Point placement of late vegetative stage nitrogen splits increase the productivity, N-use efficiency and profitability of tropical maize under decade long conservation agriculture

Hari Sankar Nayak C.M. Parihar Shankar Lal Jat ML JAT Ahmed Abdallah (2022, [Artículo])

Non-Linear Growth Model Nitrogen Remobilization Right Placement Precision Nitrogen Management CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GROWTH MODELS NITROGEN NUTRIENT MANAGEMENT

Alternative cropping and feeding options to enhance sustainability of mixed crop-livestock farms in Bangladesh

Timothy Joseph Krupnik Jeroen Groot (2024, [Artículo])

We investigated alternative cropping and feeding options for large (>10 cows), medium (5–10 cows) and small (≤4 cows) mixed crop – livestock farm types, to enhance economic and environmental performance in Jhenaidha and Meherpur districts – locations with increasing dairy production – in south western Bangladesh. Following focus group discussions with farmers on constraints and opportunities, we collected baseline data from one representative farm from each farm size class per district (six in total) to parameterize the whole-farm model FarmDESIGN. The six modelled farms were subjected to Pareto-based multi-objective (differential evolution algorithm) optimization to generate alternative dairy farm and fodder configurations. The objectives were to maximize farm profit, soil organic matter balance, and feed self-reliance, in addition to minimizing feed costs and soil nitrogen losses as indicators of sustainability. The cropped areas of the six baseline farms ranged from 0.6 to 4.0 ha and milk production per cow was between 1,640 and 3,560 kg year−1. Feed self-reliance was low (17%–57%) and soil N losses were high (74–342 kg ha−1 year−1). Subsequent trade-off analysis showed that increasing profit and soil organic matter balance was associated with higher risks of N losses. However, we found opportunities to improve economic and environmental performance simultaneously. Feed self-reliance could be increased by intensifying cropping and substituting fallow periods with appropriate fodder crops. For the farm type with the largest opportunity space and room to manoeuvre, we identified four strategies. Three strategies could be economically and environmentally benign, showing different opportunities for farm development with locally available resources.

Ruminant Feed Pareto-Based Optimization Farm Bioeconomic Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUMINANT FEEDING BIOECONOMIC MODELS MIXED CROPPING FARMS LIVESTOCK

Algorithmic differentiation of linear mixed models with variance-covariance structures

Fernando Henrique Toledo Jose Crossa Juan Burgueño Keith Gardner Rosa Angela Pacheco Gil (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MATHEMATICAL MODELS ALGORITHMS LINEAR MODELS

Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance

Roberto Fritsche-Neto Marlee Labroo (2024, [Artículo])

Genomic Prediction Reciprocal Recurrent Selection Heterotic Pools CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA STOCHASTIC MODELS RICE HYBRIDS GENETIC IMPROVEMENT GENETIC GAIN BREEDING PROGRAMMES

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Optimizing nitrogen fertilizer and planting density levels for maize production under current climate conditions in Northwest Ethiopian midlands

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

This study determined the most effective plating density (PD) and nitrogen (N) fertilizer rate for well-adapted BH540 medium-maturing maize cultivars for current climate condition in north west Ethiopia midlands. The Decision Support System for Agrotechnology Transfer (DSSAT)-Crop Environment Resource Synthesis (CERES)-Maize model has been utilized to determine the appropriate PD and N-fertilizer rate. An experimental study of PD (55,555, 62500, and 76,900 plants ha−1) and N (138, 207, and 276 kg N ha−1) levels was conducted for 3 years at 4 distinct sites. The DSSAT-CERES-Maize model was calibrated using climate data from 1987 to 2018, physicochemical soil profiling data (wilting point, field capacity, saturation, saturated hydraulic conductivity, root growth factor, bulk density, soil texture, organic carbon, total nitrogen; and soil pH), and agronomic management data from the experiment. After calibration, the DSSAT-CERES-Maize model was able to simulate the phenology and growth parameters of maize in the evaluation data set. The results from analysis of variance revealed that the maximum observed and simulated grain yield, biomass, and leaf area index were recorded from 276 kg N ha−1 and 76,900 plants ha−1 for the BH540 maize variety under the current climate condition. The application of 76,900 plants ha−1 combined with 276 kg N ha−1 significantly increased observed and simulated yield by 25% and 15%, respectively, compared with recommendation. Finally, future research on different N and PD levels in various agroecological zones with different varieties of mature maize types could be conducted for the current and future climate periods.

Maize Model Planting Density CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE MODELS SPACING NITROGEN FERTILIZERS YIELDS

Expanding the WOFOST crop model to explore options for sustainable nitrogen management: A study for winter wheat in the Netherlands

João Vasco Silva Pytrik Reidsma (2024, [Artículo])

