International Crops Research Institute for the Semi-Arid Tropics
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Nitrogen dose dependent changes in leaf greenness, crop phenology, grain nitrogen content and yield in rice (Oryza sativa L.) sub-species
Get PDFIn the present study, 30 diverse genotypes of rice sub-species were evaluated for variations in phenology, grain protein content, grain morphology and yield under field conditions with different nitrogen (N) regimes i.e., N deficient (N=0) and N sufficient (N=120 kg ha-1). N deficiency decreased the leaf greenness, panicle yield, grain protein content, altered grain morphology and grain-related parameters. Significant variations in grain morphology-related parameters such as grain length and grain width among rice genotypes were observed for different N treatments. Changes in grain morphology related parameters were correlated with yield. The study identified Sahbhagi Dhan, BAM-759, BVD-109, Pusa Sugandh-5, and Kalinga-1 that maintained higher vegetative greenness, while Sahbhagi Dhan, Vandana, Nerica-L-44, Kalinga-1 and APO that showed higher panicle yield under N0 condition. Rice genotypes APO, Nerica-L-42 and Kalinga-1 performed well under N0 with a lesser impact on crop phenology and grain morphology. Grain protein content was found higher in BAM-759, Anjali, Thurur Bhog, IR-64, Rasi, and Kalinga-1under both the treatments. Flag leaf Soil Plant Analysis Development (SPAD) and Normalized Difference Vegetation Index (NDVI) measurements were significantly correlated with grain yield, and grain protein content. The trait specific donors suitable for low N conditions identified in the study will pave the way forward to the research in understanding underlying mechanisms and in crop improvement programs
Improving women's purchasing power through land-enhancing technologies: The case of bio-reclamation of degraded lands in Niger
Get PDFIn Niger, about 50% of the land surface is composed of degraded lateritic soils, and rural women farmers have limited access to productive land. Targeting largely marginalized rural women with bio-reclamation of degraded land (BDL) technologies restores their rights to earn a livelihood through agriculture. This study examines the determinants and impacts of land-enhancing technology on women farmers in Niger. Data were collected from 1,205 randomly selected women farmers in the Maradi and Zinder regions. The sample included 69% of participants into BDL program and 31% of non-participants. To account for selection bias from observable and unobservable factors, an endogenous switching regression (ESR) model was used to estimate the impact of BDL technology on women's household income. A simple probit model was used to analyze the determinants of participation. The results show that key determinants of participation in BDL include income level before participation in BDL, household size, age of participants, number of women in the household, number of children under 5 years old, sex of household head, age of household head, and institutional support. Participation in BDL positively influences participants' income (+14%); non-participants may not benefit from participating as they would probably lose 31% of their income, and the impact of participation in BDL varies widely across regions. Before the advent of BDL, the income of non-participants was higher than that of participants by 25%. It can be inferred that BDL is a pro-poor technology that is not beneficial to all women farmers. This study makes a critical contribution to the literature on land-enhancing technologies. It suggests that the impact of land-enhancing technologies, such as BDL, is closely linked to spatial, economic, environmental, temporal, and cultural contexts. Accordingly, land-enhancing technologies should target locations with large percentages of degraded farmlands and the poorest farmers. These results contribute to food security and poverty alleviation policies in rural dryland areas
Genome-wide association mapping for LLS resistance in a MAGIC population of groundnut (Arachis hypogaea L.)
