Seasonal effects on the correlation between electromagnetic-induction signals and the properties of two Trinidad soils. (187)
Keywords:Proximal soil sensing, electromagnetic-induction, precision agriculture, crop production, Caribbean
AbstractFAO (2012) estimates revealed that hunger has been reduced significantly more than was predicted in the last 20 years, and that, given renewed efforts; the millennium hunger target may be reached by 2015. Consequently, much of this renewed effort has taken the form of technological advances to increase agricultural yields. A technological approach in crop production that addresses variability of soils within crop fields is important for conservation of resources, and efficient use and application of inputs. This is pertinent in the resource poor small island Caribbean developing states. Proximal soil sensing using electro-magnetic induction (EMI) is one such technology that provides non-invasive, rapid, cost effective and spatially exhaustive measurements of soil properties. It maps within-field variability and allows for the optimum application of site-specific inputs for increased crop yield and decreased agro-chemical contamination to the environment. Using two distinct study sites (Godineau wetland and Centeno cocoa field), we investigated proximal sensing signal from EMI to determine its application for precision agriculture in the Caribbean. Our results show that the average EMI-based apparent electrical conductivity (ECa) signal was higher during the wet season (Godineau ECa= 2.18 dS/m, Centeno ECa= 0.13 dS/m) than in the dry season (Godineau ECa= 1.94 dS/m, Centeno ECa= 0.04 dS/m). The EMI signal was dominated by clay (r= 0.76, p value <0.001) and water content (r= 0.66, p value <0.001) in the Centeno field site, while ECe (r= 0.90, p value <0.001) dominated the EMI signal in the Godineau field site. The strong linear dependence of EMI signal on these key soil properties indicates a high potential for signal calibration to create soil management zones for the purpose of precision agriculture.