Variable permutation importance test results for kg DM/ha, UFL/ha and kg CP/ha predictions.

<p>Variable permutation importance test results for kg DM/ha, UFL/ha and kg CP/ha predictions.</p>

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Bibliographic Details
Main Author:	Silverio García-Cortés (4746477) (author)
Other Authors:	Agustín Menéndez-Díaz (22041811) (author), María José Bande-Castro (22041814) (author), Alfonso Carballal-Samalea (22041817) (author), Adela Martínez-Fernández (22041820) (author), Jose Alberto Oliveira-Prendes (22041823) (author)
Published:	2025
Subjects:	Medicine Biotechnology Ecology Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified xu3 – 400 xu2 – 300 xu1 – 220 se3 – 400 se2 – 300 se1 – 200 machine learning technique machine learning approach 2000 – 2022 model evaluation yielded crude protein yield forage maize yield div >< p 2 </ sup crop management conditions influential predictor variables historical meteorological data cultivars cycle 400 three sowing dates maize model crop yield influential variables management data longest cycle lactation yield historical weather three years three sites crop field weather variables variables studied year period top two study sites specialist users six cultivars site ). probable values net energy make predictions linear relationships highest values growing season geographical location genetic parameters four sites enabled simulation different climatic development according cultivar type
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