International Crops Research Institute for Semi Arid Tropics
Recent publications
Agriculture is an important component of the ecosystem, and every human being is directly or indirectly associated with it. The use of tools and technology in agriculture has improved over time and has also contributed to increasing food production. However, the bulge in a global population at a frightening rate and the yield plateau in most of the crops has added more concern to the subject. Nanomaterials might play a remarkable role in breaking the yield plateau and have proved to be significant in enhancing the shelf life of processed foods. Although the history of nanotechnological interventions can be traced back to the previous few decades, the employment of nanomaterials is still restricted in agricultural systems. The research in the field of agricultural nanotechnology is growing at a very faster pace, but there still exists a significant difference in the research and its practical applications. A plethora of reports are available that claim the several beneficial effects of introducing nanomaterials in agroecosystems; however, several few reports have also warned about their postapplication effects in the soil, human, and environment. This provokes a dire need for evaluation of interactions existing between nanomaterials concerning soil, plants, soil microflora, and the environment before their field applications. The present chapter, therefore, highlights the fate, advantages, and issues related to nanomaterials and their interaction with the components of agroecosystems.
Cropland 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.
Being one of the most important staple dietary constituents globally, genetic enhancement of cultivated rice for yield, agronomically important traits is of substantial importance. Even though the climatic factors and crop manage- ment practices impact complex traits like yield immensely, the contribution of variation by underlying genetic factors surpasses them all. Previous studies have highlighted the importance of utilizing exotic germplasm, landraces in enhancing the diversity of gene pool, leading to better selections and thus superior cultivars. Thus, to fully exploit the potential of progenitor of Asian cultivated rice for productivity related traits, genome wide association study (GWAS) for seven agronomically important traits was conducted on a panel of 346 O. rufipogon accessions using a set of 15,083 high-quality single nucleotide polymorphic markers. The phenotypic data analysis indicated large continuous variation for all the traits under study, with a significant negative correlation observed between grain parameters and agronomic parameters like plant height, culm thickness. The presence of 74.28% admixtures in the panel as revealed by investigating population structure indicated the panel to be very poorly genetically differentiated, with rapid LD decay. The genome-wide association analyses revealed a total of 47 strong MTAs with 19 SNPs located in/close to previously reported QTL/genic regions providing a positive analytic proof for our studies. The allelic differences of significant MTAs were found to be statistically significant at 34 genomic regions. A total of 51 O. rufipogon accessions harboured combination of superior alleles and thus serve as potential candidates for accelerating rice breeding pro- grams. The present study identified 27 novel SNPs to be significantly associated with different traits. Allelic differences between cultivated and wild rice at significant MTAs determined superior alleles to be absent at 12 positions imply- ing substantial scope of improvement by their targeted introgression into cultivars. Introgression of novel significant genomic regions into breeder’s pool would broaden the genetic base of cultivated rice, thus making the crop more resilient.
Production of cereals (maize, sorghum, millet) in southern Mali is challenged by several hazards that affect yield and yield variability. The research aims to inform decision making towards effective risk management by quantifying cereal yield losses at field level due to production hazards under different management strategies. Five hazards relevant for farmers were analysed: late onset of rains, insufficient total rainfall, dry spells, low fertiliser quality and sudden lack of labour. The frequency and impact on yield of these hazards were assessed by combining a long term weather database (1965–2019) with outputs of the DSSAT crop model (baseline and optimised variety, fertiliser rates and sowing dates), and visualised in a risk matrix. The prevalence of the weather hazards was common, with all of them occurring at least once every five years. Frequency of non-weather hazards were perceived to occur once every five years (labour hazards) and once every ten years (fertiliser hazards). Under baseline conditions maize (3.39 t / ha) outperformed sorghum (1.74 t / ha) and millet (1.33 t / ha), except in cases of fertiliser hazard when sorghum yielded more than maize. Maize responded relatively well to N application, and sorghum performed relatively well without N application. The benefit of millet resided in low yield variability, and lower sensitivity to the weather hazards. Changing management to optimise yields generally involved early sowing (22 days, 2 days and 27 days after onset for maize, sorghum and millet), increased N applications (66 kg N / ha, 27 kg N / ha and 111 kg N / ha for maize, sorghum and millet), and using short duration varieties. For millet the long duration variety was more beneficial. For maize there was opportunity to increase the yield without affecting the risk of yield loss, while for sorghum there was a synergy and for millet a trade-off between yield and risk. The different interactions between hazards and management for the three cereals stress the importance of maintaining farm diversity, as well as operational farm flexibility to respond to production risks.
Resource-poor farmers who are living in the harsh environments of the West African Sahel (WAS) depend on subsistence orientated, low-input farming systems for meeting their livelihood needs. These largely extractive farming systems have resulted in nutrient depletion, soil fertility decline, low productivity and land degradation. A study conducted over 25 years in Niger, aimed to evaluate the long-term effects of organic and mineral fertilizers, cropping systems (CS) of millet and cowpea on crop productivity. The traditional millet/cowpea intercrop system without P fertilizer (TrM/C) was compared with four improved CS receiving P fertilizer: sole millet (MM), millet/cowpea intercrop (M/C), millet-cowpea rotation (M-C), and M/C and rotation with cowpea (M/C-C). Nitrogen fertilizer (N) and the residues of millet (CR) were applied alone or in combination in all five cropping systems. CR were always applied as mulch. The traditional system (TrM/C) produced the lowest millet grain yields (GY) (0.02–0.43 t/ha). All the four improved CS (MM, M/C, M-C and M/C-C) increased GY compared with the traditional system (TrM/C). The M/C and MM systems increased millet GY 3 and 3.3 times compared with the TrM/C, respectively. The M/C-C and M-C systems produced 4 and 4.2 times more GY than that of the TrM/C system, respectively. The lowest revenue was obtained with the TrM/C system. Except for the TrM/C, the revenue of the MM system was lower compared with combined cultivation of millet and cowpea. Compared with the TrM/C system, M/C and M/C-C provided 2 times more revenue. By providing 2.4 times more revenue than the TrM/C system, the M-C system was the most productive system. Cowpea provided from 54% and 56% of the revenue in M/C-C and M-C system, respectively. Soil organic carbon decreased in all the CS from 46% to 63% compared with the soil kept under natural vegetation fallow. The improved CS increased soil P from 3.4 to 4 times. Over the 25 years of cropping, the highest millet yields were obtained with the lower levels of rainfall indicating the role of nutrients in the system. The four improved systems maintained millet yields over the 25 years of cropping. By improving water and nutrient use efficiency, integrated management of mineral fertilizers, CR and cowpea affected more crop productivity than the rainfall. We concluded that cereal-legume based cropping systems treated with small doses of mineral fertilizers and CR could be used for sustainable management of soil fertility in low-input farming systems.
Chickpea is an inexpensive source of protein, minerals, and vitamins to the poor people living in arid and semi-arid regions of Southern Asia and Sub-Saharan Africa. New chickpea cultivars with enhanced levels of protein, Fe and Zn content are a medium-term strategy for supplying essential nutrients for human health and reducing malnutrition. In the current study, a chickpea reference set of 280 accessions, including landraces, breeding lines, and advanced cultivars, was evaluated for grain protein, Fe, Zn content and agronomic traits over two seasons. Using a mid-density 5k SNP array, 4603 highly informative SNPs distributed across the chickpea genome were used for GWAS analysis. Population structure analysis revealed three subpopulations (K = 3). Linkage disequilibrium (LD) was extensive, and LD decay was relatively low. A total of 20 and 46 marker-trait associations (MTAs) were identified for grain nutrient and agronomic traits, respectively, using FarmCPU and BLINK models. Of which seven SNPs for grain protein, twelve for Fe, and one for Zn content were distributed on chromosomes 1, 4, 6, and 7. The marker S4_4477846 on chr4 was found to be co-associated with grain protein over seasons. The markers S1_11613376 and S1_2772537 co-associated with grain Fe content under NSII and pooled seasons and S7_9379786 marker under NSI and pooled seasons. The markers S4_31996956 co-associated with grain Fe and days to maturity. SNP annotation of associated markers were found to be related to gene functions of metal ion binding, transporters, protein kinases, transcription factors, and many more functions involved in plant metabolism along with Fe and protein homeostasis. The identified significant MTAs has potential use in marker-assisted selection for developing nutrient-rich chickpea cultivars after validation in the breeding populations.
