International Crops Research Institute for the Semi-Arid Tropics
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The effects of foliar amino acid and Zn applications on agronomic traits and Zn biofortification in soybean (Glycine max L.)
No full textThe production and consumption of soybeans are widespread due to their nutritional and industrial value. Nutrient enrichment is vital for improving the nutritional quality of soybeans. This study aimed to evaluate the effect of foliar application of amino acids (AA) and zinc (Zn) on agronomic traits and the accumulation of grain Zn in soybeans. The experimental design comprised 16 treatment combinations involving four levels of amino acid application (0, 50, 100, and 150 ml 100 L-1) and Zn (0, 2, 4, and 6 mg L-1) following a randomized complete block design with three replications in field conditions. The results demonstrated that the application of foliar Zn and AA did not affect the yield, whereas that of AA50*Zn2 and AA150*Zn2 affected the number of pods and branches. The effects of AA application on N and the protein content in grains were determined to be significant. The application of AA100*Zn6 emerged as the most effective treatment for the enhancement of Zn biofortification in soybean grains. The combined foliar application of AA and Zn contributed to enhanced Zn accumulation in the grains
Sorghum Environment Characterization and G × M Modeling Toolbox
No full textCrop modeling plays a crucial role in modern agriculture, offering a strategic and scientific approach to crop improvement programs. By simulating and predicting the complex interactions between various factors influencing crop growth, including climate, soil, and genetic traits, crop models provide valuable insights. These insights enable researchers and breeders to optimize agricultural practices, predict crop performance under different conditions, and accelerate the development of improved varieties. Crop modeling enhances the precision of decision-making in areas such as planting schedules, resource management, and the selection of resilient genotypes. Furthermore, it contributes to the development of climate-resilient crops, helping agriculture adapt to changing environmental conditions. The efficiency, cost-effectiveness, and sustainability of crop improvement programs are significantly enhanced through the informed integration of crop modeling, ultimately contributing to global food security and agricultural sustainability
Association mapping identifies stable loci containing novel genes for developmental and reproductive traits in sorghum
No full textLandraces are ideal for identifying genes related to adaptation. The purpose of this study was to map and identify genes related to adaptation. We evaluated a mini core collection that broadly samples the global sorghum landrace gene pool for 11 traits in 4–12 environments. Association mapping with 6094 317 SNPs identified 70 loci for the 11 traits. The key findings include two panicle weight (PWt) and two grain yield (GY) loci overlapped, and two panicle length (PL) and two panicle width (PW) loci overlapped. Some loci for tiller number (TL), PL/PW, PWt, GY, and seed weight (SW) colocalized with previously mapped quantitative trait loci. We identified 33 candidate genes for TL, PL, PW, PWt, GY, SW, and MRC. The overlapping PWt and GY locus on chromosome 9 contained gibberellin receptor GID1 gene that regulates seed development. A TL locus on chromosome 1 that was consistently detected contained Sobic.001G152700 encoding a DUF1618 protein that was the sole horizontally transferred gene from sorghum to the parasitic Striga hermonthica, which was potentially related to environmental adaptation. These results are relevant for sorghum molecular breeding. Future studies are needed to functionally characterize the rich collection of novel candidate genes identified in this study.
