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

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

A line follower robot implementation using Lego's Mindstorms Kit and Q-Learning

VICTOR RICARDO CRUZ ALVAREZ ENRIQUE HIDALGO PEÑA HECTOR GABRIEL ACOSTA MESA (2012, [Artículo])

Un problema común al trabajar con robots móviles es que la fase de programación puede ser un proceso largo, costoso y difícil para los programadores. Los Algoritmos de Aprendizaje por Refuerzo ofrecen uno de los marcos de trabajo más generales en el ámbito de aprendizaje de máquina. Este trabajo presenta un enfoque usando el algoritmo de Q-Learning en un robot Lego para que aprenda "por sí mismo" a seguir una línea negra dibujada en una superficie blanca. El entorno de programación utilizado en este trabajo es Matlab.

INGENIERÍA Y TECNOLOGÍA Algoritmos de aprendizaje reforzado Q-learning (Algoritmo de aprendizaje reforzado) Lego Mindstorms (Robótica) Matlab Reinforcement learning algorithms Q-Learning (Reinforcement learning algorithm) Lego Mindstorms (Robotics) Matlab

Clonal diploid and autopolyploid breeding strategies to harness heterosis: insights from stochastic simulation

Marlee Labroo Jeffrey Endelman Dorcus Gemenet Christian Werner Robert Gaynor GIOVANNY COVARRUBIAS-PAZARAN (2023, [Artículo])

Reciprocal Recurrent Selection Clonal Diploids CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DIPLOIDY BREEDING HETEROSIS STOCHASTIC 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

Modeling the growth, yield and N dynamics of wheat for decoding the tillage and nitrogen nexus in 8-years long-term conservation agriculture based maize-wheat system

C.M. Parihar Dipaka Ranjan Sena Prakash Chand Ghasal Shankar Lal Jat Yashpal Singh Saharawat Mahesh Gathala Upendra Singh Hari Sankar Nayak (2024, [Artículo])

Context: Agricultural field experiments are costly and time-consuming, and their site-specific nature limits their ability to capture spatial and temporal variability. This hinders the transfer of crop management information across different locations, impeding effective agricultural decision-making. Further, accurate estimates of the benefits and risks of alternative crop and nutrient management options are crucial for effective decision-making in agriculture. Objective: The objective of this study was to utilize the Crop Environment Resource Synthesis CERES-Wheat model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based wheat system. The study aimed to calibrate the model using data from a field experiment conducted during the 2019-20-2020-21 growing seasons and evaluation it with independent data from the year 2021–22. Method: Crop simulation models, such as the Crop Environment Resource Synthesis CERES-Wheat (DSSAT v 4.8), may provide valuable insights into crop growth and nitrogen dynamics, enabling decision makers to understand and manage production risk more effectively. Therefore, the present study employed the CERES-Wheat (DSSAT v 4.8) model and calibrated it using field data, including plant phenological phases, leaf area index, aboveground biomass, and grain yield from the 2019-20-2020-21 growing seasons. An independent dataset from the year 2021–22 was used for model evaluation. The model was used to investigate the relationship between growing degree days (GDD), temperature, nitrate and ammonical concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on wheat yields. The experimental site is situated at ICAR-Indian Agricultural Research Institute (IARI), New Delhi, representing Indian Trans-Gangetic Plains Zone (28o 40’N latitude, 77o 11’E longitude and an altitude of 228 m above sea level). The treatments consist of four nitrogen management options, viz., N0 (zero nitrogen), N150 (150 kg N ha−1 through urea), GS (Green seeker based urea application) and USG (urea super granules @150 kg N ha−1) in two contrasting tillage systems, i.e., CA-based zero tillage (ZT) and conventional tillage (CT). Result: The outcomes exhibited favorable agreement between the model’s simulations and the observed data for crop phenology (With less than 2 days variation in 50% onset of flowering), grain and biomass yield (Root mean square error; RMSE 336 kg ha−1 and 649 kg ha−1, respectively), and leaf area index (LAI) (RMSE 0.28 & normalized RMSE; nRMSE 6.69%). The model effectively captured the nitrate-N (NO3−-N) dynamics in the soil profile, exhibiting a remarkable concordance with observed data, as evident from its low RMSE = 12.39 kg ha−1 and nRMSE = 13.69%. Moreover, as it successfully simulated the N balance in the production system, the nitrate leaching and ammonia volatilization pattern as described by the model are highly useful to understand these critical phenomena under both conventional tillage (CT) and CA-based Zero Tillage (ZT) treatments. Conclusion: The study concludes that the DSSAT-CERES-Wheat model has significant potential to assess the impacts of tillage and nitrogen management practices on crop growth, yield, and soil nitrogen dynamics in the western Indo-Gangetic Plains (IGP) region. By providing reliable forecasts within the growing season, this modeling approach can facilitate better planning and more efficient resource management. Future implications: The successful implementation of the DSSAT-CERES-Wheat model in this study highlights its applicability in assessing crop performance and soil dynamics. Future research should focus on expanding the model’s capabilities by reducing its sensitivity to initial soil nitrogen levels to refine its predictions further. Moreover, the model’s integration with decision support systems and real-time data can enhance its usefulness in aiding agricultural decision-making and supporting sustainable crop management practices.

