International Crops Research Institute for the Semi-Arid Tropics
ICRISAT Open Access RepositoryNot a member yet
12134 research outputs found
Sort by
Spatial Products for Crop Monitoring and Sustainable Agriculture
Get PDFThe spatial cropland products are of great importance in water and food security assessments, especially in India, which is home to nearly 1.4 billion people and 160 million hectares of net cropland area. In India, 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., our study was aimed at producing three distinct spatial products at 30m and 250m resolution that would be useful and needed to address food and water security challenges. The first of these, Product 1, was to assess irrigated versus rainfed croplands in India using Landsat 30 m data in GEE platform. The second, Product 2, was to map major crop types using MODIS 250 m data. The third, Product 3, to map cropping intensity (single, double and triple cropping) using MODIS 250 m data. For the kharif season (the main cropping season in India, Jun-Oct), 9 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), 5 major crops (3 irrigated crops: rice, wheat, maize; and 2 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 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 highlights production of multiple cropland products to support food security studies using multiple satellite sensor big-data, and RF machine learning algorithm that were coded, processed, and computed
How process-based modeling can help plant breeding deal with G x E x M interactions
Get PDFGenotype-by-Environment-by-Management (GxExM) interactions represent many unknowns for crop improvement programs, which hampers the development of improved varieties, especially for highly variable environments like those limited by rainfall. While breeding programs have traditionally used statistical tools to deal with these interactions, process-based crop modeling has recently become an alternative and powerful approach. Overall, while statistical methods remain the most optimal solution to deal with GxExM interactions when many production datasets across time and space are available from multi-environment trials (MET), in silico methods like crop modeling can be used if such data is lacking, or if MET data don’t cover the entire target region. Yet, despite several reviews on the potential uses of process-based modeling tools to aid such issues, their practical use in helping breeding programs is still in its infancy. After exposing the pros and cons of process-based modeling, this paper presents the step-by-step process that would allow breeding programs to harness this tool to help guide their breeding decisions. We also argue that the issue of GxExM interactions should be tackled in a co-construction process, involving breeders, agronomists, extensionists, and modelers from the beginning, and this would bring crop models one step closer to being used to help make plant breeding decisions
Optimum Plant Density for Increased Groundnut Pod Yield and Economic Benefits in the Semi-Arid Tropics of West Africa
Get PDFGroundnut is a very important crop in the West and Central Africa (WCA) region, accounting for almost 70% of Africa’s groundnut production in 2019. Despite its economic importance, the crop’s yield is still low. For a high yield and profitable economic returns, optimal plant density is a fundamental crop management practice. Plant density experiments were conducted at the ICRISAT-Mali research station between 2016 and 2021 over the main rainy and dry seasons to determine the optimum density for maximum groundnut yield and economic benefits. The treatments contained row spacing of 20 cm, 30 cm, 40 cm, 50 cm, 60 cm, 70 cm, 80 cm, 90 cm, and 100 cm, with intra-row spacing of 10 cm, 15 cm, and 20 cm. Results showed that when plant density was increased, dry pod yield, production value, and net economic benefit per hectare increased in a no moisture stress scenario. During the rainy season, the 40 cm × 10 cm spacing gave the highest dry pod yield (1693 kg), production value (403.5) per hectare. The highest dry pod yield (3703 kg), production value (1510.2) per hectare were obtained from 30 cm × 10 cm spacing during the dry season. The number of pods per plant and 100 SW increased with lower plant densities. Therefore, it is recommended to increase plant density to at least 222,000 plants per hectare in the Sudan Savannah agroecology of WCA
Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery
Get PDFWater hyacinth (Pontederia crassipes, also known as Eichhornia crassipes) is a highly invasive aquatic macrophyte species, indigenous to Amazonia, Brazil and tropical South America. It was introduced to India in 1896 and has now become an environmental and social challenge throughout the country in community ponds, freshwater lakes, irrigation channels, rivers and most other surface waterbodies. Considering its large speed of propagation on the water surface under conducive conditions and the adverse impact the infesting weed has, constant monitoring is needed to aid civic bodies, governments and policy makers involved in remedial measures. The synoptic coverage provided by satellite imaging and other remote sensing practices make it convenient to find a solution using this type of data. While there is an established background for the practice of remote sensing in the detection of aquatic plants, the use of Synthetic Aperture Radar (SAR) has yet to be fully exploited in the detection of water hyacinth. This research focusses on detecting water hyacinth within Vembanad Lake, Kuttanad, India. Here, results show that the monitoring of water hyacinth has proven to be possible using Sentinel-1 SAR data. A quantitative analysis of detection performance is presented using traditional and state-of-the-art change detectors. Analysis of these more powerful detectors showed true positive detection ratings of ~95% with 0.1% false alarm, showing significantly greater positive detection ratings when compared to the more traditional detectors. We are therefore confident that water hyacinth can be monitored using SAR data provided the extent of the infestation is significantly larger than the resolution cell (bigger than a quarter of a hectare)
