Construction of Linear Models for the Normalized Vegetation Index (NDVI) for Coffee Crops in Peru Based on Historical Atmospheric Variables from the Climate Engine Platform
Open Access
- 1 August 2024
- journal article
- research article
- Published by MDPI AG in Atmosphere
- Vol. 15 (8) , 923
Abstract
The rapid development of digital tools for crop management offers new opportunities to mitigate the effects of climate change on agriculture. This study examines the Normalized Difference Vegetation Index (NDVI) in coffee-growing areas of the province of Rodriguez de Mendoza, southern Peru, from 2001 to 2022. The objectives were the following: (a) to analyze NDVI trends in these areas; (b) to investigate trends in climatic variables and their correlations with altitude and NDVI; and c) to develop linear models tailored to each coffee-growing area. The study identified significant differences in NDVI trends among coffee plants, with mean NDVI values ranging from about 0.6 to 0.8. These values suggest the presence of stress conditions that should be monitored to improve crop quality, particularly in Huambo. Variability in rainfall, maximum and minimum temperatures, relative humidity, and altitude was also observed, with NDVI values showing a strong negative correlation with altitude. These results are crucial for making informed strategic decisions in integrated crop management and for monitoring crop health using vegetation indices.Keywords
Funding Information
- Instituto de Investigación para el Desarrollo Sustentable de Ceja de Selva (INDES-CES) (2317883—CEINCAFÉ, PE501083491-2023-PROCIENCIA, PE501086357-2024-PROCIENCIA)
- ApiGen Project (2317883—CEINCAFÉ, PE501083491-2023-PROCIENCIA, PE501086357-2024-PROCIENCIA)
- CoffeSmart Project (2317883—CEINCAFÉ, PE501083491-2023-PROCIENCIA, PE501086357-2024-PROCIENCIA)
- Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas del Perú (2317883—CEINCAFÉ, PE501083491-2023-PROCIENCIA, PE501086357-2024-PROCIENCIA)
This publication has 77 references indexed in Scilit:
- Precipitation attribution distanceAtmospheric Research, 2023
- Watershed runoff modeling through a multi-time scale approach by multivariate empirical mode decomposition (MEMD)Environmental Science and Pollution Research, 2021
- Using NDVI for the assessment of canopy cover in agricultural crops within modelling researchComputers and Electronics in Agriculture, 2021
- A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensingJournal of Forestry Research, 2020
- Mapping vineyard vigor using airborne remote sensing: relations with yield, berry composition and sanitary status under humid climate conditionsPrecision Agriculture, 2019
- Shift in precipitation regime promotes interspecific hybridization of introduced Coffea speciesEcology and Evolution, 2016
- Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methodsAgricultural and Forest Meteorology, 2016
- Forecasting crop yield using remotely sensed vegetation indices and crop phenology metricsAgricultural and Forest Meteorology, 2013
- NDVI, temperature and precipitation changes and their relationships with different vegetation types during 1998–2007 in Inner Mongolia, ChinaInternational Journal of Climatology, 2012
- Cross-correlations between weather variables in AustraliaBuilding and Environment, 2007