International Crops Research Institute for the Semi-Arid Tropics
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Optimizing Crop Yield Estimation through Geospatial Technology: A Comparative Analysis of a Semi-Physical Model, Crop Simulation, and Machine Learning Algorithms
Get PDFThis study underscores the critical importance of accurate crop yield information for national food security and export considerations, with a specific focus on wheat yield estimation at the Gram Panchayat (GP) level in Bareilly district, Uttar Pradesh, using technologies such as machine learning algorithms (ML), the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and semi-physical models (SPMs). The research integrates Sentinel-2 time-series data and ground data to generate comprehensive crop type maps. These maps offer insights into spatial variations in crop extent, growth stages and the leaf area index (LAI), serving as essential components for precise yield assessment. The classification of crops employed spectral matching techniques (SMTs) on Sentinel-2 time-series data, complemented by field surveys and ground data on crop management. The strategic identification of crop-cutting experiment (CCE) locations, based on a combination of crop type maps, soil data and weather parameters, further enhanced the precision of the study. A systematic comparison of three major crop yield estimation models revealed distinctive gaps in each approach. Machine learning models exhibit effectiveness in homogenous areas with similar cultivars, while the accuracy of a semi-physical model depends upon the resolution of the utilized data. The DSSAT model is effective in predicting yields at specific locations but faces difficulties when trying to extend these predictions to cover a larger study area. This research provides valuable insights for policymakers by providing near-real-time, high-resolution crop yield estimates at the local level, facilitating informed decision making in attaining food security
Mitigating agricultural residue burning: challenges and solutions across land classes in Punjab, India
Get PDFIndia faces significant air quality challenges, contributing to local health and global climate concerns. Despite a national ban on agricultural residue burning and various incentive schemes, farmers in northern India continue to face difficulties in curbing open-field burning. Using data
from 1021 farming households in rural Punjab in India, we examine the patterns and drivers of the adoption of no-burn agriculture, particularly for farmers who mulch instead of burning crop residue. We find a growing trend in no-burn farming practices among farmers between 2015 and 2017, with the highest adoption rates among large farmers compared to medium and small farmers. Our findings suggest that access to equipment and learning opportunities may increase the likelihood of farmers using straw as mulch instead of burning it. Specifically, social learning appears to increase the likelihood of farmers embracing no-burn practices relative to learning from extension agencies. Furthermore, the form of learning depends on farm size. While large and medium farmers exhibit a variety of learning strategies, small farmers primarily self-learn. These
results underscore the importance of a multiprong policy that provides sufficient access to equipment and a combination of learning platforms that enabling farmers from different land classes to adopt no-burn technologies
Classification of new germplasm into existing heterotic groups of pearl millet [Pennisetum glaucum (L.) R. Br.]
Get PDFThe study assigned new germplasm, which includes populations and inbreds, to established heterotic groups using various approaches to broaden the existing genetic base while maintaining the heterotic pattern in pearl millet [Pennisetum glaucum (L.) R. Br.]. It utilized 13 pearl millet populations of African and Asian origins and 24 new inbred parents from ICRISAT's breeding program. Testers, both inbred and composite, were employed to categorize these materials into heterotic groups. Different sets of line × tester crosses were generated and evaluated during the rainy season at multiple locations in India. The pearl millet populations were assigned to heterotic group B (seed parental groups) (HGB1 and HGB2) and heterotic group R (pollinator parental groups) (HGR1 and HGR2) based on general combining ability (GCA) and specific combining ability effects. Composite testers were found to be more effective for the heterotic grouping of pearl millet populations. New inbred lines were classified into HGB and HGR based on GCA and hybrid performance using opposite heterotic group testers and also using genetic similarity obtained from genotype-by-sequencing data.The new germplasm classified into heterotic groups will help enhance the genetic gain for the long-term success of pearl millet hybrid breeding programs
MILLETS in upland regions of Odisha (MURO) for crop diversification, climate resilience and enhanced Food and Nutritional Security
Get PDFIn Odisha, agricultural practices predominantly revolve around rice cultivation, particularly in rainfed ecosystems. However, the reliance on rice poses significant challenges, including susceptibility to water scarcity and moisture stress, leading to low yields and inadequate financial returns for farmers. Additionally, nutritional deficiencies, as highlighted by the National Family Health Survey (NFHS) 2015-16, further underscore the urgent need for intervention. Thirty-four percent of children suffer from malnutrition, emphasizing the critical importance of addressing food and nutritional security issues.
