International Crops Research Institute for the Semi-Arid Tropics
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Shooting shadows: India’s struggle to reduce the burden of anaemia
Get PDFDespite several efforts by the Government of India, the national burden of anaemia remains high and its growing prevalence (between 2015–2016 and 2019–2021) is concerning to India’s public health system. This article reviews existing food-based and clinical strategies to mitigate the
anaemia burden and why they are premature and insufficient. In a context where multiple anaemia control programmes are in play, this article proposes a threefold strategy for consideration. First, except the Comprehensive National Nutrition Survey, 2016–2018, which measured Hb concentration among children and adolescents aged 1–19 years using venous blood samples, all national surveys use capillary blood samples to determine Hb levels, which could be erroneous. The Indian government should prioritise conducting a nationwide survey for estimating the burden of anaemia and its clinical determinants for all age groups using venous blood samples. Second, without deciding the appropriate dose of Fe needed for an individual, food fortification programmes that are often compounded with layering of other micronutrients could be harmful and further research on this issue is needed. Same is true for the pharmacological intervention of Fe tablet or syrup supplementation programmes, which is given to individuals without assessing its need. In addition, there is a dire need for robust research to understand both the long-term benefit and side effects of Fe supplementation programmes. Third and final, the WHO is in process of reviewing the Hb threshold
for defining anaemia, therefore the introduction of new anaemia control programmes should be restrained
NIR Instruments and Prediction Methods for Rapid Access to Grain Protein Content in Multiple Cereals
Get PDFAchieving global goals for sustainable nutrition, health, and wellbeing will depend on delivering enhanced diets to humankind. This will require instantaneous access to information on food-source quality at key points of agri-food systems. Although laboratory analysis and benchtop NIR spectrometers are regularly used to quantify grain quality, these do not suit all end users, for example, stakeholders in decentralized agri-food chains that are typical in emerging economies. Therefore, we explored benchtop and portable NIR instruments, and the methods that might aid these particular end uses. For this purpose, we generated NIR spectra for 328 grain samples from multiple cereals (finger millet, foxtail millet, maize, pearl millet, and sorghum) with a standard benchtop NIR spectrometer (DS2500, FOSS) and a novel portable NIR-based instrument (HL-EVT5, Hone). We explored classical deterministic methods (via winISI, FOSS), novel machine learning (ML)-driven methods (via Hone Create, Hone), and a convolutional neural network (CNN)-based method for building the calibrations to predict grain protein out of the NIR spectra. All of the tested methods enabled us to build relevant calibrations out of both types of spectra (i.e., R2 ≥ 0.90, RMSE ≤ 0.91, RPD ≥ 3.08). Generally, the calibration methods integrating the ML techniques tended to enhance the prediction capacity of the model. We also documented that the prediction of grain protein content based on the NIR spectra generated using the novel portable instrument (HL-EVT5, Hone) was highly relevant for quantitative protein predictions (R2 = 0.91, RMSE = 0.97, RPD = 3.48). Thus, the presented findings lay the foundations for the expanded use of NIR spectroscopy in agricultural research, development, and trade
Whole-genome sequencing based discovery of candidate genes and diagnostic markers for seed weight in groundnut
Get PDFSeed weight in groundnut (Arachis hypogaea L.) has direct impact on yield as well as market price because of preference for bold seeds by consumers and industry, thereby making seed-size improvement as one of the most important objectives of groundnut breeding programs globally. Marker-based early generation selection can accelerate the process of breeding for developing large-seeded varieties. In this context, we deployed the quantitative trait locus-sequencing (QTL-seq) approach on a biparental mapping population (Chico × ICGV 02251) to identify candidate genes and develop markers for seed weight in groundnut. A total of 289.4–389.4 million reads sequencing data were generated from three libraries (ICGV 02251 and two extreme bulks) achieving 