Abstract:
The impact of agricultural chemicals on the environment has come under close scrutiny in the country of South Africa, for that reason, we are investigating alternative and appropriate methods for nutrients management. The objective of the study was to assess infield spatial variability of soil nutrients in a uniformly managed corn field, and (ii) to recommend method that can potentially help corn (Zea mays L.) producers in Limpopo Province to enhance grain yield with optimal utilization of resources. The study was conducted at Syferkuil agricultural experimental farm (23o50’ S; 29 o40’ E) of the University of Limpopo, in the northern semi-arid region of South Africa. Prior to planting of corn on this uniformly managed 7 ha portion of a 1 705 ha farm, the field was mapped with Ag132 Trimble differentially corrected global positioning system (DGPS) equipped with Field Rover II® GIS mapping software. Land suitability assessment for corn was conducted before planting and the field was classified for suitability as S1 based on FAO guidelines for irrigated agriculture and South African Binomial System of Soil classification. Soils and corn leaf sample parameters, including N were collected and measured from geo-referenced locations on a 40 x 40 m grid. Nutrient distribution spatial maps were produced with Surfer software 8.0. There was a significant variability (P≤0.05) of soil nutrients and pH across the corn field. Corn grain yield ranged from 2.7 to 6.3 Mg ha-1. For a land suitability class of S1 under linear irrigation in a semi-arid environment, these grain yields were considered lower. This lower grain yields can be linked to variability of soil nutrients, and pH because the field was classified suitable according to FAO guidelines. This field, with its significant variability of nutrients and pH that resulted in lower grain yields, is potentially a good field for precision agriculture
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methods of nutrient management such site-specific management zones for environmental quality and economic efficiency.
Keywords: Maize, Small-scale farming, Soil nutrient management, and Spatial variability
