Articles
Image-based production prediction analysis and monitoring of processing tomato vegetative development
Article number
1445_1
Pages
1 – 4
Language
English
Abstract
In 2022, Extremadura was the primary region for processing tomato production in Spain, contributing 61% of the national output, particularly in Vegas del Guadiana.
However, the rise of super-intensive olive and almond plantations, which require less water and are more profitable, is reducing the significance of tomato cultivation.
A major issue in intensive horticulture in irrigated areas of Spain is over-fertilization, leading to nitrate contamination of groundwater.
This problem is exacerbated by inadequate crop nutritional monitoring, traditional over-fertilization, and excessive irrigation practices aimed at ensuring yields, combined with the low nitrogen extraction efficiency of horticultural crops.
These factors have driven the development of monitoring methods using satellite images or drones.
This study aims to identify the most accurate image analysis indices (NDVI, NDRE, and GNDVI) for assessing the nutritional and developmental status of processing tomato crops and to determine the optimal timing for these measurements.
The trial included four nitrogen fertilization treatments for processing tomatoes at Finca La Orden, Badajoz.
Standard agronomic practices were followed, and drone flights were conducted to correlate dry matter production (DMP) with NDVI, GNDVI, and NDRE indices.
The results showed that this methodology effectively measures crop DMP in real time and non-destructively, with NDVI being the most accurate index, particularly around 84 days after transplanting.
However, the rise of super-intensive olive and almond plantations, which require less water and are more profitable, is reducing the significance of tomato cultivation.
A major issue in intensive horticulture in irrigated areas of Spain is over-fertilization, leading to nitrate contamination of groundwater.
This problem is exacerbated by inadequate crop nutritional monitoring, traditional over-fertilization, and excessive irrigation practices aimed at ensuring yields, combined with the low nitrogen extraction efficiency of horticultural crops.
These factors have driven the development of monitoring methods using satellite images or drones.
This study aims to identify the most accurate image analysis indices (NDVI, NDRE, and GNDVI) for assessing the nutritional and developmental status of processing tomato crops and to determine the optimal timing for these measurements.
The trial included four nitrogen fertilization treatments for processing tomatoes at Finca La Orden, Badajoz.
Standard agronomic practices were followed, and drone flights were conducted to correlate dry matter production (DMP) with NDVI, GNDVI, and NDRE indices.
The results showed that this methodology effectively measures crop DMP in real time and non-destructively, with NDVI being the most accurate index, particularly around 84 days after transplanting.
Authors
J.M. Vadillo, V. Cerasola, C. Campillo, V. González, H. Prieto
Keywords
NDVI, processing tomato, precision agriculture
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