93.9–95.1% genome coverage and 8.34–9.29× average read depth. The analysis of sequencing data using QTL-seq pipeline identified five genomic regions (three on chromosome B06 and one each on chromosomes B08 and B09) for seed weight. Detailed analysis of above associated genomic regions detected 182 single-nucleotide polymorphisms (SNPs) in genic and intergenic regions, and 11 of these SNPs were nonsynonymous in the genomic regions of 10 candidate genes including Ulp proteases and BIG SEED locus genes. Kompetitive allele specific polymerase chain reaction (KASP) markers for 14 SNPs were developed, and four of these markers (snpAH0031, snpAH0033, snpAH0037, and snpAH0038) were successfully validated for deployment in breeding for large-seeded groundnut varieties
A superior gene allele involved in abscisic acid signaling enhances drought tolerance and yield in chickpea
Get PDFIdentifying potential molecular tags for drought tolerance is essential for achieving higher crop productivity under drought stress. We employed an integrated genomics-assisted breeding and functional genomics strategy involving association mapping, fine mapping, map-based cloning, molecular haplotyping and transcript profiling in the introgression lines (ILs)- and near isogenic lines (NILs)-based association panel and mapping population of chickpea (Cicer arietinum). This combinatorial approach delineated a bHLH (basic helix–loop–helix) transcription factor, CabHLH10 (Cicer arietinum bHLH10) underlying a major QTL, along with its derived natural alleles/haplotypes governing yield traits under drought stress in chickpea. CabHLH10 binds to a cis-regulatory G-box promoter element to modulate the expression of RD22 (responsive to desiccation 22), a drought/abscisic acid (ABA)-responsive gene (via a trans-expression QTL), and two strong yield-enhancement photosynthetic efficiency (PE) genes. This, in turn, upregulates other downstream drought-responsive and ABA signaling genes, as well as yield-enhancing PE genes, thus increasing plant adaptation to drought with reduced yield penalty. We showed that a superior allele of CabHLH10 introgressed into the NILs improved root and shoot biomass and PE, thereby enhancing yield and productivity during drought without compromising agronomic performance. Furthermore, overexpression of CabHLH10 in chickpea and Arabidopsis (Arabidopsis thaliana) conferred enhanced drought tolerance by improving root and shoot agro-morphological traits. These findings facilitate translational genomics for crop improvement and the development of genetically tailored, climate-resilient, high-yielding chickpea cultivars
Whole Genome Sequencing and Morphological Trait-Based Evaluation of UPOV Option 2 for DUS Testing in Rice
Get PDFTo evaluate the application potential of high-density SNPs in rice distinctness, uniformity, and stability (DUS) testing, we screened 37,929 SNP loci distributed on 12 rice chromosomes based on whole-genome resequencing of 122 rice accessions. These SNP loci were used to analyze the DUS testing of rice varieties based on the correlation between the molecular and phenotypic distances of varieties according to UPOV option 2. The results showed that statistical algorithms and the number of phenotypic traits and SNP loci all affected the correlation between the molecular and phenotypic distances of rice varieties. Relative to the other nine algorithms, the Jaccard similarity algorithm had the highest correlation of 0.6587. Both the number of SNPs and the number of phenotypes had a ceiling effect on the correlation between the molecular and phenotypic distances of varieties, and the ceiling effect of the number of SNP loci was more obvious. To overcome the correlation bottleneck, we used the genome-wide prediction method to predict 30 phenotypic traits and found that the prediction accuracy of some traits, such as the basal sheath anthocyanin color, glume length, and intensity of the green color of the leaf blade, was very low. In combination with group comparison analysis, we found that the key to overcoming the ceiling effect of correlation was to improve the resolution of traits with low predictive values. In addition, we also performed distinctness testing on rice varieties by using the molecular distance and phenotypic distance, and we found that there were large differences between the two methods, indicating that UPOV option 2 alone cannot replace the traditional phenotypic DUS testing. However, genotype and phenotype analysis together can increase the efficiency of DUS testing
