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Leaf area estimation of cassava from linear dimensions.

Samara Zanetti1, Laís F M Pereira1, Maria Márcia P Sartori1

  • 1Universidade Estadual Paulista/UNESP, Faculdade de Ciências Agronômicas, Departamento de Produção e Melhoramento Vegetal, Rua José Barbosa de Barros, 1780, 18603-970 Botucatu, SP, Brazil.

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Summary

Predictor models for cassava leaf area were developed using linear leaf measurements. These models accurately estimate leaf area for the IAC 576-70 cultivar, aiding in crop management.

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Area of Science:

  • Agricultural Science
  • Plant Physiology
  • Agronomy

Background:

  • Accurate estimation of cassava leaf area is crucial for crop yield prediction and management.
  • Traditional methods of leaf area measurement can be time-consuming and destructive.
  • Developing non-destructive methods for estimating leaf area is essential for efficient agricultural practices.

Purpose of the Study:

  • To determine predictor models for estimating cassava leaf area using simple linear leaf measurements.
  • To evaluate the efficacy of polynomial and multiple regression models for this estimation.
  • To identify the most suitable linear functions for predicting leaf area in the IAC 576-70 cassava cultivar.

Main Methods:

  • Experiments were conducted in a greenhouse with cassava cultivar IAC 576-70.
  • Stem cuttings were planted and maintained at field capacity soil moisture.
  • Leaf area, central lobe length and width, and number of lobes were measured from 140 randomly selected leaves.

Main Results:

  • Linear regression models using central lobe length were found to be suitable for estimating leaf area.
  • Multiple linear regression models incorporating lobe length, width, and number also provided accurate estimations.
  • Specific linear functions were identified as effective predictors for cassava leaf area.

Conclusions:

  • Linear leaf measurements, particularly central lobe length, can reliably predict cassava leaf area.
  • Developed regression models offer a non-destructive and efficient method for estimating leaf area in cultivar IAC 576-70.
  • These findings can support improved crop monitoring and yield forecasting in cassava cultivation.