International Crops Research Institute for the Semi-Arid Tropics
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Genome-wide association study as a powerful tool for dissecting competitive traits in legumes
Get PDFLegumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding
Crop Yield Assessment Using Field-Based Data and Crop Models at the Village Level: A Case Study on a Homogeneous Rice Area in Telangana, India
Get PDFCrop yield estimation has gained importance due to its vital significance for policymakers and decision-makers in enacting schemes, ensuring food security, and assessing crop insurance losses due to biotic and abiotic stress. This research focused on rice yield estimation at the field level in the Karimnagar district of Telangana during 2021 and 2022 by employing the leaf area index (LAI) as the primary criterion for integrating remote sensing technology and crop simulation models. Using Sentinel-2 satellite data, the rice crop was mapped with the help of ground data and machine learning algorithms, attaining an accuracy of 93.04%. Crop management data for the DSSAT tool were collected during the field visits; the model results revealed a 0.80 correlation between observed and predicted yields. Due to its strong correlation with LAI (0.82), the normalized difference vegetation index (NDVI) was selected as the critical element for integration with the model. A spatial LAI map was generated using the linear equation developed between the NDVI and LAI. The relationship between LAI and yield was used to create a spatial yield map. The study’s findings show that assimilating remote sensing data with crop models enhances the precision of rice yield prediction for insurance companies and policy- and decision-makers
Determinants of dietary diversity and drivers of food choice among low-income consumers in urban Kenya, Malawi and Zimbabwe
Get PDFIntroduction
Rapid urbanisation affects lifestyle and eating habits, predominantly causing a dietary shift that adds challenges to meet dietary recommendations within a complex food system. This research investigated dietary diversity and food choice drivers among low-income consumers in three urban settlements (Nairobi, Kenya; Bulawayo, Zimbabwe and Lilongwe, Malawi, representing rapid, moderate and slow urban growth patterns, respectively) as a first step towards improving diets across cultures and geographies.
Methods
Mixed methods data collection was employed for this study. Qualitative methods such as rapid foodscape appraisal workshops and food stories in selected low-income settlements in Nairobi, Bulawayo and Lilongwe were utilised to collect information on the food environments (food balances, infrastructure, safety, policies and institutions). Quantitative data such as socio-demographic characteristics and dietary diversity were collected via structured questionnaires using Cognitive Edge's SenseMaker® (n = 890, 450 and 440 for Nairobi, Bulawayo and Lilongwe, respectively). The dietary intake of respondents was assessed using a 24-h recall, which was then converted to the food group diversity score (FGDS).
Results
Different levels of compounded stress affected dietary diversity and quality, including high food prices, concerns about sanitation and hygiene and the role of food standards regulation bodies. The mean FGDS across all locations was lower than the recommended cut-off of 5 (4.5, 2.8 and 2.6 across Nairobi, Zimbabwe and Lilongwe, respectively). Additionally, in Nairobi, there were gender differences in diet diversity, with men having a higher dietary diversity score than women (4.6% vs. 4.3%; p = 0.004). The majority of respondents in Lilongwe (65%) reported price as the most important driver of food choice, compared to 38% in Nairobi and 42% in Bulawayo.
Discussion/Conclusions
Our observation of poor-quality diets provides further evidence of the need for food policies that are cognisant of the nutrition and health of the growing population of the urban poor. Such policies would focus on lowering the costs of nutritious foods as well as ensuring food safety within the complex food system observed in the urban low-income environment.
Key points
An investigation conducted in contrasting food environments in three urban low-income settlements in Lilongwe, Bulawayo and Nairobi suggests low consumption of nutrient-dense foods, such as fruits and animal-source foods.
Several drivers of dietary diversity and food choice, as well as perceptions, were identified. Price and convenience were identified as key drivers of food choice, with gender differences reported in dietary diversity.
