Search

Cocoa (Theobroma cacao L.) is one of the most important crops in Ecuador; however, its production is limited, among other factors, by the crop nutrition. The objective of this research was to determine the effect of the combined nitrogen, phosphorus and potassium fertilization on soil characteristics, growth traits and quality of shoots and fruits in cocoa. The experiment was carried out under a completely randomized design with factorial arrangement, with three factors, N, P and K, and two levels by factor (with and without fertilization), plus an absolute control without fertilization. The chemical characteristics of the soil, including pH, N, P, K, Ca and Mg content were evaluated. New shoots were also evaluated by measuring its number, length, leaf area, and growth rate. In the fruits, the weight, length and growth rate were measured. In shoots and fruits, quality traits including dry matter, fiber, ash, lipids and protein content were measured. Significant interactions of the applied nutrients were found, which increased the content of P and K, and decreased Ca and Mg of the soil. The N fertilization alone did not affect the growth of the shoots and foliar area. The interactions of the primary elements significantly increased the dry matter and fiber of the shoots, while the growth and quality of fruits were not modified., El cacao (Theobroma cacao L.) es uno de los cultivos más importantes de Ecuador; sin embargo, su producción está limitada, entre otros factores, por la nutrición. El objetivo de esta investigación fue determinar el efecto de la fertilización combinada de nitrógeno, fósforo y potasio sobre características del suelo, rasgos de crecimiento y calidad de brotes y frutos en cacao. El experimento se realizó bajo un diseño completamente al azar con arreglo factorial, con tres factores, N, P y K, y dos niveles por factor (con fertilización y sin fertilización), más un testigo absoluto sin fertilización. Se evaluaron las características químicas del suelo incluyendo el pH, y el contenido de N, P, K, Ca y Mg. También se evaluaron los brotes nuevos midiendo su número, longitud, área foliar y tasa de crecimiento. En los frutos, se determinó el peso, el largo y la tasa de crecimiento. En brotes y frutos, se evaluaron rasgos de calidad incluyendo materia seca, fibra, cenizas, grasas y proteínas. Se encontraron interacciones significativas entre los nutrientes aplicados, los cuales, incrementaron el contenido de P y K, y disminución del Ca y Mg del suelo. La fertilización con sólo N no afectó el crecimiento de los brotes y el área foliar. Las interacciones de los elementos primarios incrementaron significativamente la materia seca y fibra de los brotes, mientras que, el crecimiento y calidad de los frutos no se modificaron.

El Niño phenomenon is the leading mode of sea surface temperature interannual variability. It can affect weather patterns worldwide and therefore crop production. Crop models are useful tools for impact and predictability applications, allowing to obtain long time series of potential and attainable crop yield, unlike to available time series of observed crop yield for many countries. Using this tool, crop yield variability in a location of Iberia Peninsula (IP) has been previously studied, finding predictability from Pacific El Niño conditions. Nevertheless, the work has not been done for an extended area. The present work carries out an analysis of maize yield variability in IP for the whole 20th century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate‐dependent time series of crop yield for the whole region, and to use these yield to analyse the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non‐stationary on time, although the air temperature–yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The potential usefulness of this study is to apply the relationships found to improving crop forecasting in IP.

Seasonal climate prediction can potentially contribute to achieving a more resilient cropping system management. This can help alleviate food insecurity and the economical sustainability of farming at large. For this purpose, seasonal climate forecasts are used to generate crop forecasts. This study assesses two methods for linking seasonal climate forecasts with crop models to improve crop yield predictability in the Iberian Peninsula (IP). Crop models usually require daily weather data and therefore, we tested two methods to disaggregate seasonal climate forecasts into daily weather realizations: (1) a conditional stochastic weather generator (predictWTD) and (2) a simple forecast probability resampler (FResampler1).These methods were evaluated under three seasonal rainfall forecasts by analyzing the impacts on rainfed wheat yield and on irrigation requirements and yields of maize crop. In addition, we estimated the gross margins (€ ha− 1) and the production risks associated with contrasting scenarios of seasonal rainfall forecasts (dry and wet). Both methods provided comparable predictability and therefore, both seem feasible options for using seasonal forecasts to establish yield forecasts and irrigation requirements. The large impact of crop prices and of irrigation cost on gross margins for both crops suggests that using a combination of information on expected market prices and crop forecast based on seasonal climate forecasts can be an effective tool for farmer's decision-making, especially under dry forecast situation and/or in locations with low annual precipitation. These methods can help to quantify the benefits and risks from the seasonal weather forecasts to farmers in the IP. The anticipation of risks and the opportunity that skillful climate and crop forecast provide allows for windows of opportunity to prepare and pre-empt mitigating actions.

Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In Iberian Peninsula (IP), wheat yields are strongly dependent on the rainfall amount and its temporal distribution during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO), which has been partially related with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). Therefore, existence of some predictability of precipitation opens the possibility to reach some predictability of wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model, site specific calibrated and validated for the NE of IP, and several reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and to relate their variability with SST anomalies. The results show that the TNA and El Niño influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of the NAO, which exerts a positive (negative) influence on the minimum temperature and precipitation during winter and, thus, wheat yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981–2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño (La Niña) events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures and precipitation experienced by the crop in spring, during flowering and