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Production and productivity growth in Chinese agriculture: new measurement and evidence.
No full textMaintaining essential healthcare services in Addis Ababa during COVID-19: A qualitative study
No full textBackground: Worldwide, health systems have been challenged by the overwhelming demands of the COVID-19 pandemic. In Ethiopia, maintaining essential health services during the COVID-19 pandemic is critical to preventing severe outcomes and protecting the gains made over the past years in the health sector. This project aims to explore the health system’s response to maintaining essential healthcare services in Addis Ababa, Ethiopia.
Methods: A total of 60 key informant interviews were conducted by purposively selecting key stakeholders from Federal Ministry of Health, Addis Ababa Regional Health Bureau, Sub-city Health Offices, and frontline healthcare providers. Interviews were transcribed verbatim and coded using Open Code. Thematic analysis was employed to analyze the data.
Result: COVID-19 affected the delivery of essential health services in several ways, namely: decline in health service utilization, fear of infection among healthcare providers, stigma towards healthcare providers, and perceived decrease in quality-of-service provision. However, the health system actors made efforts to sustain services while responding to the pandemic by enacting changes in the service delivery modality. The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). The primary challenges encountered were burnout of the health workforce and a shortage of personal protective equipment.
Conclusion: COVID-19 has affected the delivery of essential health services in multifaceted ways. System actors have accordingly made efforts to sustain services while responding to the pandemic
Simulation of rice blast epidemics under current and projected climate change scenarios
No full textRice blast disease caused by Magnaporthe oryzae B.C. Couch causes significant yield losses in rice production globally. This research study was conducted develop, verify, and validate a mechanistic rice blast simulation model using STELLA 9.1 modeling software based on the structure of the EPIRICE model developed at IRRI. A leaf blast submodel was coupled to the neck blast submodel using the leaf and neck blast relationship based on a linear regression equation. The model was developed and verified using leaf and neck blast data from eight verification sites and validated in five sites in the Philippines. In general, graphical comparison showed similar shapes of simulated and observed leaf blast severity and neck blast incidence progress curves. Statistical validation of the model used the Wilcoxon test, Root mean square error (RMSE), and equivalence test. The RMSE test indicated satisfactory results, showing low values for leaf blast severity and approximately twice as high values for neck blast incidence. The Wilcoxon test showed significant differences between observed and simulated leaf blast severities at all validation sites and 60% accuracy in predicting neck blast. On the other hand, the equivalence test showed 40% accuracy in predicting leaf blast severity and 40% accuracy in predicting neck blast incidence. Inconsistencies in the statistical tests can be due to the complexity and differences in the leaf and neck blast pathosystems. Potential leaf blast epidemics were mapped in Bangladesh, India, Indonesia and the Philippines using projected weather data generated by the Australian Community Climate and Earth System Simulator (ACCESS) Coupled Model for the 6th Coupled Model Intercomparison Project (CMIP6) of International Panel for Climate under two climate scenarios. SSP2-4.5 (moderate greenhouse gas pathway) and SSP5- 8.5 (high greenhouse gas emission pathway) were used to evaluate the projected effects of climate change disease epidemics in 2030 and 2050. Projected leaf blast epidemics are expected to decline in several rice-growing regions. However, rice-growing areas with significant rainfall and cool temperature due to climate change remain at risk for the disease. This underscores the importance of prioritizing the development and implementation of strategies to manage leaf blast in vulnerable areas
Assessing the long-term impact of conservation agriculture on wheat-based systems in Tunisia using APSIM simulations under a climate change context
No full textEffects of site-specific fertilizer recommendations and integrated soil fertility management practices on crop yields and incomes in the Ethiopian highlands: baseline report
No full textThe Vision of a Digital Public Infrastructure for Agriculture