Policies and programmes need to consider steering diets towards higher consumption of nutrient-dense foods while taking into account price, convenience and environmental sustainability
Improving agronomic effectiveness of elemental sulfur to increase productivity in sulfur-deficient soils
Get PDFElemental sulfur (ES), a byproduct of oil and gas processing, could be an alternate sulfur (S) fertilizer source for crop production if its bioavailability is improved. Increasing the specific surface of ES by reducing its particle size can accelerate ES oxidation to enhance its bioavailability. In field trials at six locations across three countries: two each in the United States, Ghana, and Mali, we determined the agronomic effectiveness of micronized ES (MES). Specific objectives were to quantify (i) corn (Zea mays L.) productivity, (ii) S recovery, and (iii) residual soil S concentration; following MES application, compared to ammonium sulfate (AS), a commercially available sulfate fertilizer, at four application rates—(i) locally recommended sulfur application rate (SR), (ii) 50%_SR, (iii) 75%_SR, and (iv) 125%_SR—and a control where no S was applied. Averaged across all sites and in the three growing seasons, AS at 50%_SR increased corn yield by ≤8% relative to control. Increasing to 75%_SR, SR, and 125%_SR resulted in 12%, 26%, and 28% yield increases, respectively. Applying MES at 50%_SR increased yield by ≤6%, and at 75%_SR, yield increased by ≤26%. Increasing the S application rate to SR and 125%_SR resulted in marginal yield increases. The combined data suggest that MES can be applied at a reduced rate of 75_SR to achieve similar yields as AS applied at SR. We conclude that MES could be an efficient S fertilizer alternative. However, economic analysis is needed to determine the potential profitability of using MES fertilizer products for crop production
Advances and opportunities in unraveling cold-tolerance mechanisms in the world’s primary staple food crops
Get PDFTemperatures below or above optimal growth conditions are among the major stressors affecting productivity, end-use quality, and distribution of key staple crops including rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays L.). Among temperature stresses, cold stress induces cellular changes that cause oxidative stress and slowdown metabolism, limit growth, and ultimately reduce crop productivity. Perception of cold stress by plant cells leads to the activation of cold-responsive transcription factors and downstream genes, which ultimately impart cold tolerance. The response triggered in crops to cold stress includes gene expression/suppression, the accumulation of sugars upon chilling, and signaling molecules, among others. Much of the information on the effects of cold stress on perception, signal transduction, gene expression, and plant metabolism are available in the model plant Arabidopsis but somewhat lacking in major crops. Hence, a complete understanding of the molecular mechanisms by which staple crops respond to cold stress remain largely unknown. Here, we make an effort to elaborate on the molecular mechanisms employed in response to low-temperature stress. We summarize the effects of cold stress on the growth and development of these crops, the mechanism of cold perception, and the role of various sensors and transducers in cold signaling. We discuss the progress in cold tolerance research at the genome, transcriptome, proteome, and metabolome levels and highlight how these findings provide opportunities for designing cold-tolerant crops for the future
Towards sustainable watershed-based landscape restoration in degraded drylands: Perceived benefits and innovative pathways learnt from project-based interventions in Ethiopia
Get PDFLand degradation is one of the contemporary environmental challenges affecting regions inhabited by over one-third of the global population. In response to land degradation, restoration of degraded landscapes through area closure has been implemented through government and bilateral organizations for the last three decades in Ethiopia. Objectives of this study were to: i) explore the effects of landscape restoration on vegetation cover; ii) identify the perceived benefits to local communities; and 3) synthesize the lessons learnt on communities’ willingness to sustain the restored landscapes. The study was conducted in project-supported restoration areas including the Dimitu and Kelisa watersheds representing the central rift valley dry lands and the Gola Gagura watershed representing the eastern dry land areas around Dire Dawa. The temporal changes in land use and land cover due to area closure integrated with physical and biological soil and water conservation measures were detected using GIS/Remote sensing techniques. Moreover, eighty-eight rural households were interviewed. The results of the study revealed that landscape restoration activities such as area closure integrated with physical soil and water conservation, and planting of trees and shrubs contributed to the significant changes in land covers of the watersheds in 3–5 years. Hence, barren lands were reduced by 35–100% while there were significant increases in forest lands (15%), woody grasslands (247–785%), and bushlands (78–140%). More than 90% of the respondents in the Dimitu and Gola Gagura watersheds verified that the landscape restoration activities improved vegetation cover and ecosystem services, reduced erosion, and increased incomes. A great majority of farm households (63–100%) expressed their willingness to contribute to different forms of landscape restoration interventions. Encroachment of livestock to closed area, shortage of finance, and the growing number of wild animals in closed area were the perceived challenges. Proper planning and implementation of integrated interventions, creating local watershed user associations, ensuring appropriate benefit-sharing and implementing innovative pathways to reconcile the tradeoffs could be considered to scale up interventions and address potential conflicts of interest
Do diverse wheat genotypes unleash their biochemical arsenal differentially to conquer cold stress? A comprehensive study in the Western Himalayas
No full textWheat is one of the most important cereal crops in the world. Cold stress is a major constraint in production of wheat grown in cold climate regions. In this study, we conducted a comprehensive assessment of cold stress tolerance in wheat genotypes through field screening, cell membrane stability through electrolyte leakage assay and biochemical profiling. A core set comprising 4560 genotypes was evaluated for two years (2021–2022), revealing substantial genetic variation for cold stress tolerance. Most genotypes exhibited moderate tolerance, while a smaller proportion showed susceptibility to cold stress. Based on the cold screening data in the field, a mini-core set of 350 genotypes was selected for membrane stability analysis using electrical conductivity assays. Significant differences were observed in membrane stability among the genotypes, indicating the presence of genetic variation for this trait. Furthermore, a mini-core set was narrowed down to 50 diverse candidate genotypes that were subsequently profiled for various biochemicals, including reactive oxygen species (ROS) like lipid peroxidation (MDA) and hydrogen peroxide (H202), osmoprotectant (proline) and enzymatic antioxidants including ascorbate peroxidase (APX), superoxide dismutase (SOD), guaiacol peroxidase (GPX), and catalase (CAT). Correlation analysis of the biochemicals revealed negative associations between antioxidants and reactive oxygen species (ROS), highlighting their role in mitigating oxidative damage under cold stress. This study enhances our understanding of the physiological and biochemical mechanisms underlying cold stress tolerance in wheat. The identified genotypes with superior cold stress tolerance can serve as valuable genetic resources for wheat breeding
Empowering local partners for inclusive and sustainable agricultural development — experiences from the Tropical Legumes Project in Africa
Get PDFThe importance of strong local partnerships and alliances
for the sustainability and long-term success of agricultural
development efforts cannot be overemphasized. This is supported by its inclusion as a standalone goal (goal
17) in the Sustainable Development Goals (SDGs), but also by
increasing calls to make local partnerships and alliances integral components of development projects and programmes.
