Theoretical Development of Plant Root Diameter Estimation Based on GprMax Data and Neural Network Modelling
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Notice bibliographique
Résumé
The in situ non-destructive quantitative observation of plant roots is difficult. Traditional detection methods are not only time-consuming and labor-intensive, but also destroy the root environment. Ground penetrating radar (GPR), as a non-destructive detection method, has great potential in the estimation of root parameters. In this paper, we use GprMax software to perform forward modeling of plant roots under different soil dielectric constants, and analyze the situation of plant roots with different dielectric constants and different root diameters under 1.5 GHz frequency antenna detection. Firstly, root systems with increasing diameter under different values of root and soil dielectric constant were scanned. Secondly, from the scanning results, two time points T1 and T2 of radar wave entering and penetrating the root system were defined, and the correlation between root diameter D and time interval ΔT between T1 and T2 was analyzed. Finally, the least square regression model and back propagation (BP) neural network model for root diameter parameter estimation were established, and the estimation effects of the two models were compared and evaluated. The research results show that the root diameter (12–48 mm) is highly correlated with the time interval. Given the dielectric constants of the root and soil, the prediction results of the two models are accurate, but the prediction result of the neural network model is more stable, and the residual between the predicted value and the actual value is mainly concentrated in the [−1.5 mm, 1.5 mm] range, as well as the average of prediction error percentage being 3.62%. When the dielectric constants of the root and soil are unknown, the accuracy of the prediction results of the two models is decreased, but the stability of the neural network model is still superior to the least squares model, and the residual error is mainly concentrated in the range of [−5.3 mm, 5.0 mm], the average of prediction error percentage is 10.19%. This study uses GprMax to simulate root system detection and reveals the theoretical potential of GPR technology for non-destructive estimation of root diameter parameters. It is also pointed out that in the field exploration process, if the dielectric constants of the root and soil in the experimental site are sampled and measured first, the prediction accuracy of the model for root diameter would be effectively improved. This research is based on simulation experiments, so further simulation followed by laboratory and field testing is warranted using non-uniform roots and soil.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle