Simple, efficient and robust techniques for automatic multi-objective function parameterisation: Case studies of local and global optimisation using APSIM. - Matthew Tom Harrison; Pier Paolo Roggero; Laura Zavattaro (Environ. Model. Softw., 2019)

Estimating Pasture Biomass Using Sentinel-2 Imagery and Machine Learning. - Yun Chen 010; Juan Guerschman; Yuri Shendryk; Dave Henry 002; Matthew Tom Harrison (Remote. Sens., 2021)

Optimizing Crop Management with Reinforcement Learning and Imitation Learning. - Ran Tao; Pan Zhao 003; Jing Wu 020; Nicolas F. Martin; Matthew Tom Harrison; Carla Sofia Santos Ferreira; Zahra Kalantari; Naira Hovakimyan (IJCAI, 2023)

Residual correlation and ensemble modelling to improve crop and grassland models. - Renata Sándor; Fiona Ehrhardt; Peter Grace; Sylvie Recous; Pete Smith; Val Snow; Jean-François Soussana; Bruno Basso; Arti Bhatia; Lorenzo Brilli; Jordi Doltra; Christopher D. Dorich; et al. (Environ. Model. Softw., 2023)

Advancing Skyborne Technologies and High-Resolution Satellites for Pasture Monitoring and Improved Management: A Review. - Michael Gbenga Ogungbuyi; Caroline Mohammed; Iffat Ara; Andrew M. Fischer; Matthew Tom Harrison (Remote. Sens., 2023)

Integration of Drone and Satellite Imagery Improves Agricultural Management Agility. - Michael Gbenga Ogungbuyi; Caroline Mohammed; Andrew M. Fischer; Darren Turner; Jason Whitehead; Matthew Tom Harrison (Remote. Sens., 2024)

Irrigation with Artificial Intelligence: Problems, Premises, Promises. - Hanyu Wei; Wen Xu; Byeong Kang 001; Rowan Eisner; Albert Muleke; Daniel Rodriguez; Peter deVoil; Victor Oscar Sadras; Marta Monjardino; Matthew Tom Harrison (Hum. Centric Intell. Syst., 2024)

Global sensitivity analyses prior to parameter calibration significantly improves prediction quality. - Chunhu Wang; Matthew Tom Harrison; Hamish Brown; Yongliang Qiao; Xiaogang Yin; Rui Yang; Yunbo Zhang; Meixue Zhou; Ke Liu (Comput. Electron. Agric., 2025)

Uncovering environmental implications of historical stewardship of Japanese Moso Bamboo (Phyllostachys edulis) forests: a review using a multivariate imputation approach. - Daniel Forster; Matthew Tom Harrison; Minaco Adachi (Ecol. Informatics, 2025)