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JRM Vol.38 No.2 pp. 471-482
(2026)
doi: 10.20965/jrm.2026.p0471

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Predictive Modeling of Crop Growth Using a Smart Agriculture Measurement Module Composed of Multipoint Soil Moisture Sensor and Environmental Sensors

Katsushi Ogawa ORCID Icon, Wakana Ono, and Seonghee Jeong

Osaka Electro-Communication University
18-8 Hatsucho, Neyagawa-shi, Osaka 572-8530, Japan

Received:
October 9, 2025
Accepted:
February 2, 2026
Published:
April 20, 2026
Creative Commons License
Keywords:
smart agriculture, crop growth prediction, multipoint soil moisture sensing, broccoli
Abstract

In this study, we addressed agricultural labor shortages by developing a smart farming sensor module that integrated low-cost environmental sensors with a multipoint soil moisture sensor to predict broccoli growth, plant height (PH), and leaf count (Ln). Multivariable regression confirmed that integrated solar radiation (S) was the most dominant factor, although broccoli growth involved a complex interplay of solar radiation, optimal temperature, humidity, and soil moisture. More importantly, the analysis revealed that the middle layer soil moisture (um) exhibited the strongest positive contribution to PH. This finding indicated that water availability in the main root zone was essential for vertical growth and highlighted the indispensability of multipoint sensing over conventional single-depth measurements to accurately model the intricate relationship between soil moisture and crop development. Moving forward, we aim to leverage the superiority of multipoint data to construct a sophisticated growth prediction model, thereby contributing to the optimization of irrigation and temperature management in smart farming systems.

Conceptual diagram of the environmental monitoring system for broccoli growth in the field

Conceptual diagram of the environmental monitoring system for broccoli growth in the field

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Cite this article as:
K. Ogawa, W. Ono, and S. Jeong, “Predictive Modeling of Crop Growth Using a Smart Agriculture Measurement Module Composed of Multipoint Soil Moisture Sensor and Environmental Sensors,” J. Robot. Mechatron., Vol.38 No.2, pp. 471-482, 2026.
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Last updated on Apr. 19, 2026