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Estimation of Sugar Beet Yield and its Dry Matter Partitioning Under Different Irrigation and Nitrogen Levels

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  • Hamidreza Kamali
  • Shahrokh Zand-Parsa

Abstract

In this study, a simple logistic model was developed for estimating total dry matter of sugar beet under different irrigation and nitrogen levels. The experiment was conducted using line source sprinkler irrigation in 2013 and furrow irrigation in 2014. Irrigation treatments were from 44% to 130% of full irrigation and applied nitrogen treatments ranged from 0 to 240 kg N ha-1. Results showed that the model was more accurate in predicting total dry matter at harvest date with the Normalized Root Mean Square Error (NRMSE) amounting to almost 10 percent. After total dry matter estimation, a model was needed for dry matter partitioning between different organs of sugar beet. To achieve this goal, another logistic model was developed and was compared with three revised models. Finally, white sugar content of root dry matter was estimated using a quadratic equation as a function of applied water and nitrogen. Validation results indicated that total and root dry matters, and white sugar yield were estimated fairly well. Results showed that excessive water had negative effects on total dry matter and root dry matter. Also, excessive nitrogen affected root dry matter negatively too, but even the excess had positive effects on total dry matter. In contrast to common belief, our results showed that drought stress reduced both ratios of root to leaf, and root to shoot dry matter.

Suggested Citation

  • Hamidreza Kamali & Shahrokh Zand-Parsa, 2017. "Estimation of Sugar Beet Yield and its Dry Matter Partitioning Under Different Irrigation and Nitrogen Levels," Modern Applied Science, Canadian Center of Science and Education, vol. 11(1), pages 143-143, September.
    • Handle: RePEc:ibn:masjnl:v:11:y:2016:i:1:p:143
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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