Strong local partnerships are critical not only for identifying development needs, setting priorities, and driving the implementation of validated development interventions but also for scaling and sustaining impacts of such interventions
Documentation of multi‑pathotype durable resistance in exotic wheat genotypes to deadly stripe and leaf rust diseases
Get PDFLeaf and yellow rusts are considered as one of the most serious biotic constraints of wheat inflicting massive economic losses globally. Host resistance is the only efficient, economical, ecofriendly way of controlling the rust diseases. Characterization of diverse wheat materials is always of a paramount importance for identifying potential varietal material to effectively control rusts and insignificant yield losses. With this background, the present experiments were designed and carried out at Wheat Rusts Multiplication and Phenotyping Facility, Wheat Pathology Experiment Farm and National Phytotron Facility
of ICAR-IARI, New Delhi, and ICAR-IIWBR, Regional Station, Flowerdale, Shimla, for two consecutive years 2018–2019
and 2019–2020. Multi-environment phenotyping and characterization of stripe and leaf rust resistance were performed at both seedling stage in temperature-controlled growth chamber/greenhouse and adult plant stage in field conditions. By applying the gene-matching technique using multi-pathotypes data, five Yr (YrA, Yr2, Yr9, Yr18 and Yr27) and eight Lr (Lr1, Lr3, Lr10, Lr13, Lr19, Lr23, Lr26 and Lr34) genes in 98 exotic wheat genotypes (PG-Parent genetic pool, GS-Genomic selection genotype of CIMMYT-BISA, CIMCOG-CIMMYT Mexico core germplasm panel) were characterized singly or combinations with other vital genes. Adult plant slow rusting resistance was assessed through host response and different epidemiological parameters. All these promising rust-resistant genotypes at adult plant stage were susceptible at seedling stage to one or more pathotype(s), which indicated the presence of non-race-specific resistance gene(s). The lines identified could play pivotal role in the hybridization programs to enhance the resistance
High-Throughput Canopy and Belowground Phenotyping of a Set of Peanut CSSLs Detects Lines with Increased Pod Weight and Foliar Disease Tolerance
Get PDFWe deployed field-based high-throughput phenotyping (HTP) techniques to acquire trait data for a subset of a peanut chromosome segment substitution line (CSSL) population. Sensors mounted on an unmanned aerial vehicle (UAV) were used to derive various vegetative indices as well as canopy temperatures. A combination of aerial imaging and manual scoring showed that CSSL 100, CSSL 84, CSSL 111, and CSSL 15 had remarkably low tomato spotted wilt virus (TSWV) incidence, a devastating disease in South Georgia, USA. The four lines also performed well under leaf spot pressure. The vegetative indices showed strong correlations of up to 0.94 with visual disease scores, indicating that aerial phenotyping is a reliable way of selecting under disease pressure. Since the yield components of peanut are below the soil surface, we deployed ground penetrating radar (GPR) technology to detect pods non-destructively. Moderate correlations of up to 0.5 between pod weight and data acquired from GPR signals were observed. Both the manually acquired pod data and GPR variables highlighted the three lines, CSSL 84, CSSL 100, and CSSL 111, as the best-performing lines, with pod weights comparable to the cultivated check Tifguard. Through the combined application of manual and HTP techniques, this study reinforces the premise that chromosome segments from peanut wild relatives may be a potential source of valuable agronomic trait