced six small RNA libraries of CMS line UPAS 120A and isogenic fertile line UPAS 120B using Illumina technology. Results revealed 316 miRNAs including 248 known and 68 novel types. A total of 637 gene targets were predicted for known miRNAs, while 324 genes were associated with novel miRNAs. Degradome analysis revealed 77 gene targets of predicted miRNAs, which included a variety of transcription factors playing key roles in plant reproduction such as F-box family proteins, apetala 2, auxin response factors, ethylene-responsive factors, homeodomain-leucine zipper proteins etc. Differential expression of both known and novel miRNAs implied roles for both conserved as well as species-specific players. We also obtained several miRNA families such as miR156, miR159, miR167 that are known to influence crucial aspects of plant fertility. Gene ontology and pathway level analyses of the target genes showed their possible implications for crucial events during male reproductive development such as tapetal degeneration, pollen wall formation, retrograde signaling etc. To the best of our knowledge, present study is first to combine deep sequencing of small RNA and degradome for elucidating the role of miRNAs in flower and male reproductive development in pigeonpea.

Sorghum is widely grown as a failsafe crop in semi-arid regions particularly in post rainy season. Though the effect of drought on crop performance is studied widely there are few studies illustrating the association of fodder quality and agronomic traits under drought. To study the interactions we evaluated a set of 24 cultivars under drought for three years in post rainy season. The effect of drought was evident in delayed flowering (by 2 days) and reduce plant height (by 0.98 cm) compared to control. The fodder digestibility traits were reduced (in vitro organic matter digestibility by 2.25 times) under drought. All the plant growth and yield parameters recorded higher heritability compared to fodder quality parameters (

Millets are the strategic food crops in arid and drought-prone ecologies. Millets, by virtue of nature, are very well-adapted to drought conditions and able to produce sustainable yield. Millets have important nutrients that can help prevent micro-nutrient malnutrition. As a result of the adverse effect of climate change and widespread malnutrition, millets have attained a strategic position to sustain food and nutritional security. Although millets can adapt well to the drought ecologies where other cereals fail completely, the yield level is very low under stress. There is a tremendous opportunity to increase the genetic potential of millet crops in dry lands when the genetics of the drought-tolerance mechanism is fully explained. MicroRNAs (miRNAs) are the class of small RNAs that control trait expression. They are part of the gene regulation but little studied in millets. In the present study, novel miRNAs and gene targets were identified from the genomic resources of pearl millet, sorghum, foxtail millet, finger millet, and proso millet through in silico approaches. A total of 1,002 miRNAs from 280 families regulating 23,158 targets were identified using different filtration criteria in five millet species. The unique as well as conserved structural features and functional characteristics of miRNA across millets were explained. About 84 miRNAs were conserved across millets in different species combinations, which explained the evolutionary relationship of the millets. Further, 215 miRNAs controlling 155 unique major drought-responsive genes, transcription factors, and protein families revealed the genetics of drought tolerance that are accumulated in the millet genomes. The miRNAs regulating the drought stress through specific targets or multiple targets showed through a network analysis. The identified genes regulated by miRNA genes could be useful in developing functional markers and used for yield improvement under drought in millets as well as in other crops.

Brown planthopper (BPH), one of the most important pests of the rice (Oryza sativa) crop, becomes catastrophic under severe infestations and causes up to 60% yield loss. The highly disastrous BPH biotype in the Indian sub-continent is Biotype 4, which also known as the South Asian Biotype. Though many resistance genes were mapped until now, the utility of the resistance genes in the breeding programs is limited due to the breakdown of resistance and emergence of new biotypes. Hence, to identify the resistance genes for this economically important pest, we have used a multi-parent advanced generation intercross (MAGIC) panel consisting of 391 lines developed from eight indica founder parents. The panel was phenotyped at the controlled conditions for two consecutive years. A set of 27,041 cured polymorphic single nucleotide polymorphism (SNPs) and across-year phenotypic data were used for the identification of marker&ndash, trait associations. Genome-wide association analysis was performed to find out consistent associations by employing four single and two multi-locus models. Sixty-one SNPs were consistently detected by all six models. A set of 190 significant marker-associations identified by fixed and random model circulating probability unification (FarmCPU) were considered for searching resistance candidate genes. The highest number of annotated genes were found in chromosome 6 followed by 5 and 1. Ninety-two annotated genes identified across chromosomes of which 13 genes are associated BPH resistance including NB-ARC (nucleotide binding in APAF-1, R gene products, and CED-4) domain-containing protein, NHL repeat-containing protein, LRR containing protein, and WRKY70. The significant SNPs and resistant lines identified from our study could be used for an accelerated breeding program to develop new BPH resistant cultivars.

Pigeonpea is one of the important pulse crops grown in many states of India and plays a major role in sustainable food and nutritional security for the smallholder farmers. In order to overcome the productivity barrier the Translational Pigeonpea Genomics Consortium (TPGC) was established, representing research institutes from six different states (Andhra Pradesh, Karnataka, Madhya Pradesh, Maharashtra, Telangana, and Uttar Pradesh) of India. To enhance pigeonpea productivity and production the team has been engaged in deploying modern genomics approaches in breeding and popularizing modern varieties in farmers&rsquo, fields. For instance, new genetic stock has been developed for trait mapping and molecular breeding initiated for enhancing resistance to fusarium wilt and sterility mosaic disease in 11 mega varieties of pigeonpea. In parallel, genomic segments associated with cleistogamous flower, shriveled seed, pods per plant, seeds per pod, 100 seed weight, and seed protein content have been identified. Furthermore, 100 improved lines were evaluated for yield and desirable traits in multi-location trials in different states. Furthermore, a total of 303 farmers&rsquo, participatory varietal selection (FPVS) trials have been conducted in 129 villages from 15 districts of six states with 16 released varieties/hybrids. Additionally, one line (GRG 152 or Bheema) from multi-location trials has been identified by the All India Coordinated Research Project on Pigeonpea (AICRP-Pigeonpea) and released for cultivation by the Central Variety Release Committee (CVRC). In summary, the collaborative efforts of several research groups through TPGC is accelerating genetics gains in breeding plots and is expected to deliver them to pigeonpea farmers to enhance their income and improve livelihood.

