TY - GEN
T1 - Crop growth prediction model at vegetative phase to support the precision agriculture application in plant factory
AU - Rizkiana, Aulia
AU - Nugroho, Andri Prima
AU - Irfan, Muhammad Abiyyu
AU - Sutiarso, Lilik
AU - Okayasu, Takashi
N1 - Funding Information:
Authors wishing to acknowledge financial support from Ministry of Research, Technology and Higher Education of the Republic of Indonesia by 2018 - 2019 Research Grants of Penelitian Terapan Unggulan Perguruan Tinggi (PTUPT) 2018 (No. 1878/UN1/DITLIT/DIT-LIT/LT/2018) and 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:
© 2019 Author(s).
PY - 2019/12/27
Y1 - 2019/12/27
N2 - Plant factory is an extensive cultivation that produce vegetable under a controllable environment. The concept of Precision Agriculture has been introduced to enhance the plant factory production by monitoring of crop growth intensively. Crop growth can be estimated using a mathematical model to determine the state of the plant during the growth period. However, the application of a crop growth model in plant factory has several challenges because every plant has a specific model to be observed. The objective of this study was to construct a crop growth prediction model for vegetative development phase. The activity covers the development of mathematical model and model validation using Chili (Capsicum frutescens) as a preliminary experiment. Four samples (S1, S2, S3, S4) of Chili with age of five weeks after planting were used and measured daily for 30 days to get the actual height (cm). Three crop height observation data set (S1, S1, S3), were used to develop a mathematical model and the rest dataset was for model validation and evaluation. Linear and polynomial model were applied to obtain the appropriate prediction. The model was validated and evaluated using the Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). As a result, Determination coefficient (R2) of the Linear model was 0.9667, and the RMSE was 2.16; The Polynomial model shows R2 0.98755, and RMSE RMSE 1.68. The result of the model that is suitable for the Chili crop during the vegetative phase is the polynomial model with error rate of 1,68%.
AB - Plant factory is an extensive cultivation that produce vegetable under a controllable environment. The concept of Precision Agriculture has been introduced to enhance the plant factory production by monitoring of crop growth intensively. Crop growth can be estimated using a mathematical model to determine the state of the plant during the growth period. However, the application of a crop growth model in plant factory has several challenges because every plant has a specific model to be observed. The objective of this study was to construct a crop growth prediction model for vegetative development phase. The activity covers the development of mathematical model and model validation using Chili (Capsicum frutescens) as a preliminary experiment. Four samples (S1, S2, S3, S4) of Chili with age of five weeks after planting were used and measured daily for 30 days to get the actual height (cm). Three crop height observation data set (S1, S1, S3), were used to develop a mathematical model and the rest dataset was for model validation and evaluation. Linear and polynomial model were applied to obtain the appropriate prediction. The model was validated and evaluated using the Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). As a result, Determination coefficient (R2) of the Linear model was 0.9667, and the RMSE was 2.16; The Polynomial model shows R2 0.98755, and RMSE RMSE 1.68. The result of the model that is suitable for the Chili crop during the vegetative phase is the polynomial model with error rate of 1,68%.
UR - http://www.scopus.com/inward/record.url?scp=85078036113&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078036113&partnerID=8YFLogxK
U2 - 10.1063/1.5141717
DO - 10.1063/1.5141717
M3 - Conference contribution
AN - SCOPUS:85078036113
T3 - AIP Conference Proceedings
BT - International Conference on Science and Applied Science, ICSAS 2019
A2 - Suparmi, A.
A2 - Nugraha, Dewanta Arya
PB - American Institute of Physics Inc.
T2 - International Conference on Science and Applied Science 2019, ICSAS 2019
Y2 - 20 July 2019
ER -