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Trade-offs between labour migration and agricultural productivity: Evidence from smallholder wheat systems in Nepal
No full textRural labour out-migration has become a major contributor to off-farm income through remittances and plays a crucial role in supporting the livelihoods of rural households in developing economies. However, research on the simultaneous on-farm and off-farm impacts of labour migration is still lacking. This study assesses the impacts of household labour migration on wheat productivity, labour and total costs, profitability and off-farm income among smallholder wheat growers in Nepal. We use endogenous switching regression and two-stage least squares regression models to control for potential endogeneity. The findings reveal that labour migration boosts off-farm income due to remittances but negatively affects wheat productivity and profitability due to labour shortages. In addition, heterogeneous effects are observed, with large farms, cooperative membership, use of farm mechanization and non-marginalized castes recording positive impacts. The study suggests that social institutions, such as cooperatives, and farm mechanization can create synergies between labour migration and agricultural productivity in Nepal.202-22
Adaptations of rice seed germination to drought and hypoxic conditions: Molecular and physiological insights
No full textSeed germination is crucial for plant survival, crop stand establishment, and achieving optimal grain yield. The main objective of this review is to explore the physiological and molecular mechanisms governing rice seed germination under aerobic (water stress) and anaerobic (hypoxic) conditions in direct-seeded rice (DSR) systems. Moreover, it discusses the recent genomic advancements and innovations to improve rice seed germination. Here, we discuss how coleoptile and mesocotyl elongation plays a vital role in anaerobic germination (AG) and the function of raised antioxidants, including superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) in maintaining Reactive Oxygen Species (ROS), and malondialdehyde (MDA) homeostasis for stabilizing seed germination in water-scarce conditions. This study comprehensively highlights the functions and dynamics of phytohormones-GA (gibberellic acid) and ABA (abscisic acid)-key regulatory genes, transcription factors (TFs), key proteins, and regulatory metabolic pathways, including glycolysis, the pentose phosphate pathway (PPP), and the tricarboxylic acid cycle (TCA), in regulating seed germination under both conditions. Conventional agronomic and cultural practices, such as seed selection, seed priming, seed coating, and hardening, have proven to improve seed germination. Moreover, the utilization of molecular and novel approaches-such as clustered regularly interspaced short palindromic repeat (CRISPR-Cas9) mediated genome editing, marker-assisted selection (MAS), genome-wide associations studies (GWAS), single nucleotide polymorphisms (SNPs), multi-omics, RNA sequencing-combined with beneficial quantitative trait loci (QTLs) has expanded knowledge of crop genomics and inheritance. These advancements aid the development of specific traits for enhancing seed germination in DSR.656-67
Data augmentation enhances plant-genomic-enabled predictions
No full textGenomic selection (GS) is revolutionizing plant breeding. However, its practical implementation is still challenging, since there are many factors that affect its accuracy. For this reason, this research explores data augmentation with the goal of improving its accuracy. Deep neural networks with data augmentation (DA) generate synthetic data from the original training set to increase the training set and to improve the prediction performance of any statistical or machine learning algorithm. There is much empirical evidence of their success in many computer vision applications. Due to this, DA was explored in the context of GS using 14 real datasets. We found empirical evidence that DA is a powerful tool to improve the prediction accuracy, since we improved the prediction accuracy of the top lines in the 14 datasets under study. On average, across datasets and traits, the gain in prediction performance of the DA approach regarding the Conventional method in the top 20% of lines in the testing set was 108.4% in terms of the NRMSE and 107.4% in terms of the MAAPE, but a worse performance was observed on the whole testing set. We encourage more empirical evaluations to support our findings
The adult plant resistance (APR) genes Yr18, Yr29 and Yr46 in spring wheat showed significant effect against important yellow rust races under North-West European field conditions