Nitrogen Dynamics Mechanistic Crop Growth Models Crop Simulation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN CONSERVATION AGRICULTURE WHEAT MAIZE CROP GROWTH RATE SIMULATION MODELS

Towards gender-inclusive innovation: Assessing local conditions for agricultural targeting

Diana E. Lopez Romain Frelat Lone Badstue (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE CLIMATE FEMALES GENDER HUMANS GENDER EQUALITY

Monitoreo con drones en gráficas con viento dinámico

Jovanni Manuel López Elisea (2024, [Tesis de maestría])

108 páginas. Maestría en Optimización.

Dada una gráfica completa no dirigida, se desea recorrer un subconjunto de sus aristas usando una flotilla de drones. Los drones tienen baterías limitadas que pueden recargarse al regresar a la base y, en principio, el tiempo para recorrer una arista está en función de la distancia entre sus vértices. Sin embargo, ante la presencia de viento el tiempo de recorrer una arista puede depender del sentido en el que se haga. La dificultad del problema aumenta si además la intensidad del viento puede variar de un instante a otro. En esta tesis se aborda el problema anteriormente descrito para el caso particular en el que los vértices son puntos en el plano, el impacto del viento en los tiempos de recorrido de las aristas está relativamente acotado y el subconjunto de las aristas a recorrer inducen un árbol que abarca todos los vértices excepto la base de los drones. Dado que los drones operan simultáneamente y pueden recorrer distintas partes de la gráfica de manera independiente, se desea minimizar el tiempo que emplea el dron con el recorrido más tardado. Esta tesis presenta un modelo matemático para resolver el problema de manera exacta, así como tres heurísticas diferentes para obtener buenas soluciones factibles. La primera de estas heurísticas transforma una solución sin viento y sin batería en una solución con viento y batería. La segunda heurística es un algoritmo glotón sin comunicación entre los drones y la última heurística también es un algoritmo glotón, pero con comunicación entre los drones. Aunque el problema abordado resulta ser lo suficientemente difícil como para que su resolución exacta sea inviable en la práctica, las heurísticas diseñadas son fáciles de implementar y obtuvieron resultados razonables en un tiempo corto de cómputo.

Drone aircraft--Control systems. Drone aircraft--Mathematical models. Mathematical optimization. Heuristic programming. Dynamical systems. Graph theory. Micro vehículos aéreos. Optimización matemática. Programación heurística. Teoría de grafos. TL589.4 CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA MATEMÁTICAS INVESTIGACIÓN OPERATIVA DISTRIBUCIÓN Y TRANSPORTE

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