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Assessment of Yield Variability by Linear Regression Model

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Advances in Computer Science, Intelligent System and Environment

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 105))

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Abstract

A long-term experiment was started in early 1990s and continued until 2008 to study the effects of crop rotation and chemical fertilization on the yield and yield stability of maize (Zea mays L.). The results indicated that the yield of maize was higher in the cropping system of soybean-maize rotation than that in maize monoculture. The yield of maize under the treatments without fertilizer N increased significantly in the crop rotation system. This observation can be explained by residual nutrients after legumes. The rotation effect would be diminished by balanced nutrient supply. Maize yield increased significantly under N fertilization treatments and was even higher under the treatments of N combined with P (NP) and NP plus K (NPK). The stability analysis showed that stability of maize yield of soybean-maize rotation was significantly improved compared to maize monoculture, and higher stability could be obtained in NP and NPK treatments regardless of crop sequences, which can be attributed mainly to balanced macronutrients supply.

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© 2011 Springer-Verlag Berlin Heidelberg

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Ma, Q., Zhou, H., Xu, Y. (2011). Assessment of Yield Variability by Linear Regression Model. In: Jin, D., Lin, S. (eds) Advances in Computer Science, Intelligent System and Environment. Advances in Intelligent and Soft Computing, vol 105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23756-0_84

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  • DOI: https://doi.org/10.1007/978-3-642-23756-0_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23755-3

  • Online ISBN: 978-3-642-23756-0

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