No full textA genome-wide association study (GWAS) on component traits of LLS resistance in an eight-way multiparent advance generation intercross (MAGIC) population of groundnut in the field and in a light chamber (controlled conditions) was performed via an Affymetrix 48 K single-nucleotide polymorphism (SNP) ‘Axiom Arachis’ array. Multiparental populations with high-density genotyping enable the detection of novel alleles. In total, five quantitative trait loci (QTLs) with marker − log10(p value) scores ranging from 4.25 to 13.77 for the incubation period (IP) and six QTLs with marker − log10(p value) scores ranging from 4.33 to 10.79 for the latent period (LP) were identified across the A- and B-subgenomes. A total of 62 markers‒trait associations (MTAs) were identified across the A- and B-subgenomes. Markers for LLS scores and the area under the disease progression curve (AUDPC) recorded for plants in the light chamber and under field conditions presented − log10 (p value) scores ranging from 4.22 to 27.30. The highest number of MTAs (six) was identified on chromosomes A05, B07 and B09. Out of a total of 73 MTAs, 37 and 36 MTAs were detected in subgenomes A and B, respectively. Taken together, these results suggest that both subgenomes have equal potential genomic regions contributing to LLS resistance. A total of 30 functional nucleotide polymorphisms or genic SNP markers were detected, among which eight genes were found to encode leucine-rich repeat (LRR) receptor-like protein kinases and putative disease resistance proteins. These important SNPs can be used in breeding programmes for the development of cultivars with improved disease resistance
Crop models for assessing impact and adaptation options under climate change
Get PDFIncreased amount of greenhouse gases (GHG) in the atmosphere will cause climate change that will adversely impact crop production especially in the arid and semi-arid regions of the developing countries. Development and implementation of field level adaptations measures to cope up with climate change are necessary to the farmers whose livelihood depends on crop-based income. Crop simulation models that incorporate soil-crop-climate processes of plant growth and that are sensitive to climate change factors can be used to quantify impact of climate change on crop production and evaluating and prioritizing adaptation measures at farm level. This paper analyses the impacts of climate change and plau-sible agronomic, land and water management and genetic adaptations options for the major crops of the semi-arid tropical region with examples from selected sites in India and other developing countries. The crop models need to be linked to the improved pest, disease and weed models to analyze and predict yield losses, especially those due to climate change. The simulation models also need to incorporate the impact of extreme weather events on crop production that is projected to increase with climate change
Landscape pattern analysis using GIS and remote sensing to diagnose soil erosion and nutrient availability in two agroecological zones of Southern Mali
Get PDFBackground Soil is a basic natural resource for the existence of life on earth, and its health is a major concern for rural livelihoods. Poor soil health is directly associated with reduced agricultural land productivity in many subSaharan countries, such as Mali. Agricultural land is subjected to immense degradation and the loss of important soil nutrients due to soil erosion. The objective of the study was to diagnose the spatial distribution of soil erosion and soil nutrient variations under diferent land use in two agroecological zones of Southern Mali using the Geographical Information System (GIS) software, the empirically derived relationship of the Revised Universal Soil Loss Equation, in-situ soil data measurement and satellite products. The soil erosion efect on agricultural land productivity was discussed to highlight the usefulness of soil and water conservation practices in Southern Mali.
Results The results of the land use and land cover change analysis from 2015 to 2019 revealed signifcant area
reductions in water bodies, bare land, and savanna woodland for the beneft of increased natural vegetation and
agricultural land. There was signifcant variation in the annual soil loss under the diferent land use conditions. Despite recordings of the lowest soil erosion rates in the majority of the landscape (71%) as a result of feld-based soil and water conservation practices, the highest rates of erosion were seen in agricultural felds, resulting in a reduction in agricultural land area and a loss of nutrients that are useful for plant growth. Spatial nutrient modelling and mapping revealed a high defciency and signifcant variations (p<0.05) in nitrogen (N), phosphorus (P), potassium (K), and carbon (C) in all land use and land cover types for the two agroecologies. Conclusions The study highlighted the inadequacies of existing feld-based soil and water conservation practices to reduce soil erosion and improve landscape management practices. The fndings of the study can inform land management planners and other development actors to strategize and prioritize landscape-based intervention practices and protect catchment areas from severe erosion for the enhanced productivity of agricultural felds
Developing future heat‑resilient vegetable crops
Get PDFClimate change seriously impacts global agriculture, with rising temperatures directly affecting the yield. Vegetables are an essential part of daily human consumption and thus have importance among all agricultural crops. The human population is increasing daily, so there is a need for alternative ways which can be helpful in maximizing the harvestable yield of vegetables. The increase in temperature directly affects the plants’ biochemical and molecular processes; having a significant impact on quality and yield. Breeding for climate-resilient crops with good yields takes a long time and lots of breeding efforts. However, with the advent of new omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, the efficiency and efficacy of unearthing information on pathways associated with high-temperature stress resilience has improved in many of the vegetable crops. Besides omics, the use of genomics-assisted breeding and new breeding approaches such as gene editing and speed breeding allow creation of modern vegetable cultivars that are more resilient to high temperatures. Collectively, these approaches will shorten the time to create and release novel vegetable varieties to meet growing demands for productivity and quality. This review discusses the effects of heat stress on vegetables and highlights recent research with
