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In agriculture, the yield is a measurement of the amount of a crop grown, or product such as wool, meat or milk produced, per unit area of land. The seed ratio is another way of calculating yields. Cereal yield in tons per hectare and kilograms of nitrogenous fertilizer applied per hectare of cropland.
CropSyst, a multi-year multi-crop daily time-step crop simulation model developed by a team at Washington State University's Department of Biological Systems Engineering. [ 4 ] DSSAT , the Decision Support System for Agro-technology Transfer, is a multi-crop, multi-year crop simulation model which evolved from the IBSNAT (1982-1993) and ICASA ...
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
The van Genuchten–Gupta model is based on an inverted S-curve and applied to the response of crop yield to soil salinity. Examples of the application of the logistic S-curve to the response of crop yield (wheat) to both the soil salinity and depth to water table in the soil are shown in modeling crop response in agriculture.
Wheat yields in least developed countries since 1961. The steep rise in crop yields in the U.S. began in the 1940s. The percentage of growth was fastest in the early rapid growth stage. In developing countries maize yields are still rapidly rising. [6] Productivity is driven by changes in either agricultural technique or improvements in technology.
An example of a multiple disease/pest forecasting system is the EPIdemiology, PREdiction, and PREvention (EPIPRE) system developed in the Netherlands for winter wheat that focused on multiple pathogens. [6] USPEST.org graphs risks of various plants diseases based on weather forecasts with hourly resolution of leaf wetness.
Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.
The theoretical molar yield is 2.0 mol (the molar amount of the limiting compound, acetic acid). The molar yield of the product is calculated from its weight (132 g ÷ 88 g/mol = 1.5 mol). The % yield is calculated from the actual molar yield and the theoretical molar yield (1.5 mol ÷ 2.0 mol × 100% = 75%). [citation needed]