کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2415147 1552125 2009 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification and regression tree (CART) for analysis of soybean yield variability among fields in Northeast China: The importance of phosphorus application rates under drought conditions
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم زراعت و اصلاح نباتات
پیش نمایش صفحه اول مقاله
Classification and regression tree (CART) for analysis of soybean yield variability among fields in Northeast China: The importance of phosphorus application rates under drought conditions
چکیده انگلیسی

Drought is the most critical environmental factor limiting the productivity of agricultural crops worldwide. Increased frequency and severity of drought are expected to accompany climate change and will negatively impact global food security. Wide yield variability from field to field, and consequently reduced average yield on a regional scale often occur under drought conditions. The reasons for the yield variability are still poorly understood. In this study, we explored sources of soybean yield variability among fields in a rural village of Northeast China associated with a severe drought growing season in 2007. Soil parameter measurements were made on fields following three transects with different distances from homestead. Management data were assembled from household interviews. The relative importance of soil parameters and management practices resulting in yield variability among fields was analyzed with general linear model (GLM) and classification and regression trees (CARTs) models. Our analysis showed that variability in management options, as opposed to variability in soil parameters, caused the majority of yield variability from field to field. The amount of P applied was the most important variable determining yield variability and explained roughly 61% of the variability. Whether or not manure was added into fields was of secondary importance. The classification tree analysis indicated that yield differences among transects was attributed to the content of K nutrient. This might result from variations of long-term management options with distance from homestead. CART models are robust technique for predicting yield variability responses to variations of soil properties and management practices due to its low prediction error. Our study highlights the pressing need to adjust management strategies for narrowing yield variability and increasing crop production in drought years. We recommend that in addition to testing soil, government programs in China should also pay close attention to management practices of farmers.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agriculture, Ecosystems & Environment - Volume 132, Issues 1–2, July 2009, Pages 98–105
نویسندگان
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