Mathematical Modeling of Crop Water Production Functions for Sugar Beet


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Ayas S.

SUGAR TECH, cilt.27, sa.2, ss.1-12, 2025 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 27 Sayı: 2
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1007/s12355-025-01572-8
  • Dergi Adı: SUGAR TECH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, CAB Abstracts, Food Science & Technology Abstracts
  • Sayfa Sayıları: ss.1-12
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

Crop water production functions, which describe the relationship between yield and water use, are of great importance in

determining the economic value of irrigation, identifying different irrigation strategies and determining optimum irrigation

levels. The main objective of this study was to evaluate the performance of Stewart, Jensen, Minhas, Blank and Rao functions

in predicting root yield in sugar beet. Field studies were carried out in 2019 and 2020 in Bursa Yenişehir Vocational

School Production Area. Water stress sensitivity indices of crop water production functions were determined using ET and

yield values in the first year. Root yield values simulated with crop water production functions were compared with root

yield values measured in the field in 2020. Sensitivity indices of sugar beet to water at four different growth stages were

determined using five different crop water production models. Considering the sensitivity indices of sugar beet to water in

four different growth periods, it was determined that the yield formation period (Y) was the most sensitive to water. Yield

formation (Y) period was followed by vegetative (V) and establishment (E) periods. The least water-sensitive period of sugar

beet was the ripening (R) period. Jensen and Minhas models were recommended when the sensitivity indices to water stress

calculated for four different growth stages of sugar beet were compared.