Can Artificial Intelligence Help Palm Oil In Colombia?

Published 2024년 8월 7일

Tridge summary

Researchers in Colombia, led by professor Isis Bonet Cruz, are using deep learning models to predict the ripeness of oil palm fruit in real-time, aiming to increase efficiency and conserve biodiversity without expanding plantations. This project, part of Colombia's efforts to ensure palm oil production without deforestation, could potentially reduce the use of water and fertilizers by predicting the optimal harvesting times. Meanwhile, Alberto Gomez Mejia, a botanist, is working to protect two culturally and economically important palm species in Colombia, Taparo and Chontaduro, which are native to the country and face extinction, by establishing a gene bank, reintroducing them into the wild, and developing sustainable commercial plantations.

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Original content

Researchers in Colombia are using deep learning models to predict the ripeness of oil palm fruit, helping to increase efficiency. Colombia is the largest palm oil producer in the Americas and ranks fourth overall. Oil palm is associated worldwide with deforestation, but in Colombia a lot of work has been done to ensure that palm plantations are free of deforestation with a zero deforestation agreement (ZDA) signed in 2017. Isis Bonet Cruz, a Cuban researcher and professor at the La Universidad EIA in Antioquia, Colombia, says that her project aims to lift the productivity of existing plantations without the need to expand into new areas, helping to conserve forests and biodiversity. “In the project, photos were collected from videos of the processing area, the fruits were classified by experts and a deep learning model was trained to classify the fruits in real time, determining their ripeness and quality,” she says, adding that the model classifies the fruits into green, ripe and ...

Source: UkrAgroConsult