The present investigation was performed to assess genetic divergence and heterosis prediction in hybrid parents of pearl millet [Pennisetum glaucum (L.) R Br.] using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. Using 56 SSR loci, 412 alleles were detected in 147 lines with an average of 7.36 alleles per locus, and 75,007 SNP loci were detected in 117 lines. Both SSR- and SNP-based clustering and structure analysis partitioned all maintainer (B) and restorer (R) lines into two clear-cut separate groups, indicating the existence of two diverse gene pools, each representing the seed and restorer parents in pearl millet. Results of analysis of molecular variance and principal coordinate analysis also showed significant diversity between B and R lines. The correlation between parental genetic distances estimated based on SSRs and SNPs was high and significant (r = 0.58, p < .01). Similar clustering pattern of hybrid parents was observed with both marker systems, although the cost of genotyping was 41% less with SNPs than with SSRs, and the ratio of loci detected with SNPs was much higher (1:364 SSR/SNP), hence the use of SNPs is indicated over SSRs for germplasm characterization. A set of 136 hybrids (including all B × B, R × R, and B × R crosses) generated crossing 17 hybrid parents (nine B lines and eight R lines) in half diallel (without reciprocal) fashion, and evaluation at two locations revealed that the correlation between genetic distance and better parent heterosis for grain yield was moderate, positive, and significant (with SSR, 0.33, p < .01; with SNP, 0.35, p < .01), hence both SSRs and SNPs were found comparable in results for heterosis prediction.

Three bacteria, IC-59, IC-76A and IC-2002, isolated from the nodules of chickpea, were characterized for nodulation, nitrogen fixation, plant growth-promoting (PGP) and yield traits in five cultivars of chickpea such as BG256, RSG888, Subhra, K850 and ICCV2. All the bacteria produced cellulase, protease, β-1,3-glucanase, indole acetic acid, siderophore, hydro cyanic acid and 1-aminocyclopropane-1-carboxylate deaminase while none produced lipase and chitinase. The 16 S rDNA gene sequences of IC-59, IC-76A and IC-2002 were found to match closely with Rhizobium pusense, Paraburkholderia kururiensis and Stenotrophomonas maltophilia, respectively. The three bacteria nodulated all the cultivars of chickpea well, amplified nifH gene and fixed nitrogen. Under greenhouse conditions at 30 and 45 days after sowing, treatment of five cultivars of chickpea with bacterial cultures IC-59, IC-76A and IC-2002, enhanced the nodule number (up to 45%, 38% and 43%), nodule weight (up to 31%, 15% and 39%), shoot weight (11%, 16% and 14%) and root weight (37%, 48% and 62%), respectively, over the un-inoculated control. At crop maturity, IC-59, IC-76A and IC-2002 were found to enhance the shoot weight (16%, 40% and 26%), pod number (37%, 69% and 81%), pod weight (17%, 45% and 49%), seed number (21%, 31% and 39%) and seed weight (14%, 56% and 65%), respectively, over the un-inoculated control. Among the five cultivars, Subhra was found to enhance most of the PGP traits when treated with the three diazotrophic bacteria. It is concluded that the three diazotrophic bacteria could be potentially exploited for improving nodulation, nitrogen fixation, PGP and yields of chickpea.

Pearl millet is a non-model grain and fodder crop adapted to extremely hot and dry environments globally. In India, a great deal of public and private sectors’ investment has focused on developing pearl millet single cross hybrids based on the cytoplasmic-genetic male sterility (CMS) system, while in Africa most pearl millet production relies on open pollinated varieties. Pearl millet lines were phenotyped for both the inbred parents and hybrids stage. Many breeding efforts focus on phenotypic selection of inbred parents to generate improved parental lines and hybrids. This study evaluated two genotyping techniques and four genomic selection schemes in pearl millet. Despite the fact that 6× more sequencing data were generated per sample for RAD-seq than for tGBS, tGBS yielded more than 2× as many informative SNPs (defined as those having MAF > 0.05) than RAD-seq. A genomic prediction scheme utilizing only data from hybrids generated prediction accuracies (median) ranging from 0.73-0.74 (1000-grain weight), 0.87-0.89 (days to flowering time), 0.48-0.51 (grain yield) and 0.72-0.73 (plant height). For traits with little to no heterosis, hybrid only and hybrid/inbred prediction schemes performed almost equivalently. For traits with significant mid-parent heterosis, the direct inclusion of phenotypic data from inbred lines significantly (P < 0.05) reduced prediction accuracy when all lines were analyzed together. However, when inbreds and hybrid trait values were both scored relative to the mean trait values for the respective populations, the inclusion of inbred phenotypic datasets moderately improved genomic predictions of the hybrid genomic estimated breeding values. Here we show that modern approaches to genotyping by sequencing can enable genomic selection in pearl millet. While historical pearl millet breeding records include a wealth of phenotypic data from inbred lines, we demonstrate that the naive incorporation of this data into a hybrid breeding program can reduce prediction accuracy, while controlling for the effects of heterosis per se allowed inbred genotype and trait data to improve the accuracy of genomic estimated breeding values for pearl millet hybrids.

Genetic distances between hybrid parents based on phenotypic traits and molecular markers were investigated to assess their relationship with heterosis for grain and stover yield and other traits in pearl millet (Pennisetum glaucum [L.] R. Br.). Fifty-one hybrids developed using 101 hybrid parents (B and R lines) and showing a wide range of genetic distance between their parents based on eight phenotypic traits and 28–38 SSRs were evaluated in two sets for two seasons. The correlation between Euclidean distance (phenotypic distance, ED) and simple matching distance (molecular distance, SM) for parents of both sets was low but positive and significant (r = 0.2, P

Post flowering stalk rot (PFSR) is one of the major biotic constraints to maize production in tropical and sub-tropical environments. It is a complex disease caused by multiple pathogens, among which Fusarium moniliforme and Macrophomina phaseolina are the major ones that cause severe yield losses in the Asian tropics. A set of maize inbred lines was evaluated at two locations for Fusarium stalk rot (FSR) and Macrophomina stalk rot (MSR). Based on line evaluation trials, resistant and susceptible lines were selected and crossed following a Diallel mating design IV to study the gene action for resistance to these stalk rots and the estimating the combining ability of inbred lines. A 9 × 9 diallel (Diallel-A) produced 36 hybrids for studying FSR resistance, and a 12 × 12 diallel (Diallel-B) produced 66 hybrids to analyse the resistance towards both FSR and MSR. These hybrids were evaluated at two locations for MSR and one location for FSR with artificial inoculation. The hybrids differed significantly for FSR (p

The All India Coordinated Rice Improvement Project of ICAR-Indian Institute of Rice Research, Hyderabad organizes multi-location testing of elite lines and hybrids to test and identify new rice cultivars for the release of commercial cultivation in India. Data obtained from Initial Hybrid Rice Trials of three years were utilized to understand the genotype × environment interaction (GEI) patterns among the test locations of five different agro-ecological regions of India using GGE and AMMI biplot analysis. The combined analysis of variance and AMMI ANOVA for a yield of rice hybrids were highly significant for GEI. The GGE biplots first two PC explained 54.71%, 51.54% and 59.95% of total G + GEI variation during 2010, 2011 and 2012, respectively, whereas AMMI biplot PC1 and PC2 explained 46.62% in 2010, 36.07% in 2011 and 38.33% in 2012 of the total GEI variation. Crossover interactions, i.e. genotype rank changes across locations were observed. GGE biplot identified hybrids, viz. PAN1919, TNRH193, DRH005, VRH639, 26P29, Signet5051, KPH385, VRH667, NIPH101, SPH497, RH664 Plus and TNRH222 as stable rice hybrids. The discriminative locations identified in different test years were Coimbatore, Maruteru, VNR, Jammu, Raipur, Ludhiana, Karjat and Dabhoi. The AMMI1 biplot identified the adaptable rice hybrids viz., CNRH102, DRH005, NK6303, NK6320, DRRH78, NIPH101, Signet5050, BPH115, Bio452, NPSH2003, and DRRH83. The present study demonstrated that AMMI and GGE biplots analyses were successful in assessing genotype by environment interaction in hybrid rice trials and aided in the identification of stable and adaptable rice hybrids with higher mean and stable yields.

The dearth of proper delineation for energy sorghum cultivation has led to a prerequisite for evaluation and identification of test environments for the newly developed lines. This becomes of vital importance as the biomass yield is highly influenced by genotype and environmental (G × E) interactions. Several agronomic traits were considered to assess the biomass yield and the combined analysis of variance for G (genotype), L (location) and interaction effect of G × L. The variations in the yield caused by the interaction of G × L are very essential to acquire knowledge on the specific adaptation of a genotype. Thus, the multi-location trials conducted across locations and years have helped to identify the stable environments with specific adaptation for biomass sorghum. The presence of close association between the test locations suggested that the same information about the genotypes could be obtained from fewer test environments, and hence the potential to reduce evaluation costs. The two genotypes—IS 13762 and ICSV 25333—have shown stable performance for biomass traits across all the locations, in comparison with CSH 22SS (check). The top ten entries with stable and better performance for fresh biomass yield, dry biomass yield, grain yield and theoretical ethanol yield were ICSV 25333, IS 13762, CSH 22SS, IS 25302, IS 25301, IS 27246, IS 16529, DHBM2, ICSSH 28 and IS 17349.

A survey was conducted in 2014 to determine the prevalence of fungal diseases on sorghum across different agroecological zones in Tanzania and Uganda. In Tanzania, 37 sorghum fields were sampled in Dodoma and Singida Provinces, representing the central drier areas, and in Simiyu, Shinyanga, Mwanza, and Mara Provinces, representing the lake-zone region. In Uganda, 134 fields were sampled across four agroecological zones of Teso, Western, Northern, and West Nile. Farmers were purposively selected, and at least 30 plants per field along two diagonal transects were visually assessed for disease. Ten and 14 diseases were identified in Tanzania and Uganda, respectively. Among the major diseases identified, those more prevalent in Tanzania than in Uganda were leaf blight caused by Setosphaeria turcica (P = 0.0031) and rust caused by Puccinia purpurea (P < 0.0001). Major diseases more prevalent in Uganda than in Tanzania were anthracnose caused by Colletotrichum sublineola (P = 0.0207) and zonate leaf spot caused by Gloeocercospora sorghi (P = 0.0312). We report for the first time the occurrence of ladder leaf spot caused by Cercospora fusimaculans in Uganda and confirm its occurrence in Tanzania. This is the first comprehensive sorghum disease survey report in over 15 years in both countries.

The staple crops, maize, sorghum, bambara nut, groundnut, and sunflower common in semi-arid agro-pastoral farming systems of central Tanzania are prone to aflatoxin contamination. Consumption of such crop produce, contaminated with high levels of aflatoxin B1 (AFB1), affects growth and health. In this paper, aflatoxin contamination in freshly harvested and stored crop produce from central Tanzania was examined, including the efficacy of aflatoxin mitigation technologies on grain/kernal quality. A total of 312 farmers were recruited, trained on aflatoxin mitigation technologies, and allowed to deploy the technologies for 2 years. After 2 years, 188 of the 312 farmers were tracked to determine whether they had adopted and complied with the mitigation practices. Aflatoxigenic Aspergillus flavus and aflatoxin B1 contamination in freshly harvested and stored grains/kernels were assessed. A. flavus frequency and aflatoxin production by fungi were assayed by examining culture characteristics and thin-layer chromatography respectively. AFB1 was assayed by enzyme-linked immunosorbent assay. The average aflatoxin contamination in freshly harvested samples was 18.8 μg/kg, which is above the acceptable standard of 10 μg/kg. Contamination increased during storage to an average of 57.2 μg/kg, indicating a high exposure risk. Grains and oilseeds from maize, sorghum, and sunflower produced in aboveground reproductive structures had relatively low aflatoxin contamination compared to those produced in geocarpic structures of groundnut and bambara nut. Farmers who adopted recommended post-harvest management practices had considerably lower aflatoxin contamination in their stored kernels/grains. Furthermore, the effects of these factors were quantified by multivariate statistical analyses. Training and behavioral changes by farmers in their post-harvest practice minimize aflatoxin contamination and improve food safety. Moreover, if non-trained farmers receive mitigation training, aflatoxin concentration is predicted to decrease by 28.9 μg/kg on average.

Soil erosion and shifting cultivation are the major constraints to agriculture in the north-eastern region of India. Low acceptance of cost-intensive soil conservation technologies (e.g., terracing) calls for developing low-cost erosion control measures. Thus, a field experiment was conducted during the monsoon period of 2008 and 2009, in runoff plots on a land slope of 40% to test the hypothesis that weed cover, if properly managed, minimizes soil erosion and improves soil productivity. The treatments implemented in duplicates were: maize (Zea mays) under shifting cultivation (T1), maize on contour lines (T2), groundnut (Arachis hypogea) on upper and maize on lower half of treatment plot, with both on contour lines (T3), groundnut on contour lines (T4) and maize on contour lines with natural vegetation as buffer strips (T5). The average sediment concentration of runoff water varied from 5.20 g L−1 (T1) to 1.07 g L−1 (T5) in 2008 and from 3.84 (T1) to 0.89 g L−1 (T5) in 2009. The soil loss ranged from 20.8 (T1) to 4.7 Mg ha−1 (T5), with corresponding loss of 670–147 kg ha−1 of SOC, 6.85–1.48 kg ha−1 of available N, and 2.14–0.87 kg ha−1 of available P. Weed strips and weed mulch on the upstream side of maize rows in T5 led to formation of stable mini-terraces promoting better plant and root growth. This study indicates cover management involving selective weed retention can reduce soil erosion, favourably modify land slope and promotes soil productivity.