a focus on how omics and genome editing can produce temperature-resilient vegetables more efficiently and faster
Assessing the environment mediated alterations in chickpea wilt incidence in North Western Zone of India
No full textFusarium wilt, a devastating disease of chickpea is highly influenced by environmental conditions. Several reports have shown that host-plant resistance becomes ineffective as a result of changes in climatic factors. In this study, two chickpea varieties, JG 62 (wilt susceptible) and HC 5 (wilt resistant) were evaluated for changes in natural wilt incidence for a period of three years (2017-18 to 2019-20) in relation to the atmospheric and edaphic factors occurring in the growing seasons. Lower temperatures and higher soil moisture conditions favoured by the rainfall supported little reduction in wilt incidence during the cropping season in resistant variety HC 5, as compared to the previous years. However, there was no significant change in the disease incidence in the case of variety JG 62 owing to its strong susceptible nature
Household modelling and trade-off analysis to design resilient crop-livestock farming systems in dry regions of Senegal
Get PDFThis paper analyzes integrated crop-livestock farming systems in dryland regions of Senegal using household survey data and whole farm household modeling. It focuses on the Kaffrine and Thies regions, which exhibit differences in cultivated land area, staple crops grown, and livestock holdings. The analysis identifies region-specific opportunities to sustainably enhance productivity, resilience, and food security. The mechanistic model incorporates factors like crop mixes, livestock herd dynamics, climate impacts, economics, and labor to simulate entire farms. It finds crops generating most of the household income in the more crop-focused Thies region versus only about one-third in livestock-centric Kaffrine, where nearly half of incomes are from small ruminants. Three resilience enhancing interventions were evaluated in the model – i. introducing improved cattle, ii. farmer participation in climate smart agriculture (CSA) and climate information services (CIS) program, and iii. Combining intervention scenario-i and intervention scenario-ii. Introducing improved cattle have over twice the marginal impact on farm cashflows in cattle-dominant Kaffrine compared to crop-focused Thies. Farmers participation in CSA and CIS program raises their incomes in comparable percentages in both regions given the broad importance of crops. Pursuing integrated crop and livestock interventions yields additive income gains in mixed farming Kaffrine versus specialized Thies. The analysis demonstrates greater opportunities for synergies between crops and livestock in Kaffrine’s mixed system context compared to Thies. It provides empirical evidence to inform agricultural policies and investments tailored to regional production patterns. Overall, the paper shows the value of integrated, context-specific approaches to enhancing productivity, resilience, and food security across Senegal's diverse smallholder systems
Haemoglobin diagnostic cut-offs for anaemia in Indian women of reproductive age
No full textBackground
The persistent high prevalence of anaemia among Indian women of reproductive age (WRA) despite aggressive long-term iron supplementation could be related to over-diagnosis from an inappropriately high haemoglobin (Hb) diagnostic cut-off. To develop an appropriate cut-off for Indian WRA, we hypothesized that during iron-folic acid (IFA) supplementation to a mixed (anaemic/non-anaemic) WRA population, the positive slope of the Hb-plasma ferritin (PF) response in anaemic women would inflect into a plateau (zero-response) as a non-anaemic status is reached. The 2.5th percentile of the Hb distribution at this inflection point will be the diagnostic Hb cut-off for iron-responsive anaemia.
Method
A hierarchical mixed effects model, with a polynomial mean and variance model to account for intraclass correlation due to repeated measures, was used to estimate the response curve of Hb to PF, or body iron stores, in anaemic and non-anaemic WRA (without inflammation), who were receiving a 90-day IFA supplementation.
Results
The Hb response curve at low PF values showed a steep increase, which inflected into a plateau at a PF of 10.1 µg/L and attained a steady state at a PF of 20.6 µg/L. The Hb distribution at the inflection was a normal probability distribution, with a mean of 12.3 g/dL. The 2.5th percentile value of this distribution, or the putative diagnostic Hb cut-off for anaemia, was 10.8 g/dL (~11 g/dL).
Conclusion
The derived Hb cut-off is lower than the current adult values of 12 g/dL and could partly explain the persistently high prevalence of anaemia
Crop modelling in agricultural crops
Get PDFWith limited land resources and a growing population, agricultural output is under considerable strain. New technology is necessary for overcoming these issues and advising farmers, legislators and other decision-makers on adopting sustainable agriculture despite global climate variations. This has led to the crop simulation models that illustrate crop growth and development processes as a function of climate, soil and crop man-agement. They also support agricultural agronomy (yield estimate, biomass, etc.), pest control, breeding and natural resource management. This study examines crop modelling for agricultural production planning and field-level management strategies. These can help res-earchers comprehend the significance of crop modelling for scenario-building and provide field-level suggestions by analysing future conditions and strategic activities to minimize the predicted negative influence and maximize the projected positive effect. The limitations and poten-tial directions of crop modelling improvement have also been highlighted in this study