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Validation of crop weather models for crop assessment arid yield prediction under Tanzania conditions

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dc.creator Kihupi, N.
dc.creator Dihenga, B.O.
dc.creator Ntella, P. M.
dc.date 2017-12-18T06:15:13Z
dc.date 2017-12-18T06:15:13Z
dc.date 2000
dc.date.accessioned 2022-10-25T08:50:26Z
dc.date.available 2022-10-25T08:50:26Z
dc.identifier 0856 668X
dc.identifier https://www.suaire.sua.ac.tz/handle/123456789/1918
dc.identifier.uri http://hdl.handle.net/123456789/90214
dc.description Tanzania Journal of Agricultural Sciences 2000, Vol. 392) : 129-136
dc.description Information gatheringfor early warning and crop assessment in Tanzania is based on physical inspection of standing crop in sample jields. This process is subject to human error, inadequate and is also time consuming. Recent developments in computer simulation have paved the way for more efficient methods of analysing datafor purposes of early warning and crop assessment. Two such sch~mes based on soil water balance simulation, viz. IRSIS and CRPSM models were used in this study fo see how closeZv they could predict grain yieldsfor selected stations in Tanzania. Inputfor the models comprised of weather, crop and soil data collected from jive selected stations. Simulation results show that IRSIS model tends to over predict grain yields of maize, sorghum and wheat, a fact that could be attributed to the inadequacy of the model to accurately account for rainfall excess. On the other hand, the CRPSA1 model simulated results were not significantZv different (P>O. 05) from the actual grain yields ojmaize, sorghum,. wheat and beans. Although the agreement between actual and simulated yield data was good, it was observed that mean valuesfor predicted grain yields were consistently lower thanfor actual grain yields. This could be attributed to the use of approximate rather than location specific input parameters required by the CRPSM model. Locally calibrated input parameters in the CRPSM model could filrther improve the accuracy of the model and hence its ability to predict grain yields.
dc.format application/pdf
dc.language en
dc.subject Soil water balance
dc.subject Simulation model
dc.subject Crop assessment
dc.subject Yield prediction
dc.title Validation of crop weather models for crop assessment arid yield prediction under Tanzania conditions
dc.title Validation of Validation of crop weather models for crop assessment arid yield prediction under Tanzania conditions
dc.type Article


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