Trade-offs in the genetic control of functional and nutritional quality traits in UK winter wheat

Nick Fradgley Keith Gardner Stéphanie M. Swarbreck Alison Bentley (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT GENETIC CONTROL NUTRITIVE VALUE QUANTITATIVE TRAIT LOCI

Estudio experimental con modelos físicos para generación de criterios de peligro por inundación y para caracterización de efectos del arrastre de sólidos sobre estructuras de cruce en ríos de zonas urbanas : parte 2 : estudio experimental para la caracterización del efecto del arrastre de sólidos en flujos a superficie libre con estructuras de cruce en ríos de zonas urbanas

XOCHITL PEÑALOZA RUEDA José Alfredo González Verdugo MARIA JOSELINA CLEMENCIA ESPINOZA AYALA (2015, [Documento de trabajo])

Dada la necesidad de proponer estrategias para evitar inundaciones causadas por la construcción de estructuras de cruce, se llevó a cabo un estudio experimental con modelos físicos para la caracterización del efecto del arrastre de sólidos (madera) en flujos a superficie libre, con estructuras de cruce en zonas urbanas. Esto con el objetivo de generar una metodología para establecer las propiedades de las estructuras de cruce ante el efecto de arrastre de sólidos, y así garantizar el correcto funcionamiento hidráulico. Específicamente, para determinar el claro o separación mínima entre pilas, con el cual se evite o reduzca la posibilidad de acumulación de material leñoso entre las mismas.

Ríos Control de inundaciones Zonas urbanas INGENIERÍA Y TECNOLOGÍA

Chapter 20. Insect resistance

Wuletaw Tadesse Marion Harris Leonardo Abdiel Crespo Herrera Zakaria Kehel (2022, [Capítulo de libro])

Gene Introgression Insect Resistance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING GENETICS INSECT CONTROL

Investigation of the impact of Arundo donax in Mexico and evaluation of candidate biological control agents

MARICELA MARTINEZ JIMENEZ (2018, [Documento de trabajo])

The arrival and spread of non-native species into new environments is a serious threat to ecosystems, that is the case of Arundo donax L. (Poaceae Arundinoideae), a perennial grass native to the western Mediterranean to India. Arundo donax was introduced to North America from the Iberian Peninsula within the last 500 years and is now a widespread and invasive weed in the Rio Grande Basin, (the border line between Mexico and the United States) and in almost all the basins in Mexico. This plant is extremely invasive and damaging, affecting especially water supplies. In many parts of Mexico, precipitation and inflows periodically decline and result in a drought, for this reason water conservation programs have to consider the inclusion of control programs of this plant. In Mexico, A. donax is managed by cutting the stems, which is ineffective because of prolific asexual reproduction from an extensive rhizome system, and by using herbicides. However, evidence of serious harm to health and the environment of chemical control indicates that the herbicides are not desirable for it use in shorelines of water bodies where Arundo's infestations are established.

Especies invasoras Impacto ambiental Control de malezas Control biológico BIOLOGÍA Y QUÍMICA

Impacto del cambio climático en la calidad del agua y propuesta de políticas públicas a la dependencia competente

NORMA RAMIREZ SALINAS Camilo Vázquez Bustos (2012, [Documento de trabajo])

Este estudio busca un seguimiento al trabajo hasta hoy realizado en el Instituto Mexicano de Tecnología del Agua con respecto a la relación cambio climático y calidad del agua, con el fin de presentar propuestas de políticas públicas a las autoridades competentes con base a los estudios efectuados en el IMTA en los últimos cinco años.