No full textThe book chapter is published on page no 105-121, by Ram Dhulipala, Nipun Mehrotra and Ajit Kanitkar. The authors published a policy brief in 2023 titled “The Vision of a Digital Public Infrastructure for Agriculture” for the T20/G20, which was subsequently selected out of 300+ briefs by the Government of India to be published as a detailed book chapter in 2024 in the G20 Compendium. The chapter emphasizes the dual challenge in agriculture of enhancing smallholder productivity and incomes while ensuring environmental sustainability. Digital technologies, when implemented responsibly, can address these issues by transforming agrifood systems. A conceptual approach termed "Digital Public Infrastructure for Agriculture" (DPI4A) focuses on equitable development in G20 nations, aligning with the IDEA framework from India. Key elements include ethical safeguards, public-private partnerships, and governance mechanisms. The chapter highlights G20 leadership in fostering partnerships, global pilots, and frameworks for collaboration to address climate change and equity challenges in agrifood systems
Exploring the genetic variability and diversity of pearl millet core collection germplasm for grain nutritional traits improvement
No full textImproving essential nutrient content in staple food crops through biofortification breeding can overcome the micronutrient malnutrition problem. Genetic improvement depends on the availability of genetic variability in the primary gene pool. This study was aimed to ascertain the magnitude of variability in a core germplasm collection of diverse origin and predict pearl millet biofortification prospects for essential micronutrients. Germplasm accessions were evaluated in field trials at ICRISAT, India. The accessions differed significantly for all micronutrients with over two-fold variation for Fe (34–90 mg kg−1), Zn (30–74 mg kg−1), and Ca (85–249 mg kg−1). High estimates of heritability (> 0.81) were observed for Fe, Zn, Ca, P, Mo, and Mg. The lower magnitude of genotype (G) × environment (E) interaction observed for most of the traits implies strong genetic control for grain nutrients. The top-10 accessions for each nutrient and 15 accessions, from five countries for multiple nutrients were identified. For Fe and Zn, 39 accessions, including 15 with multiple nutrients, exceeded the Indian cultivars and 17 of them exceeded the biofortification breeding target for Fe (72 mg kg−1). These 39 accessions were grouped into 5 clusters. Most of these nutrients were positively and significantly associated among themselves and with days to 50% flowering and 1000-grain weight (TGW) indicating the possibility of their simultaneous improvement in superior agronomic background. The identified core collection accessions rich in specific and multiple-nutrients would be useful as the key genetic resources for developing biofortified and agronomically superior cultivars
How does the human rights perspective help to shape the food and nutrition policy research agenda?
No full textA band selection method for consumer-grade camera modification for UAV-based rapeseed growth monitoring
No full textNear-infrared (NIR) modification of low-cost cameras is considered an important method to acquire high-resolution NIR images on an unmanned aerial vehicle (UAV) platform. However, few studies have examined filter selection methods to modify consumer-grade cameras for UAV-based agricultural crop monitoring. This study addresses a key challenge: how to balance imaging quality with spectral sensitivity when selecting filters for the modification of consumer-grade cameras. To this end, the normalized difference spectral index (NDSI) and the ratio spectral index (RSI) formulations were used to calculate the spectral indices (SIs) from all possible combinations of any two center wavelengths in UAV hyperspectral data. The contour maps of the coefficient of determination (R2) between the SIs and ground-measured rapeseed LAI were then computed to automatically generate the broadband combinations with optimized center wavelengths and effective bandwidths for selecting filters on camera modification. Results showed that a consumer-grade camera (Nikon D7000) modified by the selected filters had performance comparable with a multispectral camera (RedEdge Micasense 3), but slightly worse than a research-grade hyperspectral camera (Nano-Hyperspec®) in terms of SIs for LAI estimation. In addition, the high-resolution images from the modified camera were processed to obtain accurate crop plant height information. The SIs coupled with plant height from the modified camera (rRMSE = 18.1 % for field 1 and 14.3 % for field 2) was found to perform similar to, and in some cases even better than, those from the research-grade multispectral (rRMSE = 17.9 % and 16.7 % for the respective fields) and hyperspectral (rRMSE = 18.8 % for field 1) cameras for UAV-based LAI estimation. The findings from this study indicate that the proposed camera modification method is feasible and adaptable to agricultural crop monitoring. Thus, appropriately modified consumer-grade cameras can be a cost-effective replacement for research-grade sensors to rapidly and accurately assess crop growth status