Dual-Purpose Sorghum: A Targeted Sustainable Crop-Livestock Intervention for the Smallholder Subsistence Farming Communities of Adilabad, India
Get PDFSorghum plays an important role in the mixed crop–livestock system of tribal farming
communities in Adilabad District, a high climate risk-prone region in India. Currently, the
local seed system is limited to landraces and hybrids that are primarily used for domestic
grain and fodder purposes. This study aimed to understand the farmers’ needs and
context, and use this knowledge to deliver relevant, adoptable climate-smart sorghum
crop technologies through farmer-participatory approaches (FPAs). We conducted an
ex-ante survey with 103 farmer households to understand their preferences and
constraints concerning sorghum, their staple food-crop. Farmers expressed taste as the
most important characteristic, followed by stover yield, grain yield, drought adaptation,
and pest resistance. They identified fodder deficit, loss of seed purity in landraces,
and lack of diverse sorghum seed options as critical constraints. Therefore, we chose
dual-purpose, open-pollinated sorghum varieties suitable for postrainy/rabi cultivation
as the study site’s entry point. Accordingly, sixteen popular rabi sorghum varieties were
tested at ICRISAT station (2017–18 and 2018–19) for agronomic performance in field
conditions under a range of treatments (irrigation and fertilization). The standing crop was
also scored by farmer representatives. Additionally, the detailed lysifield study elucidated
the plant functions underlying the crop agronomic performance under water stress (plant
water use and stay-green score) and an important trait of farmer’s interest (relation
between stay-green score and in-vitro stover digestibility and relation between grain fat
and protein content) The selected varieties– Phule Chitra, CSV22, M35-1 and preferred
landrace (Sevata jonna)–were further tested with 21 farmers at Adilabad (2018–20).
Participating farmers from both the trials and focus group discussions voiced their
preference and willingness to adopt Phule Chitra and CSV22. This article summarizes
how system-relevant crop options were selected for subsistence farmers of Adilabad and deployed using participatory approaches. While varieties are developed for wider
adoption, farmers adopt only those suitable for their farm, household, and accessible
market. Therefore, we strongly advocate FPA for developing and delivering farmer
relevant crop technologies as a vehicle to systematically break crop adoption barriers
and create a positive impact on household diets, well-being, and livelihoods, especially
for smallholder subsistence farmers
Physicochemical and sensory attributes of gluten-free sourdough breads produced from underutilised African cereal flours and flour blends
Get PDFTo seek potential alternative(s) for imported wheat in the African baking industry, the physicochemical parameters and sensory attributes of sourdough breads developed from locally sourced underutilised cereals and their blends were assessed. Processed sorghum (Sorghum bicolour), finger millet (Eleusine coracana) and pearl millet (Pennisetum glaucum) and their composites (50:50) were used to produce sourdough. Sourdough and flour-sourdough blends (30% sourdough) were used in making gluten-free breads. The
protein content of the breads ranged from 16.29% to 39.26%, whereas the fat, crude fibre, ash and carbohydrate contents fell between 14.02–18.80%, 0.55–1.22%, 1.90–3.32% and 42.16–65.61%, respectively. The calculated energy value of the gluten-free breads (405.99–446.39 Kcal per 100 g) exceeded that of wheat bread (396.43 Kcal per 100 g), while the specific loaf volume varied from 1.46 to 1.80 cm3 g-1.
Although the produced gluten-free breads have improved nutritional content compared to conventional wheat bread, they were at best moderately liked. This is perhaps due to the non-cohesive nature of the crumbs and psychological preference for known products. Further research targeted at improving the organoleptic properties of these sourdough breads is recommended
Genomic insights into the genetic signatures of selection and seed trait loci in cultivated peanut
Get PDFIntroduction: Cultivated peanut (Arachis hypogaea L.) is an important oil crop for human nutrition and is cultivated in >100 countries. However, the present knowledge of its genomic diversity, evolution, and loci related to the seed traits is limited.
Objectives: Our study intended to (1) uncover the population structure and the demographic history of peanuts, (2) identify signatures of selection that occurred during peanut improvement breeding, and (3) detect and verify the functions of candidate genes associated with seed traits.
