TY - JOUR
T1 - Implementation of crop growth monitoring system based on depth perception using stereo camera in plant factory
AU - Nugroho, A. P.
AU - Fadilah, M. A.N.
AU - Wiratmoko, A.
AU - Azis, Y. A.
AU - Efendi, A. W.
AU - Sutiarso, L.
AU - Okayasu, T.
N1 - Funding Information:
Authors wishing to acknowledge financial support from The Ministry of Research, Technology and Higher Education of the Republic of Indonesia by 2018 - 2019 Research Grants of Penelitian Terapan Unggulan Perguruan Tinggi (PTUPT) 2019 (No. 2771/UN1/DITLIT/DIT-LIT/LT/2019), Research Grant of Rekognisi Tugas Akhir (RTA) Scheme from Universitas Gadjah Mada 2019 (No. 3414/UN1/DITLIT/DIT-LIT/LT/2019). Also, the author would like to thanks Smart Agriculture Research group of Agricultural and Biosystems Engineering UGM for the support.
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2020/8/6
Y1 - 2020/8/6
N2 - The plant factory is extensive cultivation to produce a high quality of vegetables under a controllable environment. The concept of Precision Agriculture (PA) was introduced to improve the plant factory production by the implementation of a crop growth monitoring system. Crop growth can be estimated by monitoring of crop height and canopy foliage by the use of computer vision technology. In our previous study, we have introduced a plant height monitoring system based on depth perception using a stereo camera. However, the validity of the various type of leave is necessary to be tested. The objective of this study was to implement the crop growth monitoring system to monitor plant development with various type of leave for system validation and evaluation. The crop growth monitoring system composed of a stereo camera implementing the depth perception for estimating the distance from camera to highest point in the crop. The implementation of the system with various types of leaves and characteristics has been conducted for (a) Samhon, (b) Lettuce, and (c) Pagoda. The developed crop growth monitoring system could perform the time series estimation of crop height with a maximum error of RMSE 0.875 cm on Pagoda, and MAPE of 5.56% on Lettuce. The system demonstrates better estimation on Samhong with minimum error RMSE of 0.408cm and 2.27 % of MAPE. Overall validation for the estimated height vs actual measurement indicates that the coefficient of determination higher than 0.7 means that it has substantial features for estimating the plant height.
AB - The plant factory is extensive cultivation to produce a high quality of vegetables under a controllable environment. The concept of Precision Agriculture (PA) was introduced to improve the plant factory production by the implementation of a crop growth monitoring system. Crop growth can be estimated by monitoring of crop height and canopy foliage by the use of computer vision technology. In our previous study, we have introduced a plant height monitoring system based on depth perception using a stereo camera. However, the validity of the various type of leave is necessary to be tested. The objective of this study was to implement the crop growth monitoring system to monitor plant development with various type of leave for system validation and evaluation. The crop growth monitoring system composed of a stereo camera implementing the depth perception for estimating the distance from camera to highest point in the crop. The implementation of the system with various types of leaves and characteristics has been conducted for (a) Samhon, (b) Lettuce, and (c) Pagoda. The developed crop growth monitoring system could perform the time series estimation of crop height with a maximum error of RMSE 0.875 cm on Pagoda, and MAPE of 5.56% on Lettuce. The system demonstrates better estimation on Samhong with minimum error RMSE of 0.408cm and 2.27 % of MAPE. Overall validation for the estimated height vs actual measurement indicates that the coefficient of determination higher than 0.7 means that it has substantial features for estimating the plant height.
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U2 - 10.1088/1755-1315/542/1/012068
DO - 10.1088/1755-1315/542/1/012068
M3 - Conference article
AN - SCOPUS:85090503341
SN - 1755-1307
VL - 542
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012068
T2 - 3rd International Conference on Agricultural Engineering for Sustainable Agriculture Production, AESAP 2019
Y2 - 14 October 2019 through 15 October 2019
ER -