Key message
We mapped 11 sorghum traits, identified 33 candidate genes, and found a grain yield gene (GID1) that regulates seed development and a grass-specific tillering gene (DUF1618) transferred to Striga hermonthica
UC-HSI: UAV-Based Crop Hyperspectral Imaging Datasets and Machine Learning Benchmark Results
No full textAccurate and timely information about crop types and their distribution is crucial for effective agricultural management, resource allocation, and policy-making. Remote sensing (RS) imaging has the potential to automate the identification and mapping of crops over large areas. The low spatial resolutions of satellite-based platforms and the limited spectral capability of RGB/multispectral cameras are the bottlenecks in efficient crop categorization. Unmanned aerial vehicle (UAV)-based hyperspectral imaging (HSI) technology has the potential to classify/map agricultural landscapes efficiently due to its extensive coverages, rich spectral information, and high spatial and temporal resolutions. However, very few crop hyperspectral (HS) datasets are publicly available, on which the research community relies on for developing and testing algorithms, which are created from either in situ spectral measurements or low-resolution satellite images. This letter presents UAV-borne Crop HyperSpectral Image (UC-HSI) datasets in the 385–1021-nm spectral range. The detailed steps for creating clean HSI datasets from UAV-based HS images are described. We also proposed a novel convolutional transformer fusion architecture to classify the crop HSI datasets efficiently and compared its performance with machine learning (ML) benchmarks; it obtained the best accuracy of 95.26% in categorizing ten crop varieties. The datasets and codes will be made publicly available at https://github.com/sankaraug/CrHyperS to benefit the RS community, allowing them to develop and test algorithms on UAV-based HSI data
Drought Adaptation in Pearl Millet (Pennisetum glaucum (L.) R. Br.): Physiological, Molecular and Genetic Approaches
No full textPearl millet, a cereal crop grown in arid and semiarid regions, faces significant constraints due to drought. As an essential source of food and fodder in water-limited environments, its production is crucial for ensuring food security in regions like Africa and the Indian subcontinent. However, drought stress can lead to substantial yield losses, making it necessary to develop pearl millet cultivars with enhanced adaptation to drought. To achieve this, understanding the drought adaptive mechanisms and their interactions with genotypes and the environment is essential. This chapter focuses on the progress made in improving drought adaptation in pearl millet through physiological, molecular, and genetic approaches. The research highlights the importance of environmental characterization and revised production zones for pearl millet cultivation in rain-fed systems. By using crop simulation modeling techniques, the study provides insights into the diverse agro-climatic conditions and production constraints across different target population environments (TPEs). The proposed zonation revision facilitates the development of targeted breeding strategies and optimization of production systems. Furthermore, the chapter discusses physiological traits related to drought adaptation, such as soil water conservation, canopy development, and water use efficiency. It also explores molecular approaches, including the role of aquaporin genes in regulating water transport and transpiration rate in pearl millet. In addition, this chapter also focuses on genetic approaches in pearl millet highlighting DNA markers and QTLs associated with drought adaptation traits, providing valuable targets for breeding programs
Transpiration efficiency variations in the pearl millet reference collection PMiGAP
Get PDFTranspiration efficiency (TE), the biomass produced per unit of water transpired, is a key trait for crop performance under limited water. As water becomes scarce, increasing TE would contribute to increase crop drought tolerance. This study is a first step to explore pearl millet genotypic variability for TE on a large and representative diversity panel. We analyzed TE on 537 pearl millet genotypes, including inbred lines, test-cross hybrids, and hybrids bred for different agroecological zones. Three lysimeter trials were conducted in 2012, 2013 and 2015, to assess TE both under well-watered and terminal-water stress conditions. We recorded grain yield to assess its relationship with TE. Up to two-fold variation for TE was observed over the accessions used. Mean TE varied between inbred and testcross hybrids, across years and was slightly higher under water stress. TE also differed among hybrids developed for three agroecological zones, being higher in hybrids bred for the wetter zone, underlining the importance of selecting germplasm according to the target area. Environmental conditions triggered large Genotype x Environment (GxE) interactions, although TE showed some high heritability. Transpiration efficiency was the second contributor to grain yield after harvest index, highlighting the importance of integrating it into pearl millet breeding programs. Future research on TE in pearl millet should focus (i) on investigating the causes of its plasticity i.e. the GxE interaction (ii) on studying its genetic basis and its association with other important physiological traits
Nurturing Sustainable Landscapes through Strengthening Partnerships in Agroecology Learning from agroecology fair held in the Mbire, Murehwa and Hwange districts of Zimbabwe
Get PDFFor many, attending a fair is synonymous with enjoyment: socializing with friends and family, exploring a variety of exhibits, collecting freebies, and enjoying local food. Yet, an often-overlooked aspect of fairs is their value as powerful learning platforms, especially for communities deeply rooted in agriculture.
Historically, the tradition of fairs stretches back centuries, with roots in Ancient Rome and medieval England. By the 1700s, agricultural fairs were formalized in Britain, where they evolved as spaces for farmers to showcase crops, livestock, and farming techniques. Today, agricultural fairs have become a global phenomenon tailored to local agricultural practices and communities, offering farmers opportunities to showcase their products, share knowledge, and build connections with other food system actors.
An agricultural fair is more than just an exhibition; it celebrates agricultural heritage and is an interactive platform for education and community engagement. These fairs include livestock, machinery, and farm produce displays alongside exhibitions on sustainable agricultural practices and innovations. Attendees gain hands-on exposure to new agricultural tools, techniques, and technologies while engaging in conversations and demonstrations covering various topics from crop management to sustainable farming practices and the adoption of mechanization.