Methods: We explored the population relationship and the evolution of peanuts using a largescale single nucleotide polymorphism dataset generated from the genome-wide resequencing of 203 cultivated peanuts. Genetic diversity and genomic scan analyses were applied to identify selective loci for genomicselection breeding. Genome-wide association studies, transgenic experiments, and RNA-seq were employed to identify the candidate genes associated with seed traits
Grain Nutrients Variability in Pigeonpea Genebank Collection and Its Potential for Promoting Nutritional Security in Dryland Ecologies
Get PDFPigeonpea, a climate-resilient legume, is nutritionally rich and of great value in Asia, Africa, and Caribbean regions to alleviate malnutrition. Assessing the grain nutrient variability in genebank collections can identify potential sources for biofortification. This study aimed to assess the genetic variability for grain nutrients in a set of 600 pigeonpea germplasms conserved at the RS Paroda Genebank, ICRISAT, India. The field trials conducted during the 2019 and 2020 rainy seasons in augmented design with four checks revealed significant differences among genotypes for all the agronomic traits and grain nutrients studied. The germplasm had a wider variation for agronomic traits like days to 50% flowering (67–166 days), days to maturity (112–213 days), 100-seed weight (1.69–22.17 g), and grain yield per plant (16.54–57.93 g). A good variability was observed for grain nutrients, namely, protein (23.35–29.50%), P (0.36–0.50%), K (1.43–1.63%), Ca (1,042.36–2,099.76 mg/kg), Mg (1,311.01–1,865.65 mg/kg), Fe (29.23–40.98 mg/kg), Zn (24.14–35.68 mg/kg), Mn (8.56–14.01 mg/kg), and Cu (7.72–14.20 mg/kg). The germplasm from the Asian region varied widely for grain nutrients, and the ones from African region had high nutrient density. The significant genotype × environment interaction for most of the grain nutrients (except for P, K, and Ca) indicated the sensitivity of nutrient accumulation to the environment. Days to 50% flowering and days to maturity had significant negative correlation with most of the grain nutrients, while grain yield per plant had significant positive correlation with protein and magnesium, which can benefit simultaneous improvement of agronomic traits with grain nutrients. Clustering of germplasms based on Ward.D2 clustering algorithm revealed the co-clustering of germplasm from different regions. The identified top 10 nutrient-specific and 15 multi-nutrient dense landraces can serve as promising sources for the development of biofortified lines in a superior agronomic background with a broad genetic base to fit the drylands. Furthermore, the large phenotypic data generated in this study can serve as a raw material for conducting SNP/haplotype-based GWAS to identify genetic variants that can accelerate genetic gains in grain nutrient improvement
Brewery industry-led seed sector development for sorghum in Tanzania
Get PDFThe use of sorghum improved variety seeds has been low among sorghum farmers in Tanzania. Due to this, stakeholders such as brewing companies have launched various initiatives to expand the use of improved sorghum seeds. In general, this study was undertaken to assess the contribution of brewing industry to the sorghum value chain in Tanzania. Specifically, this study aims to determine the extent of use of sorghum in brewing (by quantifying the amount of sorghum grain sold to brewing companies and grain off-takers), identifying stakeholders in the value chain, and the impact of the brewing industry on use of improved seeds by smallholder farmers. The study was conducted in 11 districts in 6 regions of Tanzania covering sorghum farmers, grain off-takers, brewing companies, extension officers, and seed producers. Purposive and simple random sampling was used to select respondents: 591 individual farmers, 160 farmers from 16 focus groups, 15grain off-takers, 14 extension officers, 4 Quality Declared Seed (QDS) producers, and 2 brewing companies. Data was then analyzed using descriptive analysis statistics, Probit Regression, and cost-benefit analysis
Loss-of-function of triacylglycerol lipases are associated with low flour rancidity in pearl millet [Pennisetum glaucum (L.) R. Br.]
Get PDFPearl millet is an important cereal crop of semi-arid regions since it is
highly nutritious and climate resilient. However, pearl millet is underutilized
commercially due to the rapid onset of hydrolytic rancidity of seed lipids
post-milling. We investigated the underlying biochemical and molecular
mechanisms of rancidity development in the flour from contrasting inbred
lines under accelerated aging conditions. The breakdown of storage lipids
(triacylglycerols; TAG) was accompanied by free fatty acid accumulation over
the time course for all lines. The high rancidity lines had the highest amount
of FFA by day 21, suggesting that TAG lipases may be the cause of rancidity.
Additionally, the high rancidity lines manifested substantial amounts of volatile
aldehyde compounds, which are characteristic products of lipid oxidation.
Lipases with expression in seed post-milling were sequenced from low and
high rancidity lines. Polymorphisms were identified in two TAG lipase genes
(PgTAGLip1 and PgTAGLip2) from the low rancidity line. Expression in a yeast
model system confirmed these mutants were non-functional. We provide
a direct mechanism to alleviate rancidity in pearl millet flour by identifying
mutations in key TAG lipase genes that are associated with low rancidity. These
genetic variations can be exploited through molecular breeding or precision
genome technologies to develop elite pearl millet cultivars with improved
flour shelf life