Genetic diversity in the breeding materials is an essential component to improve the efficiency of any crop improvement programme. In present study, 150 seed and restorer parents were evaluated for grain yield and its component traits at two diverse agro-ecologies CCSHAU-Hisar and ICRISAT-Patancheru. Analysis of variance revealed significant differences among hybrid parents for all traits. Clustering of hybrid parents clearly partitioned almost all the B- and R-lines into separate groups indicating B- and R-lines to be genetically distant from each other. Further, seed (B-lines) and restorer (R-lines) parents were found distributed in four clusters each, and hybrid parents having same plant type (having similar set of specific traits) were found in same cluster. Significant numbers of hybrid parents having common parent in their pedigrees were found in same cluster. Cluster B-IV of B-lines and cluster R-III of R-lines had higher grain yield and above average performance for other grain linked traits. Grain yield was found to have highly positive significant correlation with all the traits under study for both B- and R-lines, except for effective tillers plant-1. Stover yield followed by panicle girth and panicle length had highest positive direct effect on grain yield.

Fusarium wilt (FW) is one of the most important biotic stresses causing yield losses in pigeonpea. Genetic improvement of pigeonpea through genomics-assisted breeding (GAB) is an economically feasible option for the development of high yielding FW resistant genotypes. In this context, two recombinant inbred lines (RILs) (ICPB 2049 × ICPL 99050 designated as PRIL_A and ICPL 20096 × ICPL 332 designated as PRIL_B) and one F2 (ICPL 85063 × ICPL 87119) populations were used for the development of high density genetic maps. Genotyping-by-sequencing (GBS) approach was used to identify and genotype SNPs in three mapping populations. As a result, three high density genetic maps with 964, 1101 and 557 SNPs with an average marker distance of 1.16, 0.84 and 2.60 cM were developed in PRIL_A, PRIL_B and F2, respectively. Based on the multi-location and multi-year phenotypic data of FW resistance a total of 14 quantitative trait loci (QTLs) including six major QTLs explaining >10% phenotypic variance explained (PVE) were identified. Comparative analysis across the populations has revealed three important QTLs (qFW11.1, qFW11.2 and qFW11.3) with upto 56.45% PVE for FW resistance. This is the first report of QTL mapping for FW resistance in pigeonpea and identified genomic region could be utilized in GAB.

Mungbean (Vigna radiata (L.) Wilczek) is an important pulse crop in India. A major constraint for improved productivity is the yield loss caused by mungbean yellow mosaic disease (MYMD). This disease is caused by several begomoviruses which are transmitted by the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae). The objective of this study was to identify the predominant begomoviruses infecting mungbean and the major cryptic species of B. tabaci associated with this crop in India. The indigenous B. tabaci cryptic species Asia II 1 was found dominant in Northern India, whereas Asia II 8 was found predominant in Southern India. Repeated samplings over consecutive years indicate a stable situation with, Mungbean yellow mosaic virus strains genetically most similar to a strain from urdbean (MYMV-Urdbean) predominant in North India, strains most similar to MYMV-Vigna predominant in South India, and Mungbean yellow mosaic India virus (MYMIV) strains predominant in Eastern India. In field studies, mungbean line NM 94 showed a high level of tolerance to the disease in the Eastern state of Odisha where MYMIV was predominant and in the Southern state of Andhra Pradesh where MYMV-Vigna was predominant, but only a moderate level of tolerance in the Southern state of Tamil Nadu. However, in Northern parts of India where there was high inoculum pressure of MYMV-Urdbean during the Kharif season, NM 94 developed severe yellow mosaic symptoms. The identification of high level of tolerance in mungbean lines such as ML 1628 and of resistance in black gram and rice bean provides hope for tackling the disease through resistance breeding.

Much of the world’s population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia.

Micronutrient malnutrition is one of the major health problem, especially iron (Fe) and zinc (Zn) deficiencies that are widespread coupled with inadequate food supply in the developing world. Pearl millet grains are a good source of Fe and Zn elements making it a potential staple crop for overcoming hidden-hunger and micronutrient deficiencies. Breeding pearl millet with high levels of grain Zn and Fe contents represents a major opportunity to enhance the intake of these minerals for poor and malnourished people. A precise understanding of the genetic variability, correlation of mineral nutrients, genotype × environment (G × E) interaction is important for developing improved lines with high Fe and Zn content. To get fair estimates, we used a bi-parental recombinant inbred lines (RIL) mapping population representing F2 phenotypic variance. A total of 317 RILs were evaluated for grain iron and zinc content in two seasons, Summer 2016 (E1) and Summer 2017 (E2). The result from the analysis of variance exhibited a large variability for grain Fe and Zn content across the two environments. The G × E for high grain Fe were significant at P 0.01. The mean performance across the two environments data for grain Fe ranged from 22.9 to 154.5 mg kg-1 (ppm) and Zn content ranged from 19.3 to 121 mg kg-1. The correlation coefficient for grain Fe and Zn was 0.9, and 0.8 and across the two (E1 and E2) environments. The value of correlation coefficient (0.9) was found to be highly significant at P 0.01 level, that indicated good opportunities for simultaneous genetic improvement of both iron and zinc contents in pearl millet.

Genetic diversity of 130 forage-type hybrid parents of pearl millet was investigated based on multiple season data of morphological traits and two type of markers: SSRs (Simple sequence repeats) and GBS identified SNPs (Genotyping by sequencing-Single nucleotide polymorphism). Most of the seed and pollinator parents clustered into two clear-cut separate groups based on marker based genetic distance. Significant variations were found for forage related morphological traits at different cutting intervals (first and second cut) in hybrid parents. Across two cuts, crude protein (CP) varied from 11% to 15%, while in vitro organic matter digestibility (IVOMD) varied from 51% to 56%. Eighty hybrids evaluated in multi-location trial along with their parents for forage traits showed that significant heterosis can be realized for forage traits. A low but positive significant correlation found between SSR based genetic distance (GD between parents of hybrid) and heterosis for most of the forage traits indicated that SSR-based GD can be used for predicting heterosis for GFY, DFY and CP in pearl millet. An attempt was made to associate marker-based clusters with forage quality traits, to enable breeders select parents for crossing purposes in forage breeding programs.

