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Crop models are the representation of the crop growth interaction with the environment in an mathematical way where the information are predicted quantitatively. Different abiotic factors and biotic factors, factors within crop and environment, are equally used to test or assume the reality. The objective of the crop models remain in its ability to support in assistance in decision making. The earliest crop simulation models began in the 1960s where the mathematical relationships were developed between biomass growth and solar radiation. Publication in 1970s dealt biomass and its relation with the intercepted light. Crop models ARCWHEAT 1, CERES-WHEAT and the Dutch Models Simple and Universal Crop Growth Simulator were developed in 1980s and 1990s. Such models had the prime objective to compare the models with the experimental data to improve the cropping simulations.  Around 1990s, multiple crop models were developed for different crops such as Decision Support System for Agrotechnolo

NASA's EOSDIS stands for Earth Observing System Data and Information System. For this system, NASA's Distributed Active Archive Centers (DAACs) are scattered all around the USA. These centers work on processing, archiving, documenting, and distributing of the Earth Observation Data with the prime objecitve of the acessibility of the data in easiest possible way.  There are 12 DAACs each specializing in their unique functions. ~ Alaska Satellite Facility (ASF) DAAC: works on SAR Data, ~ Atmospheric Science Data Centre (ASDC): data relates to earth and the atomsphere, ~ Crustal Dynamics Data Information System (CDDIS): data relates with geodesy such as GNSS, ~ Global Hydrometerology Resource Center (GHRC) DAAC: focus on lightning, tropical cyclones, storm induced hazards, ~  Goddard Earth Sciences Data and Information Services Center (GES DISC): data relates with global climate such as atmospheric composition, precipitation, ~  Land Processes DAAC (LP DAAC): data relates with the

The difference between the actual yield and the potential yield are the main concepts used in the yield gap analysis. The potential yield or the theoretical yield is the yield that could have been achieved in the optimum conditions whose  level upto 70% (called attainable yield) is considered to be possible to be achieved from the best practices. The actual yield, usually estimated at the end of the growth period of the crops, are the real or the observed yield. All factors, biotic or abiotic and crop management factors, are involved to limit the potential yield (estimated by the crop models).  The objective of estimating the yield gap is to point the factors responsible for the difference between the yields, and for sure the other objective is the determination of the potential and the actual yields. The gap analysis methods involve ***calculation of the point ot regional based yield by the field experiments*** or ***by the simulation of the spatial and temporal surveys***.  Current r