Development of the decision-support tool ‘Harvest Mate’: agronomic algorithms

Abstract

Changing cane harvester’s primary-extractor fan speed and flow rate impacts tonnes of cane and sugar delivered to the mill and the cost of harvesting. Although past research shows a negative impact of high harvester flow rates and fan speeds on delivered cane yield, adoption rates of harvesting best practice (HBP) remain low. This is despite the potential of HBP substantially increasing overall harvested sugarcane to the Australian industry without an increase in cane area. A key barrier to adoption is the challenge for growers and contractors to confidently determine the economic benefit or cost of adopting alternative harvesting practices over standard practices. One practical solution initiated and supported by the industry is the development of a decision-support tool to assist harvesting groups in estimating both grower revenue and harvesting cost impacts. However, estimates of both yield and CCS are required to determine revenue outputs. Given the extensive production data collected during the 2017/18 harvesting trials from the project ‘Adoption of practices to mitigate harvest losses’, various algorithms were developed for a harvesting decision-support tool. These included estimates of yield, extraneous matter (utilised in CCS calculations) and billet diameter. Algorithms were also required to estimate changes in harvesting costs due to differences in fuel utilisation and bulk density. This paper examines the development of these algorithms and the functionality of Harvest Mate, a new tool that incorporates agronomic and economic considerations to determine the most economically optimal harvester settings.