Dry root rot (DRR), caused by Macrophomina phaseolina, is a prevalent disease of mungbean in Myanmar, and an emerging problem in South Asia. The pathogen is a polyphagous necrotroph, survives in the soil for many years that results disease mitigation difficult. Managing DRR in mungbean through an integrated approach has been suggested, and the use of resistant varieties is one of the economical methods. The present study aimed to identify sources of resistance against DRR from a mungbean mini-core collection and to characterize the associated M. phaseolina isolates from India and Myanmar. Evaluation of the 296 mungbean mini-core accessions against the isolate MP1 by paper towel method identified 29 accessions with DRR resistance (disease scores: ≤ 3), and 18 of them with the consistent resistance in the repeated experiment. During the screening of 18 resistant accessions in the glasshouse, nine accessions were found DRR resistance in repeated sick pot experiments with ≤10% disease incidence. A subset of 30 accessions was selected from the mini-core collection based on their in vitro DRR reactions. These accessions were evaluated for DRR resistance in the field in Yezin, Myanmar in 2018 and 2019. Out of the 30 accessions, ten accessions were found DRR resistance with ≤10% disease incidence in both years of evaluations. Pooled analysis of percent disease incidence data of 15 accessions common in both glasshouse and field revealed the stability of accessions VI001509AG, VI001244AG, and VI001400AG for DRR resistance across years and locations. The three resistant accessions along with a susceptible check VC693088 were re-evaluated by paper towel method against nine additional M. phaseolina isolates from India (MP3-MP11). The accessions VI001509AG and VI001400AG were resistant to all nine isolates, while accession VI001244AG was resistant to MP5, MP6, and MP7 isolates. These accessions could be used in mungbean DRR resistance breeding programs.

This study was conducted to dissect the genetic basis and to explore the candidate genes underlying one of the important genomic regions on an SBI-10 long arm (L), governing the complex stay-green trait contributing to post-flowering drought-tolerance in sorghum. A fine-mapping population was developed from an introgression line cross&mdash, RSG04008-6 (stay-green) &times, J2614-11 (moderately senescent). The fine-mapping population with 1894 F2 was genotyped with eight SSRs and a set of 152 recombinants was identified, advanced to the F4 generation, field evaluated with three replications over 2 seasons, and genotyped with the GBS approach. A high-resolution linkage map was developed for SBI-10L using 260 genotyping by sequencing&mdash, Single Nucleotide Polymorphism (GBS&ndash, SNPs). Using the best linear unpredicted means (BLUPs) of the percent green leaf area (%GL) traits and the GBS-based SNPs, we identified seven quantitative trait loci (QTL) clusters and single gene, mostly involved in drought-tolerance, for each QTL cluster, viz., AP2/ERF transcription factor family (Sobic.010G202700), NBS-LRR protein (Sobic.010G205600), ankyrin-repeat protein (Sobic.010G205800), senescence-associated protein (Sobic.010G270300), WD40 (Sobic.010G205900), CPK1 adapter protein (Sobic.010G264400), LEA2 protein (Sobic.010G259200) and an expressed protein (Sobic.010G201100). The target genomic region was thus delimited from 15 Mb to 8 genes co-localized with QTL clusters, and validated using quantitative real-time (qRT)&ndash, PCR.

With high global demand, seeds and gum of cluster bean are an essential raw material for various industries. Worldwide the low yield and productivity of guar (Cyamopsis tetragonoloba) create a large gap between demand and supply of guar. Therefore, to upsurge guar production, there is a need to improve the guar at genetic level. The genetic improvement of cluster bean is slower due to insufficient genomic resources, co-dominant marker system especially simple sequence repeats (SSRs) and inadequate information on the variability of germplasm. For development of microsatellite markers in cluster bean, DNA survey sequencing was carried out using the Miseq NGS system. DNA sequencing generated 73,934 sequences which harboured microsatellite repeat sequences. Successfully, a total of 15,399 marker-pairs were designed. The amplicon size ranged between 101–385 base-pairs. To validate the primers and to analyse the diversity in released varieties and germplasm of cluster bean, successfully amplifiable 21 primers pairs were used. With a mean of 2.05 alleles per primers, 21 bands were detected. The polymorphism information content (PIC) for polymorphic markers fluctuated between 0.04 - 0.67 (mean = 0.3). With the average dissimilarity coefficient of 0.11, four clusters were noticed with NJ analysis. The grouping pattern of genotypes indicated a low genetic variability in the guar gene pool. The results of this study suggested that instead of re-circulation of parental lines, hybrid breeding using diverse parents followed by selection should be performed for genetic improvement of cluster bean. Keywords: Cluster bean, Diversity, DNA marker, NGS, SSR

Dry root rot (DRR) is an important emerging disease of mungbean caused by fungus Macrophomina phaseolina. The disease is seed and soil-borne and hence management is difficult. Exploitation of host resistance could be a good option to manage the disease. The objectives of this study were to characterize the isolates of M. phaseolina from three legume crops and to identify resistant sources against DRR of mungbean. Isolates of M. phaseolina from mungbean, urdbean, and vegetable soybean were identified using morphological characteristics and sequencing internal transcribed sequence (ITS) region of 18S rRNA. Isolates of M. phaseolina from urdbean and vegetable soybean were inoculated on susceptible check genotype of mungbean to assess their pathogenicity. Forty three mungbean genotypes were screened against M. phaseolina isolate of mungbean using the paper towel method to identify sources of resistance. Among these genotypes, 9 were resistant in repeated experiment, with disease score ranging from 1.9 to 3.0. Resistant genotypes showing lower disease score, namely IPM99-125, EC693368, and EC693369, were further screened using the sick pot method to confirm their resistance. Among these three genotypes, IPM99-125 showed consistently higher plant survival rate followed by EC693368 and EC693369 as compared to susceptible checks (VC3960-88, KPS1). In addition, these three genotypes were resistant when screened with two strains of M. phaseolina isolated from urdbean and vegetable soybean, with IPM99-125 having lower disease score. The mungbean genotype IPM99-125 could be useful in mungbean breeding programs to develop root rot-resistant varieties.

