Prediction of soil moisture-holding capacity with support vector machines in dry subhumid tropics

Kaingo, Jacob; Tumbo, Siza D.; Kihupi, Nganga I.; Mbilinyi, Boniface P.

dc.creator	Kaingo, Jacob
dc.creator	Tumbo, Siza D.
dc.creator	Kihupi, Nganga I.
dc.creator	Mbilinyi, Boniface P.
dc.date	2022-05-12T11:18:13Z
dc.date	2022-05-12T11:18:13Z
dc.date	2018-07
dc.date.accessioned	2022-10-25T08:51:46Z
dc.date.available	2022-10-25T08:51:46Z
dc.identifier	1687-7675
dc.identifier	https://www.suaire.sua.ac.tz/handle/123456789/4113
dc.identifier.uri	http://hdl.handle.net/123456789/91753
dc.description	Soil moisture-holding capacity data are required in modelling agrohydrological functions of dry subhumid environments for sustainable crop yields. However, they are hardly sufficient and costly to measure. Mathematical models called pedotransfer functions (PTFs) that use soil physicochemical properties as inputs to estimate soil moisture-holding capacity are an attractive alternative but limited by specificity to pedoenvironments and regression methods. This study explored the support vector machines method in the development of PTFs (SVR-PTFs) for dry subhumid tropics. Comparison with the multiple linear regression method (MLR-PTFs) was done using a soil dataset containing 296 samples of measured moisture content and soil physicochemical properties. Developed SVR-PTFs have a tendency to underestimate moisture content with the root-mean-square error between 0.037 and 0.042 cm 3 ·cm −3 and coefficients of determination (R 2 ) between 56.2% and 67.9%. The SVR-PTFs were marginally better than MLR-PTFs and had better accuracy than published SVR-PTFs. It is held that the adoption of the linear kernel in the calibration process of SVR-PTFs influenced their performance.
dc.format	application/pdf
dc.language	en
dc.publisher	Hindawi
dc.subject	Descriptive Statistics of Soil Datasets
dc.subject	Soil moisture
dc.subject	Crop yields in dry subhumid zones
dc.title	Prediction of soil moisture-holding capacity with support vector machines in dry subhumid tropics
dc.type	Article