Prediction of paddy productivity using apparent soil electrical conductivity model.

Inexpensive, rapid and accurate methods for spatially measuring within-field soil differences associated with crop productivity are needed to improve planning for site-specific management and enhance crop yield. This study was conducted at MARDI Seberang Perai between 2002 and 2004 to investigate the application of apparent soil electrical conductivity (soil ECa) model derived from log-normal peak function using boundary line analysis. Grain yield data were obtained from crop cutting test and ECa measurements by using Veris 3100 cart equipped with data logger and a differential global positioning system. Significant relationships between potential yield and ECa were found in all three crop-season studies in the form of log-normal peak function. When comparing between predicted potential yields (Ypo) and observed yields (Yob), farm areas can be delineated into four different management zones and allows for discriminate management practices. The ECa model could correctly indicate that significant higher yield can be obtained from areas with high predicted potential yield through more intensive management practices. Accurate yield prediction couple with site-specific practices could result in less wastage of applied inputs, less pollution, lower input costs and most important, higher return. *Mechanisation and Automation Research Centre, MARDI Seberang Perai, P.O. Box 203, 13200 Kepala Batas, Pulau Pinang, Malaysia **Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia ***Mechanisation and Automation Research Centre, MARDI Headquarters, Serdang, P.O. Box 12301, 50774 Kuala Lumpur, Malaysia Authors’ full names: Chan Chee Sheng, Mohd Amin Mohd Soom, Lee Teang Shui and Mohammud Che Husain E-mail: cschan@mardi.gov.my ©Malaysian Agricultural Research and Development Institute 2009 Introduction Paddy soils are naturally heterogeneous in terms of their physico-chemical properties which influence rice productivity (Aminuddin et al. 2003). Currently, uniform application of agricultural inputs such as fertilizers, seeds, irrigation and pesticides is not efficient and could result in either insufficient or excess nutrient supply, and the yield at the end of the growing season often varies across the field. Changes in physical and chemical properties are responsible for changes in crop yield (Bauer and Black 1994; Gardner and Clancy 1996; Olson et al. 1996). Perhaps, it may be more logical and practical to apply discriminate amount of agricultural inputs to sections of the field that have different soil properties to enhance yield. To do this, good field maps showing how soil changes across the fields are needed.