Remote sensing-derived wheat crop yield-climate models were developed to highlight the impact of temperature variation during thermo-sensitive periods (anthesis and grain-filling; TSP) of wheat crop development. Specific questions addressed are: can the impact of temperature variation occurring during the TSP on wheat crop yield be detected using remote sensing data and what is the impact? Do c...

A supervised feature selection algorithm was applied to determine the most important features contributing to wheat grain yield. Four hundreds seventy two fields (as records) from different parts of Iran which were different in 21 characteristics (features) were selected for feature selection analysis. Selection of the wide range of features, including location, genotype, irrigation regime, fer...

The aim of the present study was to evaluate the response of grain yield, phosphorus (P) use efficiency (PUE, g yield g–1 P available) and related root traits of wheat and pea to different P availabilities in a high yielding environment (e.g.: yield higher than 10 Mg ha-1 for wheat). Two experiments were conducted in southern Chile. Treatments consisted of the combination of (i) two crops (spri...

In complex task domains, such as games, students may exceed their teachers. Such tasks afford diverse means to tradeoff one type of performance for another, combining task elements in novel ways to yield method variations and strategy discoveries that, if mastered, might produce large or small leaps in performance. For the researcher interested in the development of extreme expertise in the wil...

The goal of this study was to apply artificial neural networks to predict rain-fed wheat yield using meteorological data a few days to few months before harvesting. The climatic observation data used; were mean of daily minimum and maximum temperature, extreme of daily minimum and maximum temperature, sum of daily rainfall, number of rainy days, sum of daily sun hours, mean of daily wind speed,...

Regional crop yield prediction is a significant component of national food security assessment and food policy making. The crop growth model based on field scale is limited when it is extrapolated to regional scale to estimate crop yield due to the uncertainty of the input parameters. The data assimilation method which combines crop growth model and remotely sensed data has been proven to be th...

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implem...

Multiple regression approach has been used to forecast the crop production widely. This study undertaken evaluate performance of stepwise and Lasso (Least absolute shrinkage selection operator) technique in variable development wheat model for yield using weather data period 1984-2015, collected from IARI, New Delhi. Statistical parameters viz. R2, RMSE, MAPE were 0.81, 195.90 4.54 per cent res...

ABSTRACT- Crop rotation has many benefits for agro-ecosystems production. In order to evaluate two current rotation systems of wheat (Triticum aestivum L.) production in Kamalabad region of Fasa, an experiment was conducted during 2015-2016 growing season. The rotation systems were fallow-wheat and cotton (Gossypium spp.)-wheat. Research plots were arranged as a randomized complete block design...

Dynamic process-based crop simulation models are useful tool in predicting crop growth and yield in response to environmental and cultural factors but are constrained by lack of availability of the required large number of inputs when applied for regional studies. In this study we report (a) development of a prototype Crop Growth Monitoring System (CGMS) for wheat using WTGROWS simulation model...