In addition, agricultural fairs remain essential spaces for knowledge exchange, innovation, and promoting agriculture's role in economic and social development. They bring together farmers, agribusiness professionals, and organizations, fostering partnerships and encouraging collaboration within the agricultural sector. The Agroecology fairs held in Murehwa, Mbire and Hwange districts builds on this legacy, providing a vital platform for learning, sharing sustainable farming practices, and emphasizing the role of agroecology in creating resilient and sustainable landscapes through stronger partnerships. This report captures the essence and impact of the Agroecology Fair, demonstrating its role as a catalyst for knowledge-sharing and sustainable agricultural development, supporting ecologically responsible agriculture and strengthening community connections
Research agenda for holistically assessing agricultural strategies for human micronutrient deficiencies in east and southern Africa
Get PDFContext
Human micronutrient deficiencies in sub-Saharan Africa are connected through complex pathways to soils and how soils are managed. Interventions aiming directly at nutrient consumption, such as supplements and food fortification, have direct impacts but are often limited in their reach and require continuous support. In contrast, less direct changes, such as agricultural diversification and agronomic biofortification, are complicated by a wide array of factors that can limit progress toward nutritional outcomes. However, changes in agriculture and dietary patterns, if successfully linked to deficiencies, provide a more systemic transformation with the potential to achieve wide-reaching and self-perpetuating attainment of nutritional goals.
Objective
The purpose of this paper is to advance theoretical frameworks and research methods for holistic analysis of agriculture-based interventions for micronutrient deficiencies.
Methods
We synthesize lessons from the literature and from the Africa RISING project in Malawi and Tanzania about the connections between soil nutrients and human micronutrient deficiencies from the perspective of the five domains of sustainable intensification (productivity, economic, environmental, human condition and social).
Results and conclusions
We present a menu of indicators for future research on the soil-plant-food-nutrition pathway related to micronutrient deficiency and smallholder farming that need to be considered to effectively assess how agricultural interventions may or may not result in the desired nutritional outcomes. Ultimately, addressing micronutrient deficiencies through agricultural interventions requires a holistic approach that considers all five domains. Research on soil-nutrition linkages should consider the feedback loops across the five domains of sustainable intensification.
Significance
Interdisciplinary and participatory research to effectively link soils to human health supports sustainable development
Nurturing sustainable landscapes through strengthening partnerships in agroecology: Learning from agroecology fair held in the Mbire, Murehwa and Hwange districts of Zimbabwe.
No full textFor many, attending a fair is synonymous with enjoyment: socializing with friends and family, exploring a variety of exhibits, collecting freebies, and enjoying local food. Yet, an often-overlooked aspect of fairs is their value as powerful learning platforms, especially for communities deeply rooted in agriculture.
Historically, the tradition of fairs stretches back centuries, with roots in Ancient Rome and medieval England. By the 1700s, agricultural fairs were formalized in Britain, where they evolved as spaces for farmers to showcase crops, livestock, and farming techniques. Today, agricultural fairs have become a global phenomenon tailored to local agricultural practices and communities, offering farmers opportunities to showcase their products, share knowledge, and build connections with other food system actors.
An agricultural fair is more than just an exhibition; it celebrates agricultural heritage and is an interactive platform for education and community engagement. These fairs include livestock, machinery, and farm produce displays alongside exhibitions on sustainable agricultural practices and innovations. Attendees gain hands-on exposure to new agricultural tools, techniques, and technologies while engaging in conversations and demonstrations covering various topics from crop management to sustainable farming practices and the adoption of mechanization.
In addition, agricultural fairs remain essential spaces for knowledge exchange, innovation, and promoting agriculture's role in economic and social development. They bring together farmers, agribusiness professionals, and organizations, fostering partnerships and encouraging collaboration within the agricultural sector. The Agroecology fairs held in Murehwa, Mbire and Hwange districts builds on this legacy, providing a vital platform for learning, sharing sustainable farming practices, and emphasizing the role of agroecology in creating resilient and sustainable landscapes through stronger partnerships. This report captures the essence and impact of the Agroecology Fair, demonstrating its role as a catalyst for knowledge-sharing and sustainable agricultural development, supporting ecologically responsible agriculture and strengthening community connections
Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
Get PDFAgricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further