Predicting carob tree physiological parameters under different irrigation systems using Random Forest and Planet satellite images
Simone Pietro Garofalo; Vincenzo Giannico; Beatriz Lorente; Antonio José García García; Gaetano Alessandro Vivaldi; Afwa Thameur; Francisco Pedrero Salcedo · 2024 · Frontiers in Plant Science
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
IntroductionIn the context of climate change, monitoring the spatial and temporal variability of plant physiological parameters has become increasingly important. Remote spectral imaging and GIS software have shown effectiveness in mapping field variability. Additionally, the application of machine learning techniques, essential for processing large data volumes, has seen a significant rise in agricultural applications. This research was focused on carob tree, a drought-resistant tree crop spread through the Mediterranean basin. The study aimed to develop robust models to predict the net assim
Abstract by Simone Pietro Garofalo; Vincenzo Giannico; Beatriz Lorente; Antonio José García García; Gaetano Alessandro Vivaldi; Afwa Thameur; Francisco Pedrero Salcedo, Frontiers in Plant Science (2024) — licensed CC BY 4.0.
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Metadata source: DOAJ · DOI 10.3389/fpls.2024.1302435