Molecular profiling of BADH2 locus reveals distinct functional allelic polymorphism associated with fragrance variation in Indian aromatic rice germplasm
No full textAllelic variability of the aroma gene, betaine aldehyde dehydrogenase 2 (BADH2) was studied in a random subset of indigenous aromatic rice germplasm along with a few exotic aromatic accessions. Use of functional markers of four badh2 alleles identified that the test panel possessed only two alleles, badh2-E7 and badh2-p-5′UTR. Two other alleles, badh2.2 and badh2-E4-5.2 were absent. Based on the alleles present, four functional polymorphisms (FP) were detected, namely FP1 to FP4. 188 genotypes possessed FP1 having both the badh2-p-5′UTR and badh2-E7 (71.8%) alleles. The badh2 allele with FP1 is named badh2-E7-p. 39 genotypes (14.9%) possessed only the badh2-p-5′UTR allele (FP3), while three genotypes were found to carry only the badh2-E7 allele (FP2). We also found that 32 genotypes (12.2%) did not have any of the target aroma alleles tested in this study (FP4). Interestingly, for badh2-p-5′UTR marker, the expected 198 bp amplicon for the non-aromatic allele could not be detected among any of the genotypes tested. Instead, an amplicon of 456 bp length appeared with 100% presence in the non-aromatic checks. Notwithstanding, the 456 bp allele also showed a 16% presence among the aromatic lines. This article forms the first report of this allele, named badh2-p1, among aromatic rice. Quantification of 2-Acetyl-1-Pyrroline (2AP) content and sensory evaluation among the test genotypes showed that those with FP1 are highly aromatic than the genotypes carrying other types of FPs. But, a few strongly aromatic lines showed lower 2AP content. The BADH2 characterization carried out in this study is suggestive of identifying the additional gene(s)/ allele(s) governing aroma among the Indian fragrant rice
Analysis of Small RNA Sequencing Data in Plants
Get PDFOver the past decades, next-generation sequencing (NGS) has been employed extensively for investigating the regulatory mechanisms of small RNAs. Several bioinformatics tools are available for aiding biologists to extract meaningful information from enormous amounts of data generated by NGS platforms. This chapter describes a detailed methodology for analyzing small RNA sequencing data using different open source tools. We elaborate on various steps involved in analysis, from processing the raw sequencing reads to identifying miRNAs, their targets, and differential expression studies
Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine (GEE) cloud and spectral matching techniques (SMTs) in support of food and water security
Get PDFCropland products are of great importance in water and food security assessments, especially in South Asia, which is home to nearly 2 billion people and 230 million hectares of net cropland area. In South Asia, croplands account for about 90% of all human water use. Cropland extent, cropping intensity, crop watering methods, and crop types are important factors that have a bearing on the quantity, quality, and location of production. Currently, cropland products are produced using mainly coarse-resolution (250–1000 m) remote sensing data. As multiple cropland products are needed to address food and water security challenges, our study was aimed at producing three distinct products that would be useful overall in South Asia. The first of these, Product 1, was meant to assess irrigated versus rainfed croplands in South Asia using Landsat 30 m data on the Google Earth Engine (GEE) platform. The second, Product 2, was tailored for major crop types using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m data. The third, Product 3, was designed for cropping intensity (single, double, and triple cropping) using MODIS 250 m data. For the kharif season (the main cropping season in South Asia, Jun–Oct), 10 major crops (5 irrigated crops: rice, soybean, maize, sugarcane, cotton; and 5 rainfed crops: pulses, rice, sorghum, millet, groundnut) were mapped. For the rabi season (post-rainy season, Nov–Feb), five major crops (three irrigated crops: rice, wheat, maize; and two rainfed crops: chickpea, pulses) were mapped. The irrigated versus rainfed 30 m product showed an overall accuracy of 79.8% with the irrigated cropland class providing a producer’s accuracy of 79% and the rainfed cropland class 74%. The overall accuracy demonstrated by the cropping intensity product was 85.3% with the producer’s accuracies of 88%, 85%, and 67% for single, double, and triple cropping, respectively. Crop types were mapped to accuracy levels ranging from 72% to 97%. A comparison of the crop-type area statistics with national statistics explained 63–98% variability. The study produced multiple-cropland products that are crucial for food and water security assessments, modeling, mapping, and monitoring using multiple-satellite sensor big-data, and Random Forest (RF) machine learning algorithms by coding, processing, and computing on the GEE cloud
