NDLI: Improving the accuracy of estimating grain weight by discriminating each grain impact on the yield sensor

Content Provider	Springer Nature Link
Author	Shoji, Koichi Miyamoto, Muneri
Copyright Year	2013
Abstract	This study was aimed at accurately estimating total weight of harvested grain on a combine by simply attaching a small yield sensor in the grain tank and by processing the output of the sensor. The yield sensor was first installed in a grain tank of a 1.2 m-swath Japanese-style (head-feeding or jidatsu) combine, and the weight was estimated from individual impulses received at each rotation of a grain-releasing device i.e. an auger blade. A non-linear relation was assumed between the weight of grain released and the impulse received, and the parameters of the non-linear model were optimized to minimize the sum of squares between the estimated and actual weight of grain accumulated at each run of the combine. A threshold for the output discriminated between actual release and no release of the grain from the auger blade. The appropriate range of the threshold was 4–6 times the root-mean squared output of the sensor without throughput (F $_{ rms }$) of grain. The aim was to enhance the accuracy of the estimation of grain weight by disregarding signals that did not relate to the accumulation of grain in the tank. Two methods of calculating the impulses were proposed after the discrimination: “successive addition” and “interval addition”, and two non-linear models of converting impulses into the weight of grain: “odd function model” and “positive function model”. The use of the odd function model with the impulse calculated by the interval addition was the most robust, and root-mean squared relative errors of calibration and validation were both stable and around 2.5 % at a threshold of 5F $_{ rms }$. In the confirmatory experiment with a larger 1.8 m-swath Japanese-style grain combine equipped with the same sensor, the odd function model with the interval addition achieved root-mean squared relative error of 3.6 % at calibration and 4.4 % at validation at a threshold of 5F $_{ rms }$.
Starting Page	31
Ending Page	43
Page Count	13
File Format	PDF
ISSN	13852256
Journal	Precision Agriculture
Volume Number	15
Issue Number	1
e-ISSN	15731618
Language	English
Publisher	Springer US
Publisher Date	2013-11-06
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Yield monitor Impact Impulse Non-linear model Calibration Grain flow rate Agriculture Soil Science & Conservation Remote Sensing/Photogrammetry Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Atmospheric Sciences
Content Type	Text
Resource Type	Article
Subject	Agricultural and Biological Sciences

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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