The "MILLETS in upland regions of Odisha (MURO)" project offers a solution by promoting the cultivation of millets as an alternative to rice. Millets, known for their resilience to adverse weather conditions and high nutritional value, provide a dual-purpose option by serving both as food and feed crops. This project aims to diversify crops, enhance climate resilience, and improve food and nutritional security in Odisha, thereby addressing pressing agricultural and socio-economic challenges
High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut
Get PDFBackground
Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits.
Results
Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation.
Conclusion
In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs
Ethylene regulates auxin-mediated root gravitropic machinery and controls root angle in cereal crops
No full textRoot angle is a critical factor in optimizing the acquisition of essential resources from different soil depths. The regulation of root angle relies on the auxin-mediated root gravitropism machinery. While the influence of ethylene on auxin levels is known, its specific role in governing root gravitropism and angle remains uncertain, particularly when Arabidopsis (Arabidopsis thaliana) core ethylene signaling mutants show no gravitropic defects. Our research, focusing on rice (Oryza sativa L.) and maize (Zea mays), clearly reveals the involvement of ethylene in root angle regulation in cereal crops through the modulation of auxin biosynthesis and the root gravitropism machinery. We elucidated the molecular components by which ethylene exerts its regulatory effect on auxin biosynthesis to control root gravitropism machinery. The ethylene-insensitive mutants ethylene insensitive2 (osein2) and ethylene insensitive like1 (oseil1), exhibited substantially shallower crown root angle compared to the wild type. Gravitropism assays revealed reduced root gravitropic response in these mutants. Hormone profiling analysis confirmed decreased auxin levels in the root tips of the osein2 mutant, and exogenous auxin (NAA) application rescued root gravitropism in both ethylene-insensitive mutants. Additionally, the auxin biosynthetic mutant mao hu zi10 (mhz10)/tryptophan aminotransferase2 (ostar2) showed impaired gravitropic response and shallow crown root angle phenotypes. Similarly, maize ethylene-insensitive mutants (zmein2) exhibited defective gravitropism and root angle phenotypes. In conclusion, our study highlights that ethylene controls the auxin-dependent root gravitropism machinery to regulate root angle in rice and maize, revealing a functional divergence in ethylene signaling between Arabidopsis and cereal crops. These findings contribute to a better understanding of root angle regulation and have implications for improving resource acquisition in agricultural systems
High-density bin-based genetic map reveals a 530-kb chromosome segment derived from wild peanut contributing to late leaf spot resistance
No full textLate leaf spot (LLS) is one of the major foliar diseases of peanut, causing serious yield loss and affecting the quality of kernel and forage. Some wild Arachis species possess higher resistance to LLS as compared with cultivated peanut; however, ploidy level differences restrict utilization of wild species. In this study, a synthetic amphidiploid (Ipadur) of wild peanuts with high LLS resistance was used to cross with Tifrunner to construct TI population. In total, 200 recombinant inbred lines were collected for whole-genome resequencing. A high-density bin-based genetic linkage map was constructed, which includes 4,809 bin markers with an average inter-bin distance of 0.43 cM. The recombination across cultivated and wild species was unevenly distributed, providing a novel recombination landscape for cultivated-wild Arachis species. Using phenotyping data collected across three environments, 28 QTLs for LLS disease resistance were identified, explaining 4.35–20.42% of phenotypic variation. The major QTL located on chromosome 14, qLLS14.1, could be consistently detected in 2021 Jiyang and 2022 Henan with 20.42% and 12.12% PVE, respectively. A favorable 530-kb chromosome segment derived from Ipadur was identified in the region of qLLS14.1, in which 23 disease resistance proteins were located and six of them showed significant sequence variations between Tifrunner and Ipadur. Allelic variation analysis indicating the 530-kb segment of wild species might contribute to the disease resistance of LLS. These associate genomic regions and candidate resistance genes are of great significance for peanut breeding programs for bringing durable resistance through pyramiding such multiple LLS resistance loci into peanut cultivars
Diversity among Bambara groundnut (Vigna subterranea L. Verdc) accessions using agro-morphological traits and diversity array technologies sequence low density markers in Malawi
