A Machine Learning-Based Assessment of Maize Silage Dry Matter Losses by Net-Bags Buried in Farm Bunker Silos

Estimating the dry matter losses (DML) of whole-plant maize (WPM) silage is a priority for sustainable dairy and beef farming. The study aimed to assess this loss of nutrients by using net-bags (<i>n</i> = 36) filled with freshly chopped WPM forage and buried in bunker silos of 12 Italian dairy farm...

Полное описание

Библиографические подробности

Главные авторы:	Severino Segato, Giorgio Marchesini, Luisa Magrin, Barbara Contiero, Igino Andrighetto, Lorenzo Serva
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2022-05-01
Серии:	Agriculture
Предметы:	maize silage porosity density dry matter loss bunker silo machine learning
Online-ссылка:	https://www.mdpi.com/2077-0472/12/6/785
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