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, vol.17, no.4, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 4
  • Publication Date: 2019
  • Doi Number: 10.5424/sjar/2019174-14675
  • Journal Name: SPANISH JOURNAL OF AGRICULTURAL RESEARCH
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: Pyrus communis L., artificial neural networks, multiple linear regressions, model estimation, NONDESTRUCTIVE ESTIMATION, PREDICTION MODELS, NETWORKS, ACCURATE, WEIGHT, LENGTH, PLANTS, TREE
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

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).