Does access to improved grain storage technology increase farmers' welfare? Experimental evidence from maize farming in Ethiopia

Hugo De Groote Bart Minten (2024, [Artículo])

Seasonal price variability for cereals is two to three times higher in Africa than on the international reference market. Seasonality is even more pronounced when access to appropriate storage and opportunities for price arbitrage are limited. As smallholder farmers typically sell their production after harvest, when prices are low, this leads to lower incomes as well as higher food insecurity during the lean season, when prices are high. One solution to reduce seasonal stress is the use of improved storage technologies. Using data from a randomised controlled trial, in a major maize-growing region of Western Ethiopia, we study the impact of hermetic bags, a technology that protects stored grain against insect pests, so that the grain can be stored longer. Despite considerable price seasonality—maize prices in the lean season are 36% higher than after harvesting—we find no evidence that hermetic bags improve welfare, except that access to these bags allowed for a marginally longer storage period of maize intended for sale by 2 weeks. But this did not translate into measurable welfare gains as we found no changes in any of our welfare outcome indicators. This ‘near-null’ effect is due to the fact that maize storage losses in our study region are relatively lower than previous studies suggested—around 10% of the quantity stored—likely because of the widespread use of an alternative to protect maize during storage, for example a cheap but highly toxic fumigant. These findings are important for policies that seek to promote improved storage technologies in these settings.

Hermetic Storage Randomised Controlled Trial CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA STORAGE PILOT FARMS SEASONALITY WELFARE MAIZE

Transpiration of a tropical dry deciduous forest in Yucatan, Mexico

EVELYN RAQUEL SALAS ACOSTA José Luis Andrade Torres Jorge Perera ROBERTH ARMANDO US SANTAMARIA bernardo figueroa-espinoza Jorge M. Uuh-Sonda EDUARDO CEJUDO ESPINOSA (2022, [Artículo])

The study of forest hydrology and its relationships with climate requires accurate estimates of water inputs, outputs, and changes in reservoirs. Evapotranspiration is frequently the least studied component when addressing the water cycle; thus, it is important to obtain direct measurements of evaporation and transpiration. This study measured transpiration in a tropical dry deciduous forest in Yucatán (Mexico) using the thermal dissipation method (Granier-type sensors) in representative species of this vegetation type. We estimated stand transpiration and its relationship with allometry, diameter-at-breast-height categories, and previously published equations. We found that transpiration changes over time, being higher in the rainy season. Estimated daily transpiration ranged from 0.562 to 0.690 kg m–2 d–1 in the late dry season (April–May) and from 0.686 to 1.29 kg m–2 d–1 in the late rainy season (September–October), accounting for up to 51% of total evapotranspiration in the rainy season. These daily estimates are consistent with previous reports for tropical dry forests and other vegetation types. We found that transpiration was not species-specific; diameter at breast height (DBH) was a reliable way of estimating transpiration because water use was directly related to allometry. Direct measurement of transpiration would increase our ability to accurately estimate water availability and assess the responses of vegetation to climate change. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

SAP FLUX SEASONALITY STAND TRANSPIRATION EVAPOTRANSPIRATION DRY DECIDUOUS FOREST BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

Calibrated multi-model ensemble seasonal prediction of Bangladesh summer monsoon rainfall

Nachiketa Acharya Carlo Montes Timothy Joseph Krupnik (2023, [Artículo])

Bangladesh summer monsoon rainfall (BSMR), typically from June through September (JJAS), represents the main source of water for multiple sectors. However, its high spatial and interannual variability makes the seasonal prediction of BSMR crucial for building resilience to natural disasters and for food security in a climate-risk-prone country. This study describes the development and implementation of an objective system for the seasonal forecasting of BSMR, recently adopted by the Bangladesh Meteorological Department (BMD). The approach is based on the use of a calibrated multi-model ensemble (CMME) of seven state-of-the-art general circulation models (GCMs) from the North American Multi-Model Ensemble project. The lead-1 (initial conditions of May for forecasting JJAS total rainfall) hindcasts (spanning 1982–2010) and forecasts (spanning 2011–2018) of seasonal total rainfall for the JJAS season from these seven GCMs were used. A canonical correlation analysis (CCA) regression is used to calibrate the raw GCMs outputs against observations, which are then combined with equal weight to generate final CMME predictions. Results show, compared to individual calibrated GCMs and uncalibrated MME, that the CCA-based calibration generates significant improvements over individual raw GCM in terms of the magnitude of systematic errors, Spearman's correlation coefficients, and generalised discrimination scores over most of Bangladesh areas, especially in the northern part of the country. Since October 2019, the BMD has been issuing real-time seasonal rainfall forecasts using this new forecast system.

