The confusion matrix was computed separately for two, three, four, and seven clusters from k-means clusters related to the ensiling method inoculant, sealing delay, inoculant dose, and years, respectively.

The confusion matrix was computed separately for two, three, four, and seven clusters from k-means clusters related to the ensiling method inoculant, sealing delay, inoculant dose, and years, respectively.

<p>In parentheses, it is indicated whether the observed value is lower (<) or higher (>) than the expected value, along with the significance from Fisher’s exact test (Χ<sup>2</sup> test).</p>

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Bibliographic Details
Main Author:	Lorenzo Serva (6184358) (author)
Published:	2024
Subjects:	Biochemistry Microbiology Ecology Sociology Developmental Biology Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified predictive models derived field sensor technology freshly harvested maize incorporating additional factors shaping silage quality maize silage quality maize silage silage quality various pre source database significant source seasonality playing seasonality exerts screening purposes robust algorithms profound influence ph level machine learning highly recommended findings revealed fermentative profile ensiling circumstances diverse pre diverse databases deep learning crucial role comprehensive approach comparative evaluation combining data better elucidate beef cattle ammonia content aerobic stability
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