Pusa 391, a mega desi chickpea variety with medium maturity duration is extensively cultivated in the Central Zone of India. Of late, this variety has become susceptible to Fusarium wilt (FW), which has drastic impact on its yield. Presence of variability in the wilt causing pathogen, Fusarium oxysporum f.sp. ciceri (foc) across geographical locations necessitates the role of pyramiding for FW resistance for different races (foc 1,2,3,4 and 5). Subsequently, the introgression lines developed in Pusa 391 genetic background were subjected to foreground selection using three SSR markers (GA16, TA 27 and TA 96) while 48 SSR markers uniformly distributed on all chromosomes, were used for background selection to observe the recovery of recurrent parent genome (RPG). BC 1 F 1 lines with 75-85% RPG recovery were used to generate BC 2 F 1. The plants that showed more than 90% RPG recovery in BC 2 F 1 were used for generating BC 3 F 1. The plants that showed more than 96% RPG recovery were selected and selfed to generate BC 3 F 3. Multi-location evaluation of advanced introgression lines (BC 2 F 3) in six locations for grain yield (kg/ha), days to fifty percent flowering, days to maturity, 100 seed weight and disease incidence was done. In case of disease incidence, the genotype IL1 (BGM 20211) was highly resistant to FW in Junagarh, Indore, New Delhi, Badnapur and moderately resistant at Sehore and Nandyal. GGE biplot analysis revealed that IL1(BGM20211) was the most stable genotype at Junagadh, Sehore and Nandyal. GGE biplot analysis revealed that IL1(BGM 20211) and IL4(BGM 20212) were the top performers in yield and highly stable across six environments and were nominated for Advanced Varietal Trials (AVT) of AICRP
Legume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%-24% protein, 41%-51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in "Omics" sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas.
Myo-inositol is one of the most abundant form of inositol. The myo-inositol (MI) serves as substrate to diverse biosynthesis pathways and hence it is conserved across life forms. The biosynthesis of MI is well studied in animals. Beyond biosynthesis pathway, implications of MI pathway and enzymes hold potential implications in plant physiology and crop improvement. Myo-inositol oxygenase (MIOX) enzyme catabolize MI into D-glucuronic acid (D-GlcUA). The MIOX enzyme family is well studied across few plants. More recently, the MI associated pathway's crosstalk with other important biosynthesis and stress responsive pathways in plants has drawn attention. The overall outcome from different plant species studied so far are very suggestive that MI derivatives and associated pathways could open new directions to explore stress responsive novel metabolic networks. There are evidences for upregulation of MI metabolic pathway genes, specially MIOX under different stress condition. We also found MIOX genes getting differentially expressed according to developmental and stress signals in Arabidopsis and wheat. In this review we try to highlight the missing links and put forward a tailored view over myo-inositol oxidation pathway and MIOX proteins.
Spotted stem borer, Chilo partellus, is the most important constraint for increasing the production and productivity of maize and sorghum, the two major coarse cereals in Asia and Africa. The levels of resistance to this pest in the cultivated germplasm are low to moderate, and hence, farmers have to use insecticides for effective control of this pest. However, there is no information on the detoxification mechanisms in C. partellus, which is one of the constraints for deployment of appropriate insecticides to control this pest. The ability to detoxify insecticides varies across insect populations, and hence, we sequenced different populations of C. partellus to identify and understand detoxification mechanisms to devise appropriate strategies for deployment of different insecticides for controlling this pest. Larval samples were sequenced from three different cohorts of C. partellus using the Illumina HiSeq 2500 platform. The data were subjected to identify putative genes that are involved in detoxification on insecticides in our cohort insect species. These studies resulted in identification of 64 cytochrome P450 genes (CYP450s), and 36 glutathione S-transferases genes (GSTs) encoding metabolic detoxification enzymes, primarily responsible for xenobiotic metabolism in insects. A total of 183 circadian genes with > 80% homolog and 11 olfactory receptor genes that mediate chemical cues were found in the C. partellus genome. Also, target receptors related to insecticide action, 4 acetylcholinesterase (AChE), 14 γ-aminobutyric acid (GABA), and 15 nicotinic acetylcholine (nAChR) receptors were detected. This is the first report of whole genome sequencing of C. partellus useful for understanding mode of action of different insecticides, and mechanisms of detoxification and designing target-specific insecticides to develop appropriate strategies to control C. partellus for sustainable crop production.