Control de calidad del agua Cambio climático Impacto ambiental Política ambiental Política pública INGENIERÍA Y TECNOLOGÍA

Weed management and tillage effect on rainfed maize production in three agro-ecologies in Mexico

Simon Fonteyne Abel Jaime Leal González Rausel Ovando Ravi Gopal Singh Nele Verhulst (2022, [Artículo])

Maize (Zea mays L.) is grown in a wide range of agro-ecological environments and production systems across Mexico. Weeds are a major constraint on maize grain yield, but knowledge regarding the best weed management methods is lacking. In many production systems, reducing tillage could lessen land degradation and production costs, but changes in tillage might require changes in weed management. This study evaluated weed dynamics and rainfed maize yield under five weed management treatments (pre-emergence herbicide, post-emergence herbicide, pre-emergence + post-emergence herbicide, manual weed control, and no control) and three tillage methods (conventional, minimum and zero tillage) in three agro-ecologically distinct regions of the state of Oaxaca, Mexico, in 2016 and 2017. In the temperate Mixteca region, weeds reduced maize grain yields by as much as 92% and the long-growing season required post-emergence weed control, which gave significantly higher yields. In the hot, humid Papaloapan region, weeds reduced maize yields up to 63% and pre-emergence weed control resulted in significantly higher yields than treatments with post-emergence control only. In the semi-arid Valles Centrales region, weeds reduced maize yields by as much as 65%, but weed management was not always effective in increasing maize yield or net profitability. The most effective weed management treatments tended to be similar for the three tillage systems at each site, although weed pressure and the potential yield reduction by weeds tended to be higher under zero tillage than minimum or conventional tillage. No single best option for weed management was found across sites or tillage systems. More research, in which non-chemical methods should not be overlooked, is thus needed to determine the most effective weed management methods for the diverse maize production systems across Mexico.

Corn Integrated Weed Management Manual Weed Control CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE WEED CONTROL MINIMUM TILLAGE ZERO TILLAGE

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

Forest proximity positively affects natural enemy mediated control of fall armyworm in Southern Africa

Frédéric Baudron Terence Sunderland (2022, [Artículo])

Insectivorous Birds Bat Predation Maize Cultivation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FALL ARMYWORMS BIOLOGICAL PEST CONTROL INSECTIVOROUS ANIMALS MAIZE PREDATOR PREY RELATIONS

Control de sistemas usando aprendizaje de máquina

Systems control using machine learning

Jesús Martín Miguel Martínez (2023, [Tesis de maestría])

El aprendizaje por refuerzo es un paradigma del aprendizaje de máquina con un amplio desarrollo y una creciente demanda en aplicaciones que involucran toma de decisiones y control. Es un paradigma que permite el diseño de controladores que no dependen directamente del modelo que describe la dinámica del sistema. Esto es importante ya que en aplicaciones reales es frecuente que no se disponga de dichos modelos de manera precisa. Esta tesis tiene como objetivo implementar un controlador óptimo en tiempo discreto libre de modelo. La metodología elegida se basa en algoritmos de aprendizaje por refuerzo, enfocados en sistemas con espacios de estado y acción continuos a través de modelos discretos. Se utiliza el concepto de función de valor (Q-función y función V ) y la ecuación de Bellman para resolver el problema del regulador cuadrático lineal para un sistema mecánico masa-resorte-amortiguador, en casos donde se tiene conocimiento parcial y desconocimiento total del modelo. Para ambos casos las funciones de valor son definidas explícitamente por la estructura de un aproximador paramétrico, donde el vector de pesos del aproximador es sintonizado a través de un proceso iterativo de estimación de parámetros. Cuando se tiene conocimiento parcial de la dinámica se usa el método de aprendizaje por diferencias temporales en un entrenamiento episódico, que utiliza el esquema de mínimos cuadrados con mínimos cuadrados recursivos en la sintonización del crítico y descenso del gradiente en la sintonización del actor, el mejor resultado para este esquema es usando el algoritmo de iteración de valor para la solución de la ecuación de Bellman, con un resultado significativo en términos de precisión en comparación a los valores óptimos (función DLQR). Cuando se tiene desconocimiento de la dinámica se usa el algoritmo Q-learning en entrenamiento continuo, con el esquema de mínimos cuadrados con mínimos cuadrados recursivos y el esquema de mínimos cuadrados con descenso del gradiente. Ambos esquemas usan el algoritmo de iteración de política para la solución de la ecuación de Bellman, y se obtienen resultados de aproximadamente 0.001 en la medición del error cuadrático medio. Se realiza una prueba de adaptabilidad considerando variaciones que puedan suceder en los parámetros de la planta, siendo el esquema de mínimos cuadrados con mínimos cuadrados recursivos el que tiene los mejores resultados, reduciendo significativamente ...