Get PDFBambara groundnut (Vigna subterranea (L.) Verdc) is a neglected and underutilized crop that plays a big role in improving livelihoods of smallholder farmers in Sub-Saharan Africa. Despite its importance, there is limited availability of commercially improved cultivars to smallholder farmers in Malawi. This study characterized selected Bambara groundnuts accessions for agro-morphological traits for germplasm discrimination. It also identified genetic variation using Single Nucleotide Polymorphism (SNP) markers through Diversity Array Technologies Sequence Low Density (DArTseqLD) that could be used to produce improved seed for crop improvement. Forty Bambara groundnuts accessions were evaluated at the Crops and Soil Sciences Department’s farm of Lilongwe University of Agriculture and Natural Resources, Bunda College, Malawi. From the 40 accessions, 188 unique seed samples were selected for genotyping using DArTseqLD SNP markers. Data on agro-morphological traits were collected following the Bambara groundnut descriptor guidelines and multivariate analysis were performed. Principal Component Analysis revealed a total variation of 53%. The study generated 1048 DArTseqLD SNP markers. Analysis of molecular variance (AMOVA) identified 84% and 13% of genetic variation among and within the Bambara groundnut accessions respectively, whereas 3% genetic variation was observed among the total populations. Cluster analysis based on genotypic data grouped the 188 samples into 10 clusters. Based on phenotypic and genotypic data, it can be concluded that there is a significant degree of variation and genetic diversity in the accessions evaluated that can be used in crop improvement program as well as being directly used by farmers in seed production
Plastic film mulching with nitrogen application activates rhizosphere microbial nitrification and dissimilatory nitrate reduction in the Loess Plateau
No full textPlastic film mulching combined with nitrogen application is a prime chief strategy for enhancing maize yields in rain-fed agricultural areas. However, how the practice affects the productivity and functions of soil by altering nitrogen transformation mediated by rhizosphere microorganisms in the Loess Plateau, remains unclear. In this research, an 7-year field location experiment was conducted to ascertain the effects of plastic film mulching with nitrogen application (225 kg N ha−1) on the rhizosphere microbial nitrogen transformation in a rain-fed maize field on the Loess Plateau. Plastic film mulching with nitrogen application reduced the pH value and also increased the abundance of microorganisms (e.g., Nitrosospira, Halomonas) and genes (e.g., pmoB-amoB, hao, nirB, and nirD) during the vegetative stage. This promoted nitrification and dissimilatory nitrate reduction to ammonium, which increased the content of inorganic nitrogen in the rhizosphere. During the reproductive stages, plastic flim mulching reduced the relative abundance of aerobic bacteria (e.g., Skermanella, Sphingomonas), and the ratio of (nirK + nirS) / nosZ, which inhibited denitrification and dinitrogen oxide emission potential. Overall, our findings highlight the feedback mechanism of soil nitrogen transformation to plastic film mulching with nitrogen application in the Loess Plateau, providing valuable insights for manipulating specific microorganisms to regulate nitrogen transformation and promoting the sustainability of soil ecosystems
Multi-Scale analysis of the impacts of soil and water conservation practices and landscape on grain yield and return on investment in the sub-humid ethiopian highlands
Get PDFEthiopia's sub-humid highlands face a critical challenge in balancing agricultural productivity with land degradation. This study explores the effectiveness of soil and water conservation practices (SWCPs) in addressing this challenge. We investigated the interaction effects of types of SWCPs, landscape positions, and location on Teff (Eragrostis teff) and wheat (Triticum aestivum) yield. In addition, we assessed the economic viability of SWCPs using cost-benefit analysis with farmer-funded and cost-sharing scenarios. The results indicated that yield was significantly affected by the interactions between factors like SWCP type and landscape position. Soil bunds consistently increased crop yield across diverse locations and landscapes, indicating superior erosion control benefits. Lower landscape positions on foot slopes benefited most from SWCP implementation. Teff yield increased by 188 % and wheat yield by 181 % under soil bunds. The cost-benefit analysis confirmed the financial viability of SWCPs, particularly for Teff (NPV = 4499.35 USD, IRR = 50 %, and BCR = 1.51) and wheat (NPV = 544.35 USD, IRR = 16 %, and BCR = 1.06) grown on lower landscapes with farmer-funded investment scenarios. Positive return on investment was observed in both scenarios, with cost-sharing offering greater economic benefits for farmers. These findings highlight the importance of an integrated approach to SWC implementation for achieving multiple Sustainable Development Goals (SDGs) by enhancing food security, improving farmer incomes, and promoting sustainable and productive landscape management practices. Future research should explore the long-term sustainability of SWCPs, their adaptation across diverse agroecological zones and landscapes, the incorporation of various crops, the broader socioeconomic impacts, and the development of effective extension programs for wider adoption by farmers