Sorghum is an important source of dietary iron (Fe) and zinc (Zn) in parts of Africa and India, but there is a need to increase their concentrations to meet dietary requirements. Grains of a genetically biofortified sorghum line (Parbhani Shakti) had higher concentrations of Fe and Zn than a control line (M35-1). Analysis at the tissue level by histochemical staining and at the cellular level using NanoSIMS showed that both minerals are concentrated in the aleurone layer and in the scutellum of the embryo, with Zn also being concentrated in the embryonic axis. However, NanoSIMS showed that “hot spots” of ⁵⁶Fe⁺ and ⁶⁴Zn⁺ were also present in the sub-aleurone and starchy endosperm cells. Most of these hot spots also contained ³¹P¹⁶O⁺ indicating that the Fe and Zn are present as phytates, as in the aleurone and scutellum cells. Low concentrations of ⁵⁶Fe⁺ and ⁶⁴Zn⁺ were also observed in the protein matrix of these cells.
Aflatoxin contamination in commonly consumed cereals and nuts may place children at higher risk of stunting and adults at risk of developing liver cancer. This study investigated knowledge on aflatoxins and the level of aflatoxin B1 contamination in commonly consumed cereals and nuts in Malawi. It also included an examination of the proportion of cereals and nuts contaminated above regulatory maximum limits. Aflatoxin contamination in samples was assessed using an enzyme-linked immunosorbent assay (ELISA) method. Less than half of all households knew that consumption of aflatoxin contaminated grain is associated with stunting and lowered immunity. Sorghum samples were the most contaminated and millet the least contaminated. Aflatoxin contamination was highest in southern Malawi and least in northern Malawi. Observed results indicate that this population is at risk of poor health due to lack of knowledge and aflatoxin exposure. Strategies to address contamination should therefore include a comprehensive education campaign to increase knowledge and promote accessible strategies.
The dataset comprises primary data for the concentration of 29 mineral micronutrients in cereal grains and up to 84 soil chemistry properties from GeoNutrition project surveys in Ethiopia and Malawi. The work provided insights on geospatial variation in the micronutrient concentration in staple crops, and the potential influencing soil factors. In Ethiopia, sampling was conducted in Amhara, Oromia, and Tigray regions, during the late-2017 and late-2018 harvest seasons. In Malawi, national-scale sampling was conducted during the April–June 2018 harvest season. The concentrations of micronutrients in grain were measured using inductively coupled plasma mass spectrometry (ICP-MS). Soil chemistry properties reported include soil pH; total soil nitrogen; total soil carbon (C); soil organic C; effective cation exchange capacity and exchangeable cations; a three-step sequential extraction scheme for the fractionation of sulfur and selenium; available phosphate; diethylenetriaminepentaacetic acid (DTPA)-extractable trace elements; extractable trace elements using 0.01 M Ca(NO3)2 and 0.01 M CaCl2; and isotopically exchangeable Zn. These data are reported here according to FAIR data principles to enable users to further explore agriculture-nutrition linkages.
Fall armyworm (Spodoptera frugiperda (J.E. Smith); FAW)-resistant cultivars and breeding lines have been identified in sub-Saharan Africa. However, these genotypes have not been evaluated for their stability across environments with natural FAW infestation. The objectives of this study were to: (i) identify hybrids/open pollinated varieties combining high grain yield (GYD) and stability across environments with natural FAW infestation, (ii) select maize inbred lines with high GYD and stable FAW resistance, and (iii) identify the most discriminating environments for GYD performance and foliar FAW damage (FFAWD) under natural FAW infestation. The additive main effect and multiplicative interaction (AMMI) model was used to detect the presence of genotype-by-environment interaction (GEI) for GYD, and foliar and ear FAW damage. Seven stability analysis models were used to analyse adaptation and stability of genotypes across environments. The hybrids Mutsa-MN521 and CimExp55/CML334 were the best, combining adaptation and stability across FAW infested environments. Other acceptable hybrids were identified as 113WH330, Manjanja-MN421, CML338/CML334 and PAN53. The local inbred lines SV1P and CML491 combined adaptability and stable FAW resistance across environments. The best exotic donor lines exhibiting stable FAW resistance were CML67, CML346, CML121 and CML338. Harare and Gwebi were identified as the most discriminating sites for GYD performance, while Kadoma and Rattray-Arnold Research Stations were identified for FFAWD among inbred lines.
Genetic diversity studies provide important details on target trait availability and its variability, for the success of breeding programs. In this study, GBS approach was used to reveal a new structuration of genetic diversity and population structure of pigeonpea in Benin. We used a total of 688 high-quality Single Nucleotide Polymorphism markers for a total of 44 pigeonpea genotypes. The distribution of SNP markers on the 11 chromosomes ranged from 14 on chromosome 5 to 133 on chromosome 2. The Polymorphism Information Content and gene diversity values were 0.30 and 0.34 respectively. The analysis of population structure revealed four clear subpopulations. The Weighted Neighbor Joining tree agreed with structure analyses by grouping the 44 genotypes into four clusters. The PCoA revealed that genotypes from subpopulations 1, 2 and 3 intermixed among themselves. The Analysis of Molecular Variance showed 7% of the total variation among genotypes while the rest of variation (93%) was within genotypes from subpopulations indicating a high gene exchange (Nm = 7.13) and low genetic differentiation (PhiPT = 0.07) between subpopulations. Subpopulation 2 presented the highest mean values of number of different alleles (Na = 1.57), number of loci with private alleles (Pa = 0.11) and the percentage of polymorphic loci (P = 57.12%). We discuss our findings and demonstrate how the genetic diversity and the population structure of this specie can be used through the Genome Wide Association Studies and Marker-Assisted Selection to enhance genetic gain in pigeonpea breeding programs in Benin.
Knowledge and evidence on how food value chains can deliver nutrition, especially micronutrients, are limited. A deeper understanding of the food value chains as part of agri-food systems approaches addressing hunger and malnutrition through agricultural development may provide pathways for nutrition and health outcomes.. This systematic review was undertaken using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to assess the broad topic of value chains and micronutrients, focusing on interventions and their related impact pathways. Impact pathway interventions improving micronutrient delivery and consumption were classified as production, accessibility, marketing, income, knowledge and behavioral, and finally, women’s empowerment pathways. However, the case study evidence on the micronutrient-sensitive value chains for nutritional outcomes is very scant. This review identified that making value chains micronutrient-sensitive requires a multi-stakeholder, integrated approach as a basis for concerted action among various stakeholders in terms of policy, research, strengthening partnerships and coordination, and information sharing. The review illustrates the scarcity of literature with a focus on the micronutrients in the context of food value chains and developing countries. The food value chain approach offers great potential to unpack the complexity of food systems and identify entry points and pathways for improving nutrition outcomes, especially the micronutrients. Additionally, this review identifies multiple entry points and calls for strong advocacy of nutrition-sensitive value chain approaches to combat hidden hunger.
Drought is one of the major abiotic stresses that severely limit barley production which is well adapted to drought conditions in the Mediterranean basin where the unpredictable climatic conditions, particularly rainfall, rainfall distribution and both high and low temperatures, may lead to dramatic decreases in yield. Landraces and wild species, represent an important source of variation for adaptive traits that may contribute to increased yield and yield stability under drought conditions. The study includes mapping of Quantitative QTLs for agronomical and morpho-physiological traits associated with drought tolerance. A total of 76 QTLs identified to 11 traits that describe grain yield, biological yield, harvest index, kernel weight, seed per head, days to heading, kernel filling duration, growth vigor, growth habit, lodging and plant height were mapped using RIL population Arta x Harmal-2//Esp/1808-4L which was evaluated at six dry and semi-dry areas over three years.The linkage map contained 254 markers (80 SSR, 174 AFLP) spanning 691cM. Eighty-Four markers’ loci (38 SSR and 46 AFLP) were used for QTLs mapping using the Simple Interval Mapping (SIM) and Simplified Composite Interval Mapping (sCIM). The QTLs which explained the largest part of the phenotypic variation in the dry areas (rainfall <250 mm) were found on the following chromosomes: 2H for biological yield, 1H for harvest index, 2H, 4H and 5H for kernel weight, 2H for days to heading, 1H for the duration of kernel filling period and plant height. While in the semi-dry areas (rainfall between 250- 400mm) QTLs were identified on chromosomes 6H for grain yield, 2H and 5H for kernel weight, 1H and 6H for seed per head, 2H for days to heading. Some of the QTLs were common to those in other published work and some QTLs seemed specific to this study. Chromosomes 1H, 2H, 4H and 5H harbor more than 60% of mapped QTLs for dry areas. For the first time, QTLs explained the variation for grain yield, biological yield, harvest index, kernel weight and days to heading in very dry areas with rainfall less than 150 mm. An understanding of coincidental locations of QTL for correlated phenotypes allows a genetic dissection of different traits and better prediction of the loci most amendable for selection in a breeding program. The identification of marker-trait associations provides suitable opportunities for marker-assisted selection of genomic regions to improve adaptation to low rainfall environments provided interactions with other loci and with the target environments are reasonably well understood.
Since the early 2000s, digital soil maps have been successfully used for various applications, including precision agriculture, environmental assessments and land use management. Globally, however, there are large disparities in the availability of soil data on which digital soil mapping (DSM) models can be fitted. Several studies attempted to transfer a DSM model fitted from an area with a well-developed soil database to map the soil in areas with low sampling density. This usually is a challenging task because two areas have hardly ever the same soil-forming factors in two different regions of the world. In this study, we aim to determine whether finding homosoils (i.e. locations sharing similar soil-forming factors) can help transferring soil information by means of a DSM model extrapolation. We hypothesize that within areas in the world considered as homosoils, one can leverage on areas with high sampling density and fit a DSM model, which can then be extrapolated geographically to an area with little or no data. We collected publicly available soil data for clay, silt, sand, OC, pH and total N within our study area in Mali, West Africa, and its homosoils. We fitted a regression tree model between the soil properties and environmental covariates of the homosoils, and applied this model to our study area in Mali. Several calibration and validation strategies were explored. We also compared our approach with existing maps made at a global and a continental scale. We concluded that geographic model extrapolation within homosoils was possible, but that model accuracy dramatically improved when local data were included in the calibration dataset. The maps produced from models fitted with data from homosoils were more accurate than existing products for this study area, for three (silt, sand, pH) out of six soil properties. This study would be relevant to areas with very little or no soil data to carry critical soils and environmental risk assessments at a regional level.
Pigeonpea, 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.
Background Agri-innovations are mostly delivered to farmers through private and public sector-led institutions around the world, with various degrees of success in Malawi. These distribution systems, on the other hand, do not meet everyone's production and productivity needs, particularly those of smallholder farmers. Alternative gap-filling systems are therefore required. Over the course of 7 years, we performed two studies in Malawi to assess the efficiency of integrated farmer led agri-innovation delivery mechanisms, in order to advise programming and delivery improvements. The first study looked at the impact of farmer-led technology delivery on agricultural output and productivity. It was split into two phases: learning (2010–2015) and scaling-out (2016–2019). The second study looked at how smallholder farmers changed their behaviour, after receiving instruction during the scaling-out phase. A farmer-led social network, community seed banks, was used as the research platform. Results The number of farmers who had access to improved seed increased by 35-fold from 2.4% in the baseline year. Groundnut, the major study crop, had a 1.8-fold increase in productivity. In sorghum, and common bean, the difference in grain yield between beneficiaries and control populations was 19% and 30%, respectively. The lowest aflatoxin contamination was found in groundnut grain samples from trained farmers, showing that learning had occurred, with three training sessions sufficient for initiating and sustaining adoption of agri-innovations. Conclusions Many developing country economies have limited investments in agricultural extension and advisory services, and as well as inefficient agri-input delivery systems, limiting access to science solutions needed to boost productivity. The farmer-led technology and knowledge dissemination systems examined in this research, are appropriate for a variety farming contexts, especially for crops underinvested by private sector, and where public extension and advisory services are poorly funded.
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318 members
Folorunso Mathew Akinseye
  • Research Program West and Central Africa(RP-WCA)
Mahesh Damodhar Mahendrakar
  • Accelerated Crop Improvement
Padmaja Ravula
  • Innovation Systems for the Drylands
Yogendra N Kalenahalli
  • Cell molecular Biology and Trait engineering
Sunita Gorthy
  • Sorghum Breeding
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Hyderabad, India