Modelling of the leaf area for various pear cultivars using neuro computing approaches

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Öztürk A., Cemek B., Demirsoy H., Küçüktopcu E.

SPANISH JOURNAL OF AGRICULTURAL RESEARCH, cilt.17, sa.4, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 4
  • Basım Tarihi: 2019
  • Doi Numarası: 10.5424/sjar/2019174-14675
  • Dergi Adı: SPANISH JOURNAL OF AGRICULTURAL RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: Pyrus communis L., artificial neural networks, multiple linear regressions, model estimation, NONDESTRUCTIVE ESTIMATION, PREDICTION MODELS, NETWORKS, ACCURATE, WEIGHT, LENGTH, PLANTS, TREE
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Aim of study: Leaf area (LA) is an important variable for many stages of plant growth and development such as light interception, water and nutrient use, photosynthetic efficiency, respiration, and yield potential. This study aimed to determine the easiest, most accurate and most reliable LA estimation model for the pear using linear measurements of leaf geometry and comparing their performance with artificial neural networks (ANN).