Guopeng Jiang

Citation

Thesis Title
Predicting spatiotemporal yield variability to aid arable precision agriculture in New Zealand: A case study of maize-grain crop production in the Waikato Region

Precision agriculture attempts to manage within-field spatial variability by applying suitable inputs at the appropriate time, place, and amount. To achieve this, delineation of field-specific management zones, representing significantly different yield potentials, are required. To date, the effectiveness of utilising management zones in New Zealand has potentially been limited due to a lack of emphasis on the interactions between spatiotemporal factors such as soil texture, crop yield, and rainfall. Mr Jiang's thesis addresses the scientific area of Spatiotemporal Variability, specifically in methods to predict patterns of field variability as an input for decision making in precision agriculture of arable fields. In principle, the areas of new scientific knowledge and methods can be seen in developing - including testing - of (i) a filtering method for yield data from grain harvesting combines, and (ii) a deep-learning method that combines spatiotemporal yield data with easily accessible field variables.

Supervisors
Dr Miles Grafton
Professor Diane Pearson
Dr Mike Bretherton