An assessment of sugarcane yield monitoring concepts and techniques from commercial yield monitoring systems

Jensen, T. A. and Baillie, C. and Bramley, R. G. V. and Panitz, J. H. (2012) An assessment of sugarcane yield monitoring concepts and techniques from commercial yield monitoring systems. In: 34th Annual Conference of the Australian Society of Sugar Cane Technologists (ASSCT 2012), 1-4 May 2012, Cairns, Australia.


A number of attempts have been made to monitor cane yield variation across a block in Australia. These have ranged from the early yield monitoring systems based on discrete mass measurement, to the current focus of predicting yield via surrogate measurements based on chopper pressure, feed train roller displacement and elevator power. Recent work aimed at assessing commercially available sensors (Jensen et al. 2010) suggested that there were several areas in which there was room for marked improvement. Rather than testing commercially available sensors, this paper details the testing that was conducted on evaluating the measurement concept. These concepts included; the pressure drop across the elevator and chopper motors, a load cell in the elevator floor and the angle of opening of the top feed roller. These concepts cover those being employed in the commercial units, both past and present. Trials were conducted during the 2010 season in the Bundaberg region and in both the Bundaberg and Herbert regions in 2011. Campbell Scientific CR3000 dataloggers were used to read each of the sensors at 40 Hz and record the averaged value every second, along with the GPS information. In addition to this sensor data, sugarcane yield was also measured to determine the accuracy and resolution of the respective yield monitoring concepts. Yield was determined using two methods and included mill (bin) weight data for individually consigned sub-blocks and weighed 50 m row samples into a weigh truck. The approach used was consistent with the methodology previously developed to assess the accuracy of commercial yield monitoring equipment during 2008/09. Preliminary analysis indicates that there are considerable similarities between the yield monitoring concepts in terms of their ability to measure yield, and that how the sensor data is recorded and managed is critical to the accuracy and overall performance of these concepts as yield monitors. This paper reports on the findings of this work and makes recommendations for further refining the devices and for additional work.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2012 by Australian Society of Sugar Cane Technologists. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording or any information storage and retrieval system, without permission of the publisher.
Faculty/School / Institute/Centre: Historic - Faculty of Engineering and Surveying - No Department (Up to 30 Jun 2013)
Faculty/School / Institute/Centre: Historic - Faculty of Engineering and Surveying - No Department (Up to 30 Jun 2013)
Date Deposited: 06 Jun 2013 05:47
Last Modified: 31 Jan 2017 01:27
Uncontrolled Keywords: sugar farming; yield monitoring; sensors; measurement; precision agriculture; variability
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
09 Engineering > 0913 Mechanical Engineering > 091302 Automation and Control Engineering
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460304 Computer vision
40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400799 Control engineering, mechatronics and robotics not elsewhere classified
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300207 Agricultural systems analysis and modelling
Socio-Economic Objectives (2008): B Economic Development > 82 Plant Production and Plant Primary Products > 8203 Industrial Crops > 820304 Sugar

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