Pea, one of the founder crops from the Near East, has two wild species: Pisum sativum subsp. elatius, with a wide distribution centered in the Mediterranean, and P. fulvum, which is restricted to Syria, Lebanon, Israel, Palestine and Jordan. Using genome wide analysis of 11,343 polymorphic single nucleotide polymorphisms (SNPs) on a set of wild P. elatius (134) and P. fulvum (20) and 74 domesticated accessions (64 P. sativum landraces and 10 P. abyssinicum), we demonstrated that domesticated P. sativum and the Ethiopian pea (P. abyssinicum) were derived from different P. elatius genepools. Therefore, pea has at least two domestication events. The analysis does not support a hybrid origin of P. abyssinicum, which was likely introduced into Ethiopia and Yemen followed by eco-geographic adaptation. Both P. sativum and P. abyssinicum share traits that are typical of domestication, such as non-dormant seeds. Non-dormant seeds were also found in several wild P. elatius accessions which could be the result of crop to wild introgression or natural variation that may have been present during pea domestication. A sub-group of P. elatius overlaps with P. sativum landraces. This may be a consequence of bidirectional gene-flow or may suggest that this group of P. elatius is the closest extant wild relative of P. sativum.

Motivation Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. Results To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. Availability and implementation More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.

Chickpea (Cicer arietinum L.), a cool-season legume, is increasingly affected by heat-stress at reproductive stage due to changes in global climatic conditions and cropping systems. Identifying quantitative trait loci (QTLs) for heat tolerance may facilitate breeding for heat tolerant varieties. The present study was aimed at identifying QTLs associated with heat tolerance in chickpea using 292 F8-9 recombinant inbred lines (RILs) developed from the cross ICC 4567 (heat sensitive) &times, ICC 15614 (heat tolerant). Phenotyping of RILs was undertaken for two heat-stress (late sown) and one non-stress (normal sown) environments. A genetic map spanning 529.11 cM and comprising 271 genotyping by sequencing (GBS) based single nucleotide polymorphism (SNP) markers was constructed. Composite interval mapping (CIM) analysis revealed two consistent genomic regions harbouring four QTLs each on CaLG05 and CaLG06. Four major QTLs for number of filled pods per plot (FPod), total number of seeds per plot (TS), grain yield per plot (GY) and % pod setting (%PodSet), located in the CaLG05 genomic region, were found to have cumulative phenotypic variation of above 50%. Nineteen pairs of epistatic QTLs showed significant epistatic effect, and non-significant QTL &times, environment interaction effect, except for harvest index (HI) and biomass (BM). A total of 25 putative candidate genes for heat-stress were identified in the two major genomic regions. This is the first report on QTLs for heat-stress response in chickpea. The markers linked to the above mentioned four major QTLs can facilitate marker-assisted breeding for heat tolerance in chickpea.

Pearl millet is a climate resilient crop and one of the most widely grown millets worldwide. Heterotic hybrid development is one of the principal breeding objectives in pearl millet. In a maiden attempt to identify heterotic groups for grain yield, a total of 343 hybrid parental [maintainer (B-) and restorer (R-)] lines were genotyped with 88 polymorphic SSR markers. The SSRs generated a total of 532 alleles with a mean value of 6.05 alleles per locus, mean gene diversity of 0.55, and an average PIC of 0.50. Out of 532 alleles, 443 (83.27%) alleles were contributed by B-lines with a mean of 5.03 alleles per locus. R-lines contributed 476 alleles (89.47%) with a mean of 5.41, while 441 (82.89%) alleles were shared commonly between B- and R-lines. The gene diversity was higher among R-lines (0.55) compared to B-lines (0.49). The unweighted neighbor-joining tree based on simple matching dissimilarity matrix obtained from SSR data clearly differentiated B- lines into 10 sub-clusters (B1 through B10), and R- lines into 11 sub-clusters (R1 through R11). A total of 99 hybrids (generated by crossing representative 9 B- and 11 R- lines) along with checks were evaluated in the hybrid trial. The 20 parents were evaluated in the line trial. Both the trials were evaluated in three environments. Based on per se performance, high sca effects and standard heterosis, F1s generated from crosses between representatives of groups B10R5, B3R5, B3R6, B4UD, B5R11, B2R4, and B9R9 had high specific combining ability for grain yield compared to rest of the crosses. These groups may represent putative heterotic gene pools in pearl millet.

Chickpea is the most important pulse crop globally after dry beans. Climate change and increased cropping intensity are forcing chickpea cultivation to relatively higher temperature environments. To assess the genetic variability and identify heat responsive traits, a set of 296 F8–9 recombinant inbred lines (RILs) of the cross ICC 4567 (heat sensitive) × ICC 15614 (heat tolerant) was evaluated under field conditions at ICRISAT, Patancheru, India. The experiment was conducted in an alpha lattice design with three replications during the summer seasons of 2013 and 2014 (heat stress environments, average temperature 35 °C and above), and post-rainy season of 2013 (non-stress environment, max. temperature below 30 °C). A two-fold variation for number of filled pods (FPod), total number of seeds (TS), harvest index (HI), percent pod setting (%PodSet) and grain yield (GY) was observed in the RILs under stress environments compared to non-stress environment. A yield penalty ranging from 22.26% (summer 2013) to 33.30% (summer 2014) was recorded in stress environments. Seed mass measured as 100-seed weight (HSW) was the least affected (6 and 7% reduction) trait, while %PodSet was the most affected (45.86 and 44.31% reduction) trait by high temperatures. Mixed model analysis of variance revealed a high genotypic coefficient of variation (GCV) (23.29–30.22%), phenotypic coefficient of variation (PCV) (25.69–32.44%) along with high heritability (80.89–86.89%) for FPod, TS, %PodSet and GY across the heat stress environments. Correlation studies (r = 0.61–0.97) and principal component analysis (PCA) revealed a strong positive association among the traits GY, FPod, VS and %PodSet under stress environments. Path analysis results showed that TS was the major direct and FPod was the major indirect contributors to GY under heat stress environments. Therefore, the traits that are good indicators of high grain yield under heat stress can be used in indirect selection for developing heat tolerant chickpea cultivars. Moreover, the presence of large genetic variation for heat tolerance in the population may provide an opportunity to use the RILs in future-heat tolerance breeding programme in chickpea.

Agricultural disciplines are becoming data intensive and the agricultural research data generation technologies are becoming sophisticated and high throughput. On the one hand, high-throughput genotyping is generating petabytes of data; on the other hand, high-throughput phenotyping platforms are also generating data of similar magnitude. Under modern integrated crop breeding, scientists are working together by integrating genomic and phenomic data sets of huge data volumes on a routine basis. To manage such huge research data sets and use them appropriately in decision making, Data Management Analysis & Decision Support Tools (DMASTs) are a prerequisite. DMASTs are required for a range of operations including generating the correct breeding experiments, maintaining pedigrees, managing phenotypic data, storing and retrieving high-throughput genotypic data, performing analytics, including trial analysis, spatial adjustments, identifications of MTAs, predicting Genomic Breeding Values (GEBVs), and various selection indices. DMASTs are also a prerequisite for understanding trait dynamics, gene action, interactions, biology, GxE, and various other factors contributing to crop improvement programs by integrating data generated from various science streams. These tools have simplified scientists’ lives and empowered them in terms of data storage, data retrieval, data analytics, data visualization, and sharing with other researchers and collaborators. This chapter focuses on availability, uses, and gaps in present-day DMASTs.

The low grain iron and zinc densities are well documented problems in food crops, affecting crop nutritional quality especially in cereals. Sorghum is a major source of energy and micronutrients for majority of population in Africa and central India. Understanding genetic variation, genotype × environment interaction and association between these traits is critical for development of improved cultivars with high iron and zinc. A total of 336 sorghum RILs (Recombinant Inbred Lines) were evaluated for grain iron and zinc concentration along with other agronomic traits for 2 years at three locations. The results showed that large variability exists in RIL population for both micronutrients (Iron = 10.8 to 76.4 mg kg−1 and Zinc = 10.2 to 58.7 mg kg−1, across environments) and agronomic traits. Genotype × environment interaction for both micronutrients (iron and zinc) was highly significant. GGE biplots comparison for grain iron and zinc showed greater variation across environments. The results also showed that G × E was substantial for grain iron and zinc, hence wider testing needed for taking care of G × E interaction to breed micronutrient rich sorghum lines. Iron and zinc concentration showed high significant positive correlation (across environment = 0.79; p < 0.01) indicating possibility of simultaneous effective selection for both the traits. The RIL population showed good variability and high heritabilities (>0.60, in individual environments) for Fe and Zn and other traits studied indicating its suitability to map QTL for iron and zinc.

The design and diffusion of context-specific technologies is centrally important in the multi-dimensional, complex farming systems in arid and semi-arid regions. This paper uses a mixed-method framework to characterize the complexity and heterogeneity of smallholder farming systems and identifies constraints to and opportunities for sustainable intensification. Specifically, the study: (i) characterized farm household typologies based on the diversity of livelihood assets; (ii) co-designed context- specific interventions through an iterative participatory process; and (iii) ex-ante evaluated such interventions to inform multiple stakeholders. We explored farming system diversity using data from 224 farm households in western Rajasthan, India. Employing multivariate statistical techniques and participatory validation, we identified 7 distinct farm household types. Participatory appraisal with multiple stakeholders revealed heterogeneity across farm household types. For instance, the interest of farmers in integrating perennial fruit trees even among the rainfed farm household types markedly varied: household type 1 preferred the multipurpose forestry tree, khejri which requires low labor inputs; household type 2 preferred market-oriented horticulture production; household type 3 did not opt for perennials but for small ruminants; and household type 4 (dominated by women) opted for small horticulture kitchen gardens. The study demonstrated the utility of a mixed-methods approach that addresses multi-dimensional heterogeneity to generate insights and assist in co-designing locally appropriate technologies across different farm types and agro-ecological regions to achieve sustainable intensification.

Pigeonpea (Cajanus cajan), a tropical grain legume with low input requirements, is expected to continue to have an important role in supplying food and nutritional security in developing countries in Asia, Africa and the tropical Americas. From whole-genome resequencing of 292 Cajanus accessions encompassing breeding lines, landraces and wild species, we characterize genome-wide variation. On the basis of a scan for selective sweeps, we find several genomic regions that were likely targets of domestication and breeding. Using genome-wide association analysis, we identify associations between several candidate genes and agronomically important traits. Candidate genes for these traits in pigeonpea have sequence similarity to genes functionally characterized in other plants for flowering time control, seed development and pod dehiscence. Our findings will allow acceleration of genetic gains for key traits to improve yield and sustainability in pigeonpea.

Pearl millet is a multipurpose grain/fodder crop of the semi-arid tropics, feeding many of the world’s poorest and most undernourished people. Genetic variation among adapted pearl millet inbreds and hybrids suggests it will be possible to improve grain micronutrient concentrations by selective breeding. Using 305 loci, a linkage map was constructed to map QTLs for grain iron [Fe] and zinc [Zn] using replicated samples of 106 pearl millet RILs (F6) derived from ICMB 841-P3 × 863B-P2. The grains of the RIL population were evaluated for Fe and Zn content using atomic absorption spectrophotometer. Grain mineral concentrations ranged from 28.4 to 124.0 ppm for Fe and 28.7 to 119.8 ppm for Zn. Similarly, grain Fe and Zn in open pollinated seeds ranged between 22.4–77.4 and 21.9–73.7 ppm, respectively. Mapping with 305 (96 SSRs; 208 DArT) markers detected seven linkage groups covering 1749 cM (Haldane) with an average intermarker distance of 5.73 cM. On the basis of two environment phenotypic data, two co-localized QTLs for Fe and Zn content on linkage group (LG) 3 were identified by composite interval mapping (CIM). Fe QTL explained 19% phenotypic variation, whereas the Zn QTL explained 36% phenotypic variation. Likewise for open pollinated seeds, the QTL analysis led to the identification of two QTLs for grain Fe content on LG3 and 5, and two QTLs for grain Zn content on LG3 and 7. The total phenotypic variance for Fe and Zn QTLs in open pollinated seeds was 16 and 42%, respectively. Analysis of QTL × QTL and QTL × QTL × environment interactions indicated no major epistasis.

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped extensively for yield and yield related traits at two different locations (Delhi and Patancheru, India) during the crop seasons 2011–12 and 2012–13 under rainfed and irrigated conditions. In parallel, these lines were also genotyped using DArTseq platform to generate genotyping data for 3000 polymorphic markers. Phenotyping and genotyping data were used with six statistical GS models to estimate the prediction accuracies. GS models were tested for four yield related traits viz. seed yield, 100 seed weight, days to 50% flowering and days to maturity. Prediction accuracy for the models tested varied from 0.138 (seed yield) to 0.912 (100 seed weight), whereas performance of models did not show any significant difference for estimating prediction accuracy within traits. Kinship matrix calculated using genotyping data reaffirmed existence of two different groups within selected lines. There was not much effect of population structure on prediction accuracy. In brief, present study establishes the necessary resources for deployment of GS in chickpea breeding.