Reinforcement learning is a machine learning paradigm with extensive development and growing demand in decision-making and control applications. This technique allows the design of controllers that do not directly depend on the model describing the system dynamics. It is useful in real-world applications, where accurate models are often unavailable. The objective of this work is to implement a modelfree discrete-time optimal controller. Through discrete models, we implemented reinforcement learning algorithms focused on systems with continuous state and action spaces. The concepts of value-function, Q-function, V -function, and the Bellman equation are employed to solve the linear quadratic regulator problem for a mass-spring-damper system in a partially known and utterly unknown model. For both cases, the value functions are explicitly defined by a parametric approximator’s structure, where the weight vector is tuned through an iterative parameter estimation process. When partial knowledge of the dynamics is available, the temporal difference learning method is used under episodic training, utilizing the least squares with a recursive least squares scheme for tuning the critic and gradient descent for the actor´s tuning. The best result for this scheme is achieved using the value iteration algorithm for solving the Bellman equation, yielding significant improvements in approximating the optimal values (DLQR function). When the dynamics are entirely unknown, the Q-learning algorithm is employed in continuous training, employing the least squares with recursive least squares and the gradient descent schemes. Both schemes use the policy iteration algorithm to solve the Bellman equation, and the system’s response using the obtained values was compared to the one using the theoretical optimal values, yielding approximately zero mean squared error between them. An adaptability test is conducted considering variations that may occur in plant parameters, with the least squares with recursive least squares scheme yielding the best results, significantly reducing the number of iterations required for convergence to optimal values.

aprendizaje por refuerzo, control óptimo, control adaptativo, sistemas mecánicos, libre de modelo, dinámica totalmente desconocida, aproximación paramétrica, Q-learning, iteración de política reinforcement learning, optimal control, adaptive control, mechanical systems, modelfree, utterly unknown dynamics, parametric approximation, Q-learning, policy iteration INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES INTELIGENCIA ARTIFICIAL INTELIGENCIA ARTIFICIAL

EFECTO DE Trichoderma SPP. SOBRE LA ROYA BLANCA DEL CRISANTEMO INDUCIDA POR Puccinia horiana

ROMULO GARCIA VELASCO (2022, [Artículo])

En México, el Estado de México constituye el principal productor de crisantemo. La roya blanca causada por el hongo Puccinia horiana Henn se considera como una de las enfermedades más devastadoras en el cultivo. El objetivo del presente estudio fue determinar el efecto de Trichoderma barbatum Samuels y Trichoderma asperellum Samuels, Lieckfeldt & Nirenberg en el control de la roya blanca en crisantemo. Se demostró de forma exitosa el efecto biocontrolador de las cepas nativas, así como su efecto benéfico en el crecimiento de las plantas de crisantemo. Ambas cepas resultaron promisorias para el control de la roya blanca en el cultivo de crisantemo.

The State of Mexico is the main producer of chrysanthemums in Mexico. White rust caused by

the fungus Puccinia horiana Henn is considered one of the most devastating diseases in crops. The objective of this work was to determine the effect of Trichoderma barbatum Samuels and

Trichoderma asperellum Samuels, Lieckfeldt & Nirenberg in the control of white rust in chrysanthemum. The biocontrol effect of native strains was successfully demonstrated, as well as its beneficial effect in the growth of chrysanthemum plants. Both strains proved promising for the control of white rust in chrysanthemum crops.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS control biológico, enfermedades, patógeno, plantas ornamentales