Nitrogen (N) management is essential to ensure crop growth and to balance production, economic, and environmental objectives from farm to regional levels. This study aimed to extend the WOFOST crop model with N limited production and use the model to explore options for sustainable N management for winter wheat in the Netherlands. The extensions consisted of the simulation of crop and soil N processes, stress responses to N deficiencies, and the maximum gross CO2 assimilation rate being computed from the leaf N concentration. A new soil N module, abbreviated as SNOMIN (Soil Nitrogen for Organic and Mineral Nitrogen module) was developed. The model was calibrated and evaluated against field data. The model reproduced the measured grain dry matter in all treatments in both the calibration and evaluation data sets with a RMSE of 1.2 Mg ha−1 and the measured aboveground N uptake with a RMSE of 39 kg N ha−1. Subsequently, the model was applied in a scenario analysis exploring different pathways for sustainable N use on farmers' wheat fields in the Netherlands. Farmers' reported yield and N fertilization management practices were obtained for 141 fields in Flevoland between 2015 and 2017, representing the baseline. Actual N input and N output (amount of N in grains at harvest) were estimated for each field from these data. Water and N-limited yields and N outputs were simulated for these fields to estimate the maximum attainable yield and N output under the reported N management. The investigated scenarios included (1) closing efficiency yield gaps, (2) adjusting N input to the minimum level possible without incurring yield losses, and (3) achieving 90% of the simulated water-limited yield. Scenarios 2 and 3 were devised to allow for soil N mining (2a and 3a) and to not allow for soil N mining (2b and 3b). The results of the scenario analysis show that the largest N surplus reductions without soil N mining, relative to the baseline, can be obtained in scenario 1, with an average of 75%. Accepting negative N surpluses (while maintaining yield) would allow maximum N input reductions of 84 kg N ha−1 (39%) on average (scenario 2a). However, the adjustment in N input for these pathways, and the resulting N surplus, varied strongly across fields, with some fields requiring greater N input than used by farmers.

Crop Growth Models WOFOST CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROPS NITROGEN-USE EFFICIENCY WINTER WHEAT SOIL WATER

Contracting in teams with network technologies

Giselle Labrador Badía (2020, [Tesis de maestría])

We develop a contracting model between the owner and the workers of a firm when production depends directly on a network of synergies among workers. We aim to answer how the owner of the firm uses the network structure to maximize profits. With this purpose, we analyze two contracting regimes: single wage and perfect discrimination. We find that individual network characteristics, as well as aggregate measures, affect profits and salaries. We also study the parameters for wich the incentives to discriminate and to account for the network structure are significant.

Externalities (Economics) -- Mathematical models. CIENCIAS SOCIALES CIENCIAS SOCIALES

Esquema de objetivos de inflación, compromiso, comunicación y credibilidad: ¿por qué el Banco de México muestra dificultad para cumplir con su objetivo puntual de inflación del 3%?

César Geovanny Ángeles Sánchez (2021, [Tesis de maestría])

El presente documento realiza tres ejercicios empíricos para los temas de compromiso, comunicación y credibilidad del Banco de México. En última instancia, se busca responder al porqué, durante la implementación del esquema de objetivos de inflación (2003-2020), el Banco de México ha mostrado dificultad para cumplir con su objetivo puntual de inflación del 3%. Ya que, como lo indican los promedios de las series de tiempo, durante este periodo los niveles de la inflación y de las distintas expectativas de inflación se han ubicado por encima de la meta. Si bien los resultados confirman la credibilidad que tiene el Banco de México con el mantener una inflación baja y estable; siguiendo una regla de Taylor, se encuentra evidencia que, durante el periodo 2003-2020, el Banco de México ha sido tolerante con brechas positivas en el nivel de inflación (acentuándose, de manera significativa, durante el 2015-2020). En otras palabras, los resultados del documento sugieren que, durante la implementación del esquema de objetivos de inflación, el Banco de México ha ajustado su tasa de interés en busca de un nivel de inflación que se ubique en el intervalo que va del 3% + 1 punto porcentual pero no en la meta del 3%. Asimismo, resulta interesante que, del 2007 al 2020, cambios en la tasa de interés hayan sido motivados por brechas en el nivel de producción (tal como si el banco central mantuviese un mandato dual). Finalmente, a través de la construcción de un índice de comunicación que emplea los anuncios de política monetaria, se encuentra evidencia que la comunicación del Banco de México influye en las expectativas de inflación implicitas en instrumentos financieros y permite anticipar futuros movimientos en la tasa de interés (“forward guidance”).

Banco de México (1925- ) -- Effect of inflation (Finance) on -- Econometric models. Banks and banking, Central -- Mexico -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES

Informalidad laboral municipal en México: análisis de sus causas desde un enfoque espacial

Edison Smith Fonseca Correcha (2020, [Tesis de maestría])

Para el año 2019, más de 30 millones de trabajadores mexicanos estuvieron ejerciendo sus labores en condiciones informales, es decir, excluidos de la seguridad social. Para mitigar este problema público, las políticas públicas en diferentes niveles de gobierno han estado enfocadas principalmente en atacar dos de las posibles causas del problema: los incentivos económicos y la formación de la fuerza laboral. Con el fin de hacer una contribución sobre la relevancia de otras causas en la informalidad laboral, esta investigación presenta evidencia sobre el efecto que tienen los factores espaciales, sociodemográficos, de incentivos económicos y de estructura empresarial sobre la informalidad laboral municipal. Con base en los hallazgos, las recomendaciones de política pública se enfocan en aprovechar algunas estrategias de desarrollo económico regional para generar la conformación de aglomeraciones municipales de empleo formal.

Informal sector (Economics) -- Effect of space on -- Mexico -- Econometric models. Informal sector (Economics) -- Effect of demography on -- Mexico -- Econometric models. Informal sector (Economics) -- Effect of economic aspects on -- Mexico -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES