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Stevenson, M
Setiyono, T
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Authors
Draganova, I
Yule, I
Stevenson, M
Barbosa, M
Duron, D
Rontani, F
Bortolon, G
Moreira, B
Oliveira, L
Setiyono, T
Shiratsuchi, L
Silva, R.P
Holland, K.H
Topics
Precision Dairy and Livestock Management
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2024
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1. The Use of Sensing Technologies to Monitor and Track the Behavior of Cows on a Commercial Dairy Farm

New Zealand farmers are facing rapidly increasing pressure to reduce nutrient losses from their farming enterprises to the environment caused by grazing ruminants. Research... I. Draganova, I. Yule, M. Stevenson

2. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane Feedstock

Predicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland