El objetivo de esta revisión fue integrar los mecanismos por los cuales las plantas responden al estrés por calor a lo largo del continuo suelo-planta-atmósfera, desde una perspectiva agronómica. Esta revisión presenta las bases siológicas del estrés por calor, para lo cual se examinaron las temperaturas óptimas y los umbrales de estrés por calor en los cultivos, las metodologías para su estudio, y las respuestas moleculares, bioquímicas y siológicas de las plantas a altas temperaturas. Se describe el efecto de las altas temperaturas sobre la estructura y el metabolismo celular, la respiración y la aclimatación de la Q10, la estabilidad de las membranas, la acumulación de osmolitos compatibles, la producción de pigmentos y metabolitos secundarios, la producción de especies reactivas de oxígeno (ROS) y enzimas antioxidantes, la producción de proteínas de estrés, y el efecto sobre la fotosíntesis y la partición de asimilados. Además, se discuten los cambios hormonales que regulan la respuesta de las plantas en el campo, su señalización y la aclimatación al estrés térmico.

El objetivo de esta revisión fue describir las respuestas de las plantas y los mecanismos de tolerancia al estrés térmico, así como el uso de prácticas agronómicas para mitigar los efectos del estrés por alta temperatura en los cultivos. Se introduce el balance de energía de las hojas y los doseles como enlace entre la temperatura de las plantas y el aire. Se describen los efectos de las altas temperaturas sobre las relaciones hídricas, la fotosíntesis y la partición de los asimilados, y las respuestas morfológicas y fenológicas de algunos cultivos al estrés por calor. Se presenta la agronomía de respuesta para la prevención y remediación del estrés causado por calor, que se abordó desde el punto de vista del mejoramiento genético, del manejo agronómico, la farmacéutica y prácticas hortícolas variadas. Por último, se describen algunas prácticas agronómicas utilizadas para reducir los efectos negativos del estrés por alta temperatura en los cultivos, como el uso de coberturas del suelo, sombra natural o arti cial, y la aplicación de sustancias hormonales, protectoras y otros productos de la industria toquímica moderna.

Coffee is one of the most commonly traded agricultural commodities globally. It is important for the livelihoods of over 25 million families worldwide, but it is also a crop sensitive to climate change, which has forced producers to implement management practices with effects on carbon balance and water use efficiency (WUE) that are not well understood due to data scarcity. From this perspective, we propose crop canopy coupling to the atmosphere (Ώ) as an index of resilience and stability. We undertook an integrated observational approach for the scaling-up of measurements along the soil–plant–atmosphere continuum at different stages of the coffee crop phenological cycle. Additionally, we develop this perspective under pronounced climatic seasonality and variability, in order to assess carbon balance, WUE, and agroecosystem resilience in a sun-grown coffee field. Further, we devised a field layout that facilitates the measurement of intrinsic, instantaneous, and actual water use efficiency and the assessment of whether coffee fields differ in canopy structure, complexity, and agronomic management and whether they are carbon sources or sinks. Partitioning soil and canopy energy balances and fluxes in a sun-grown coffee field using eco-physiological techniques at the leaf and whole plant levels (i.e., sap flow and gas exchange), as proposed here, will allow the scaling-up to whole fields in the future. Eddy covariance was used to assess real-time surface fluxes of carbon, gross primary productivity (GPP), and evapotranspiration, as well as components of the energy balance and WUE. The preliminary results support the approach used here and suggested that coffee fields are CO₂ sinks throughout the year, especially during fruit development, and that the influence of seasonality drives the surface–atmosphere coupling, which is dominant prior to and during the first half of the rainy season. The estimated WUE showed consistency with independent studies in coffee crops and a marked seasonality driven by the features of the rainy season. A plan for the arborization of the coffee agroecosystem is suggested and the implications for WUE are described. Future comparison of sun- and shade-grown coffee fields and incorporation of other variables (i.e., crop coefficient-KC for different leaf area index (LAI) values) will allow us to better understand the factors controlling WUE in coffee agroecosystems.

Introduction. Simulation models are a tool to study crop behavior under different climatic and water conditions and agronomic management practices. Objective. To evaluate the AquaCrop model for estimating yield and water productivity in soybean var. CIGRAS-06. Materials and methods. The study was carried out at the Estación Experimental Agrícola Fabio Baudrit Moreno of the University of Costa Rica, in Alajuela, Costa Rica, from June 6 to October 23, 2018. The AquaCrop v. 7.1 model was used to simulate soybean crop development and yield. Simulated data on canopy cover, biomass production, and yield were compared with experimental data from a plot planted with soybean variety CIGRAS-06. Soil parameters measured in the field and generated with pedotransfer equations were used. Results. Predictions of yield, total biomass, and canopy cover were good (similarity values: d ≥ 0.97), but predictions of leaf coverage during the early crop cycle were susceptible to improvement. Differences between the two types of soil parameters used did not significantly affect the final simulation. Conclusions. AquaCrop successfully simulated soybean yield, biomass, and leaf coverage. Water productivity simulation was higher than values reported in the literature.

The application of leaf area index (LAI) in coffee crop management depends on the availability of methodologies for proper estimation. The objective of this study was to develop a methodology for the visual assessment of LAI in coffee fields and to establish a protocol for training, evaluation, and feedback for evaluators. Four rounds of LAI measurements were conducted using visual estimates, two instruments (LAI 2200-C and AccuPAR LP-80), and defoliation of coffee hedgerows in Poás, Costa Rica. In each round, five workers visually estimated the LAI values on two occasions separated by 15 days, and feedback reinforcement was provided to each worker at the end of each round. Visual assessments showed high repeatability and reproducibility and the estimates were adjusted to the linear regression model in most cases. Evaluators improved their capacity to visually assess the LAI throughout the rounds, as the value of R²increased consistently for most workers, with values as high as 0.87. Instrumentation evaluation of LAI produced R²values of 0.5-0.6, with significant underestimation bias. The performance of the different methods is discussed in the context of widely spaced hedgerows. The proposed visual methodology constitutes a statistically sound, rapid, simple, and reliable method for determining the LAI of coffee fields to aid in decision-making for crop management.