Unraveling Origin, History, Genetics, and Strategies for Accelerated Domestication and Diversification of Food Legumes
Get PDFDomestication is a dynamic and ongoing process of transforming wild species into cultivated species by selecting desirable agricultural plant features to meet human needs such as taste, yield, storage, and cultivation practices. Human plant domestication began in the Fertile Crescent around 12,000 years ago and spread throughout the world, including China, Mesoamerica, the Andes and Near Oceania, Sub-Saharan Africa, and eastern North America. Indus valley civilizations have played a great role in the domestication of grain legumes. Crops, such as pigeon pea, black gram, green gram, lablab bean, moth bean, and horse gram, originated in the Indian subcontinent, and Neolithic archaeological records indicate that these crops were first domesticated by early civilizations in the region. The domestication and evolution of wild ancestors into today’s elite cultivars are important contributors to global food supply and agricultural crop improvement. In addition, food legumes contribute to food security by protecting human health and minimize climate change impacts. During the domestication process, legume crop species have undergone a severe genetic diversity loss, and only a very narrow range of variability is retained in the cultivars. Further reduction in genetic diversity occurred during seed dispersal and movement across the continents. In general, only a few traits, such as shattering resistance, seed dormancy loss, stem growth behavior, flowering–maturity period, and yield traits, have prominence in the domestication process across the species. Thus, identification and knowledge of domestication responsive loci were often useful in accelerating new species’ domestication. The genes and metabolic pathways responsible for the significant alterations that occurred as an outcome of domestication might aid in the quick domestication of novel crops. Further, recent advances in “omics” sciences, gene-editing technologies, and functional analysis will accelerate the domestication and crop improvement of new crop species without losing much genetic diversity. In this review, we have discussed about the origin, center of diversity, and seed movement of major food legumes, which will be useful in the exploration and utilization of genetic diversity in crop improvement. Further, we have discussed about the major genes/QTLs associated with the domestication syndrome in pulse crops and the future strategies to improve the food legume crops
Genetic diversity analysis of East African sorghum (Sorghum bicolor [L.] Moench) germplasm collections for agronomic and nutritional quality traits
Get PDFBreeding for climate-resilient, high-yielding, and nutrient-rich sorghum cultivars is essential for sustainable food
systems and enhanced livelihoods in sub-Saharan Africa. Therefore, this study aimed to determine the genetic
diversity among East African sorghum germplasm collections through agronomic and nutritional quality traits to select promising lines for direct production or breeding. A collection of 348 sorghum germplasm was field evaluated at two locations in Uganda using an augmented design, and grain iron (Fe) and zinc (Zn) contents were profiled. Data were collected on 20 sorghum agro-morphological traits and Fe and Zn compositions. A significant (P 0.60) and genetic advance as percent of the mean (GA >20%) were computed for grain yield, Zn content, and selected agronomic traits, ensuring genetic gains through selection. A significant positive correlation was recorded between Fe and Zn concentrations (r ¼ 0.32, P < 0.001), allowing simultaneous selection for the two nutrient compositions. Cluster analysis based on phenotypic traits resolved the test sorghum genotypes into four distinct genetic groups. Six genotypes with superior agronomic traits and high Fe and Zn contents were identified for production or potential parents for quality breeding. Overall, the current study found considerable genetic variation among East African sorghum germplasm collections for strategic conservation and breeding in Uganda or similar agro-ecologies