Multi-Model Ensemble Seasonal Forecasting CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE SERVICES FORECASTING MONSOONS

Planting rice at monsoon onset could mitigate the impact of temperature stress on rice–wheat systems of Bihar, India

Carlo Montes Anton Urfels Eunjin Han Balwinder-Singh (2023, [Artículo])

Rainy Season TIMESAT APSIM Agricultural Production Systems Simulator Climate Adaptation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RICE WHEAT MONSOONS WET SEASON CROP MODELLING CLIMATE CHANGE ADAPTATION

Metodología predictiva para el análisis de asiento trasero en pruebas de anclaje de cinturón de seguridad

Predictive methodology for rear seat analysis in seat belt anchorage testings

José Guadalupe Velasco Ortega GIOVANNI VIDAL FLORES (2023, [Artículo])

Se presenta una metodología a seguir para el análisis de un asiento trasero durante la prueba de anclaje del cinturón de seguridad, establecida en la norma FMVSS 210 por sus siglas en ingles Federal Motor Vehicle Safety Standards. Es importante destacar que el cinturón de seguridad reduce el riesgo de lesiones, y en caso de colisión, el cinturón ayuda a distribuir la fuerza del impacto en una superficie más grande es decir la estructura metálica del asiento, lo que se busca es minimizar el riesgo de lesiones graves. La metodología propuesta tiene el fin de predecir el desempeño como función del desplazamiento de la estructura metálica mediante el uso del elemento finito (FEM). En esta metodología, se analiza la menor cantidad de elementos que compone la estructura del asiento con el propósito de reducir el tiempo del análisis, considerando solo los elementos y componentes que tienen mayor efecto con el desempeño del cinturón de seguridad, generando el análisis más rápido y eficiente. Al contrastar los resultados obtenidos a través del análisis mediante elemento finito con las pruebas reales se determinó que el método FEM es eficaz para predecir los puntos débiles de la estructura metálica que influyen en el desplazamiento y/o deformación del asiento durante la prueba.

A methodology is presented for analysis of a rear seat during the Safety Belt Anchorage test established in FMVSS 210 [1], which stands for Federal Motor Vehicle Safety Standards. It is important to note that the safety belt reduces the risk of injury, and in the event of a collision, the belt helps distribute the force of the impact over a larger surface area, namely the metal structure of the seat. The goal is to minimize the risk of serious injuries. The goal of proposed methodology is to predict the performance as a function of displacement of the metal structure by using Finite Element Method (FEM). In this methodology, the minimum number of elements that make up the seat structure is analyzed in order to reduce analysis time, considering only the elements that play and have effect on the performance of the safety belt, thus generating a faster and more efficient analysis. By comparing the results obtained through Finite Element Method with the actual test, it was determined that the FEM method is effective in predicting the weak points of the metal structure that influence the displacement and/or deformation of the seat during the test.

FVMSS 210 Método de elemento finito Asiento trasero Prueba de anclaje Cinturón de seguridad Finite element method Rear seat Anchorage test Seat belt INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Remedies for the Inconsistences in the Times of Execution of the Unsorted Database Search Algorithm within the Wave Approach

Manuel Ávila Aoki José Benito Elizalde Salas (2017, [Artículo])

The typical semiclassical wave version of the unsorted database search algorithm based on a system of coupled simple harmonic oscillators does not consider an important ingredient of Grovers original algorithm as it is quantum entanglement. The role of entanglement in the wave version of the unsorted database search algorithm is explored and contradictions with the time of execution of Grovers algorithm are found. We remedy the contradictions by employing two arguments, one of them qualitative and the other quantitative. For the qualitative argument we employ the probabilistic nature of a legitimate quantum algorithm and remedy the above inconsistence. Within the quantitative argument we identify a parameter in the wave version of the unsorted database search algorithm which is related to entanglement. The contradiction with the time of execution of Grovers algorithm is solved by choosing an appropriate values of such a parameter which incorporates entanglement to the wave version of the unsorted database search algorithm. The utility of the present arguments are evident if the wave version of the unsorted data base search algorithm is experimentally implemented through a system of N quantum dots with a harmonic oscillator potential as a confinement potential for each of the quantum dots. Each of the above N vibrating quantum dots must be coupled to an extra single vibrating quantum dot which entangles to all of them. In order to obtain optimal results, the coupling constants of the mentioned quantum dots should be adjusted in the way described in the present work.

Computación Unsorted database search Grover algorithm wave entanglement queries time Computación Unsorted database search Grover algorithm wave entanglement queries time INGENIERÍA Y TECNOLOGÍA

Evaluation of Kenya stem rust observation nursery wheat genotypes for yield and yield components under artificial rust conditions

Mandeep Randhawa (2021, [Artículo])

Grain Yield Yield Stability Genotype x Season Interaction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT HERITABILITY YIELDS RUSTS GENOTYPES

Soil CO2 efflux fluctuates in three different annual seasons in a semideciduous tropical forest in Yucatan, Mexico

El flujo de CO2 del suelo fluctúa en tres temporadas del año en un bosque tropical semideciduo de Yucatán, México

Fernando Arellano-Martín JUAN MANUEL DUPUY RADA ROBERTH ARMANDO US SANTAMARIA José Luis Andrade Torres (2022, [Artículo])

Tropical forest soils store a third of the global terrestrial carbon and control carbon dioxide (CO2) terrestrial effluxes to the atmosphere produced by root and microbial respiration. Soil CO2 efflux varies in time and space and is known to be strongly influenced by soil temperature and water content. However, little is known about the influence of seasonality on soil CO2 efflux, especially in tropical dry forests. This study evaluated soil CO2 efflux, soil temperature, and soil volumetric water content in a semideciduous tropical forest of the Yucatan Peninsula under two sites (flat areas close to and far from hills), and three seasons: dry, wet, and early dry (a transition between the rainy and dry seasons) throughout a year. Additionally, six 24-h periods of soil CO2 efflux were measured within these three seasons. The mean annual soil CO2 efflux was 4±2.2 μmol CO2 m-2 s-1, like the mean soil CO2 efflux during the early dry season. In all seasons, soil CO2 efflux increased linearly with soil moisture, which explained 45% of the spatial-temporal variation of soil CO2 efflux. Soil CO2 efflux was higher close to than far from hills in some months. The daily variation of soil CO2 efflux was less important than its spatial and seasonal variation likely due to small diel variations in temperature. Transition seasons are common in many tropical dry forests, and they should be taken into consideration to have a better understanding of the annual soil CO2 efflux, especially under future climate-change scenarios. © 2022 Mexican Society of Soil Science. All Rights Reserved.

EARLY DRY SEASON SOIL TEMPERATURE SOIL VOLUMETRIC WATER CONTENT TROPICAL DRY FOREST BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh

Mustafa Kamal Timothy Joseph Krupnik (2024, [Artículo])

High-resolution mapping of rice fields is crucial for understanding and managing rice cultivation in countries like Bangladesh, particularly in the face of climate change. Rice is a vital crop, cultivated in small scale farms that contributes significantly to the economy and food security in Bangladesh. Accurate mapping can facilitate improved rice production, the development of sustainable agricultural management policies, and formulation of strategies for adapting to climatic risks. To address the need for timely and accurate rice mapping, we developed a framework specifically designed for the diverse environmental conditions in Bangladesh. We utilized Sentinel-1 and Sentinel-2 time-series data to identify transplantation and peak seasons and employed the multi-Otsu automatic thresholding approach to map rice during the peak season (April–May). We also compared the performance of a random forest (RF) classifier with the multi-Otsu approach using two different data combinations: D1, which utilizes data from the transplantation and peak seasons (D1 RF) and D2, which utilizes data from the transplantation to the harvest seasons (D2 RF). Our results demonstrated that the multi-Otsu approach achieved an overall classification accuracy (OCA) ranging from 61.18% to 94.43% across all crop zones. The D2 RF showed the highest mean OCA (92.15%) among the fourteen crop zones, followed by D1 RF (89.47%) and multi-Otsu (85.27%). Although the multi-Otsu approach had relatively lower OCA, it proved effective in accurately mapping rice areas prior to harvest, eliminating the need for training samples that can be challenging to obtain during the growing season. In-season rice area maps generated through this framework are crucial for timely decision-making regarding adaptive management in response to climatic stresses and forecasting area-wide productivity. The scalability of our framework across space and time makes it particularly suitable for addressing field data scarcity challenges in countries like Bangladesh and offers the potential for future operationalization.

Synthetic Aperture Radar Random Forest Boro Rice In-Season Maps CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SAR (RADAR) RICE FLOODING CLIMATE CHANGE

Seasonal climate forecasts (SCFs) based risk management strategies: A case study of rainfed rice cultivation in India

Nand Lal Kushwaha Paresh Shirsath Dipaka Ranjan Sena (2022, [Artículo])

FResampler1 Seasonal Climate Forecasts Decision Support System for Agrotechnology Transfer CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE DECISION SUPPORT SYSTEMS YIELDS RICE RISK MANAGEMENT