Resistive Sensing of Seed Cotton Moisture Regain Based on Pressure Compensation.

Abstract

The measurement of seed cotton moisture regain (MR) during harvesting operations is an open and challenging problem. In this study, a new method for resistive sensing of seed cotton MR measurement based on pressure compensation is proposed. First, an experimental platform was designed. After that, the change of cotton bale parameters during the cotton picker packaging process was simulated through the experimental platform, and the correlations among the compression volume, compression density, contact pressure, and conductivity of seed cotton were analyzed. Then, support vector regression (SVR), random forest (RF), and a backpropagation neural network (BPNN) were employed to build seed cotton MR prediction models. Finally, the performance of the method was evaluated through the experimental platform test. The results showed that there was a weak correlation between contact pressure and compression volume, while there was a significant correlation ( p 2 ) of 0.986 and a root mean square error (RMSE) of 0.204%. The mean RMSE and mean coefficient of variation (CV) of the performance evaluation test results were 0.20% and 2.22%, respectively. Therefore, the method proposed in this study is reliable. In addition, the study will provide a technical reference for the accurate and rapid measurement of seed cotton MR during harvesting operations.

Plant phenotyping relevance

種子綿の水分戻りを抵抗式センシングと圧力補償で推定する方法を開発し、実験プラットフォームと複数の予測モデルで性能評価しており、植物試料の形質測定法が中心です。

Code and data availability

The paper's experimental data (704 records of contact pressure, resistance, and moisture regain) are not publicly deposited; the Data Availability Statement says they are available only on request from the corresponding author. No public code, models, or datasets are mentioned.

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