Sterility mosaic disease (SMD) is one of the serious production constraints that may lead to complete yield loss in pigeonpea. Three mapping populations including two recombinant inbred lines and one F2, were used for phenotyping for SMD resistance at two locations in three different years. Genotyping-by-sequencing approach was used for simultaneous identification and genotyping of SNPs on above mentioned populations. In total, 212,464, 89,699 and 64,798 SNPs were identified in ICPL 20096 × ICPL 332 (PRIL_B), ICPL 20097 × ICP 8863 (PRIL_C) and ICP 8863 × ICPL 87119 (F2) respectively. By using high-quality SNPs, genetic maps were developed for PRIL_B (1,101 SNPs; 921.21 cM), PRIL_C (484 SNPs; 798.25 cM) and F2 (996 SNPs; 1,597.30 cM) populations. The average inter marker distance on these maps varied from 0.84 cM to 1.65 cM, which was lowest in all genetic mapping studies in pigeonpea. Composite interval mapping based QTL analysis identified a total of 10 QTLs including three major QTLs across the three populations. The phenotypic variance of the identified QTLs ranged from 3.6 to 34.3%. One candidate genomic region identified on CcLG11 seems to be promising QTL for molecular breeding in developing superior lines with enhanced resistance to SMD.

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries.

Fusarium wilt (Fusarium udum Butler) is an important biotic constraint to pigeonpea (Cajanus cajan L.) production worldwide. Breeding for fusarium wilt resistance continues to be an integral part of genetic improvement of pigeonpea. Therefore, the study was aimed at identifying and validating resistant genotypes to fusarium wilt and determining the magnitude of genotype × environment (G × E) interactions through multi-environment and multi-year screening. A total of 976 genotypes including germplasm and breeding lines were screened against wilt using wilt sick plot at Patancheru, India. Ninety two genotypes resistant to wilt were tested for a further two years using wilt sick plot at Patancheru. A Pigeonpea Wilt Nursery (PWN) comprising of 29 genotypes was then established. PWN was evaluated at nine locations representing different agro-climatic zones of India for wilt resistance during two crop seasons 2007/08 and 2008/09. Genotypes (G), environment (E), and G × E interactions were examined by biplot which partitioned the main effect into G, E, and G × E interactions with significant levels (p ≤ 0.001) being obtained for wilt incidence. The genotype contributed 36.51% of resistance variation followed by the environment (29.32%). A GGE biplot integrated with a boxplot and multiple comparison tests enabled us to identify seven stable genotypes (ICPL 20109, ICPL 20096, ICPL 20115, ICPL 20116, ICPL 20102, ICPL 20106, and ICPL 20094) based on their performance across diverse environments. These genotypes have broad based resistance and can be exploited in pigeonpea breeding programs.

Axiom Cajanus SNP array revealed genetic architecture and temporal diversity in pigeonpea varieties. As one of the major outputs of next‐generation sequencing (NGS), a large number of genome‐wide single‐nucleotide polymorphisms (SNPs) have been developed in pigeonpea [Cajanus cajan (L.) Huth.]. However, SNPs require a genotyping platform or assay to be used in different evolutionary studies or in crop improvement programs. Therefore, we developed an Axiom Cajanus SNP array with 56K SNPs uniformly distributed across the genome and assessed its utility in a genetic diversity study. From the whole‐genome resequencing (WGRS) data on 104 pigeonpea lines, ∼2 million sequence variations (SNPs and insertion–deletions [InDels]) were identified, from which a subset of 56,512 unique and informative sequence variations were selected to develop the array. The Axiom Cajanus SNP array developed was used for genotyping 103 pigeonpea lines encompassing 63 cultivars released between 1960 and 2014 and 40 breeding, germplasm, and founder lines. Genotyping data thus generated on 103 pigeonpea lines provided 51,201 polymorphic SNPs and InDels. Genetic diversity analysis provided in‐depth insights into the genetic architecture and trends in temporal diversity in pigeonpea cultivars. Therefore, the continuous use of the high‐density Axiom Cajanus SNP array developed will accelerate high‐resolution trait mapping, marker‐assisted breeding, and genomic selection efforts in pigeonpea.

Pearl millet is a climate-resilient nutritious crop requiring low inputs and is capable of giving economic returns in marginal agro-ecologies. In this study, we report large-effect iron (Fe) and zinc (Zn) content quantitative trait loci (QTLs) using diversity array technology (DArT) and simple sequence repeats (SSRs) markers to generate a genetic linkage map using 317 recombinant inbred line (RIL) population derived from the (ICMS 8511-S1-17-2-1-1-B-P03 × AIMP 92901-S1-183-2-2-B-08) cross. The base map [seven linkage groups (LGs)] of 196 loci was 964.2 cM in length (Haldane). AIMP 92901-S1-183-2-2-B-08 is an Iniadi line with high grain Fe and Zn, tracing its origin to the Togolese Republic, West Africa. The content of grain Fe in the RIL population ranged between 20 and 131 ppm (parts per million), and that of Zn from 18 to 110 ppm. QTL analysis revealed a large number of QTLs for high grain iron (Fe) and zinc (Zn) content. A total of 19 QTLs for Fe and Zn were detected, of which 11 were for Fe and eight were for Zn. The portion of the observed phenotypic variance explained by different QTLs for grain Fe and Zn content varied from 9.0 to 31.9% (cumulative 74%) and from 9.4 to 30.4% (cumulative 65%), respectively. Three large-effect QTLs for both minerals were co-mapped in this population, one on LG1 and two on LG7. The favorable QTL alleles of both mineral micronutrients were contributed by the male parent (AIMP 92901-deriv-08). Three putative epistasis interactions were observed for Fe content, while a single digenic interaction was found for Zn content. The reported QTLs may be useful in marker-assisted selection (MAS) programs, in genomic selection (GS) breeding pipelines for seed and restorer parents, and in population improvement programs for pearl millet.

Combining morphological and molecular data to identify genetic variation and marker–trait association is one of the most important prerequisites for genomics-assisted selection in crop improvement. To this end, a total of 138 finger millet (Eleusine coracana subsp. coracana) accessions including five improved varieties were evaluated to assess the genetic variation and population structure and undertake association mapping. These accessions were basically collected from Ethiopia (96), Eritrea (8), Kenya (7), Zambia (9) and Zimbabwe (13). Finger millet accessions were evaluated in the field for 10 important agronomic traits and also characterised using a set of 20 microsatellite markers. Mean polymorphism information content of 0.61 was observed from a total of 222 alleles with an average of 11.1 alleles per microsatellite locus. About 61% of alleles detected were rare (