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Geospatial information technology Land suitability assessment and Maizesoybean intercropping
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Land Suitability Assessment And Precision Farming Prospects For Irrigated Maize-Soybean Intercropping In Syferkuil Experimental Farm Using Geospatial Information Technology
Abstract
To maximize maize-soybean production, and ensure efficiency and sustainability in land use, there was a need to conduct an intensive qualitative land suitability assessment. The objective of the study was to digitize the University of Limpopo experimental farm map, produce expert knowledge based land suitability map, and quantify the suitable areas for
maize-soybean production under irrigation. The qualitative land suitability assessment approach study was conducted over five consecutive years from 1999 at Syferkuil experimental farm, Limpopo Province, South Africa. The evaluation of land in terms of the suitability classes was based on the method described in FAO guidelines for land evaluation for irrigated agriculture. A 1:10 000 corrected scale aerial photograph of the farm was georegistered using MapInfo Professional software, with a differential global positioning system coordinates. The soils on the farm were sampled and profiles classified using South African Binomial system of soil classification. The farm was divided into suitability classes of highly suitable (S1), suitable (S2), and unsuitable (N1), and permanently unsuitable (N2) classes. Maize-soybean suitability maps were produced based on soil characteristics and crop requirements. About 16.5% of the study area was found to be suitable for maize-soybean production, and 19.7% highly suitable. Even though there was a huge area suitable for maize-soybean production, the current land use indicated that most of it has already been used for Orchards production and horticultural research. The permanently unsuitable area (60.1 %) had shallow soils dominated by stones and plinthic horizon which had a combination of properties that restrict water movement and the penetration of roots. About 3.7%, which was classified as unsuitable was characterized by deep well weathered salt affected soils with a clay textured topsoil. The results of the study
serve as a good foundation for precision farming practices with favourable environmental conservation. Geospatial information technology and soil expert knowledge are potentially powerful tools to save the land from degradation through high-quality land suitability assessment for agricultural sustainability and resource management.
maize-soybean production under irrigation. The qualitative land suitability assessment approach study was conducted over five consecutive years from 1999 at Syferkuil experimental farm, Limpopo Province, South Africa. The evaluation of land in terms of the suitability classes was based on the method described in FAO guidelines for land evaluation for irrigated agriculture. A 1:10 000 corrected scale aerial photograph of the farm was georegistered using MapInfo Professional software, with a differential global positioning system coordinates. The soils on the farm were sampled and profiles classified using South African Binomial system of soil classification. The farm was divided into suitability classes of highly suitable (S1), suitable (S2), and unsuitable (N1), and permanently unsuitable (N2) classes. Maize-soybean suitability maps were produced based on soil characteristics and crop requirements. About 16.5% of the study area was found to be suitable for maize-soybean production, and 19.7% highly suitable. Even though there was a huge area suitable for maize-soybean production, the current land use indicated that most of it has already been used for Orchards production and horticultural research. The permanently unsuitable area (60.1 %) had shallow soils dominated by stones and plinthic horizon which had a combination of properties that restrict water movement and the penetration of roots. About 3.7%, which was classified as unsuitable was characterized by deep well weathered salt affected soils with a clay textured topsoil. The results of the study
serve as a good foundation for precision farming practices with favourable environmental conservation. Geospatial information technology and soil expert knowledge are potentially powerful tools to save the land from degradation through high-quality land suitability assessment for agricultural sustainability and resource management.