No full textYellow rust caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most important wheat diseases. Adult plant resistance (APR) genes have gained the attention of breeders and scientists because they show higher durability compared to major race-specific genes. Here, we determined the effect of the APR genes Yr18, Yr29 and Yr46 in North-West European field conditions against three currently important Pst races. We used three pairs of sibling wheat lines developed at CIMMYT, which consisted of a line with the functional resistance gene and a sibling with its non-functional allele. All APR genes showed significant effects against the Pst races Warrior and Warrior (-), and a race of the highly aggressive strain PstS2. The effects of Yr18 and Yr46 were especially substantial in slowing down disease progress. This effect was apparent in both Denmark, where susceptible controls reached 100 percent disease severity, and in United Kingdom where disease pressure was lower. We further validated field results by quantifying fungal biomass in leaf samples and by micro-phenotyping of samples collected during early disease development. Microscopic image analyses using deep learning allowed us to quantify separately the APR effects on leaf colonization and pustule formation. Our results show that the three APR genes can be used in breeding yellow rust resistant varieties of spring wheat to be grown in North-West European conditions, and that deep learning image analysis can be an effective method to quantify effects of APR on colonisation and pustule formation
Prospective impacts of expanding agroecological transitions on Zimbabwe’s government's socio-economic and environmental agendas
No full textThe CGIAR funded Agroecology Initiative (AE-I) in Zimbabwe aims to achieve specific outcomes that will contribute to the broader goal of promoting agroecology in diverse contexts in Zimbabwe by 2024. As AE-I gains a deeper understanding of agroecology in the context of its implementation sites in Zimbabwe, it has become clear that it must critically evaluate its incremental efforts viz their transformative capabilities per agroecological principles.Thus, the current assignment seeks to assess the extent to which AE-I’s activities impact the broader socioeconomic and environment agendas in Zimbabwe. The goal is to assess agroecological practices' early impacts and map transformative pathways to achieving broader systemic impact. This analysis will inform a scaling strategy for AE-I. Moreover, it will allow AE-I to navigate the complex relationship between agroecology and broader social-economic-ecological agendas. By conducting an ex-ante assessment, this assignment aims to determine the potential extent and impacts of agroecological transitions, as defined by the activities undertaken by AE-I, on government priorities and commitments, including key national benchmarks like the Nationally Determined Contributions (NDCs) and the National Biodiversity Strategy and Adaptation Plans (NBSAPs). Additionally, we recognize the importance of understanding the underlying dynamics shaping agroecological transitions. This involves analyzing the roles of agroecological science, practices, and social movements in influencing behavioral shifts and empowering smallholder farming households. By synthesizing insights from Zimbabwean experiences and AE -I activities, and integrating them into a strategic framework, we aim to facilitate the transition of farming households in low- and middle-income countries towards agroecology. This report details an ex-ante assessment to evaluate the prospective impacts of expanding agroecological transitions on government socio-economic and environmetal agendas, incorporating an analysis of national commitments like Nationally Determined Contributions (NDCs) and the National Biodiversity Strategy and Adaptation Plans (NBSAPs).25 page
Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021
No full textBackground: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.2100-213
CropSustaiN: new innovative crops to reduce the nitrogen footprint from agriculture
No full textThe Novo Nordisk Foundation is excited to launch CropSustaiN, a pioneering research and innovation effort in collaboration with the International Maize and Wheat Improvement Centre (CIMMYT). This transformative initiative aims to validate and enhance the potential impact of novel wheat lines that are significantly better at using nitrogen through integration of Biological Nitrification Inhibition (BNI) capability – accelerating breeding and subsequent deployment of these innovative wheat lines. CropSustaiN addresses the pressing challenges of nitrogen pollution and inefficient fertiliser use in agriculture, which significantly contribute to greenhouse gas (GHG) emissions and ecological degradation.4 page
Exploration of economic and environmental impacts of crop diversification in the northwestern IGP of India
No full textThe energy-intensive rice-wheat system in the northwestern Indo-Gangetic Plain (NWIGP) significantly increases production costs and greenhouse gas (GHG) emissions, driven by chemical fertilizers, fossil fuels for intensive tillage, irrigation, and high labor use. A particularly harmful practice is residue burning, commonly used to clear fields after harvest, releasing large amounts of carbon dioxide and particulate matter, worsening air pollution, and posing health risks to local communities. To address these challenges, on-station research was initiated in collaboration with the ICAR-Central Soil Salinity Research Institute (CSSRI) and the Transforming Agrifood Systems in South Asia (TAFSSA) initiative under CIMMYT. The research focuses on reducing cultivation costs, improving farm profitability, decreasing energy use, and lowering GHG emissions through diversified cropping systems. 12 page