Délimitation de zones d’aménagement à l’aide de capteurs proximaux du sol dans deux champs de culture intensive de la pomme de terre.
Bibliographic record
Abstract
L’utilisation des zones d’amenagement (ZA) dans la culture de la pomme de terre permet controler la variabilite spatiale du sol et est une des approches dans la gestion localisee des proprietes du sol. L’objectif de cette etude etait d’evaluer la capacite de trois capteurs proximaux du sol (CPS) pour delimiter des ZA pour deux champs (Champ SVP et champ SVS ; 12 hectares) en culture commerciale de pomme de terre (Solanum tuberosum L.) dans la province de Nouveau-Brunswick, Canada. La conductivite electrique apparente du sol (CEa) ont ete mesures avec deux CPS i.e. le VERIS (modele MSP3) et le DUALEM (modele 21S). En plus, des mesures de haute frequence electromagnetique ont ete prises avec un georadar (GPR;GSSI modele SIR-3000; antenne 400 MHz) pour determiner l’epaisseur des horizons de sol et la profondeur de la roche-mere. Les proprietes physicochimiques (texture, matiere organique, pH, Mehlich-3) de 154 echantillons de sol pour les champs SVP et 141 echantillons pour le champ SVS ont ete analyses. Le rendement total en tubercule a ete mesure pour les annees 2013, 2014 et 2016 pour le champ SVP et 2014 et 2016 pour le champ SVS a l’aide d’un capteur de rendement. L’algorithme fuzzy k-means a ete utilise pour delimiter les ZA. Une correlation significative entre le rendement et les CPS a ete obtenue (r= -0.52, 0.19 pour les champs SVP et SVS). L’argile a ete la propriete la plus correlee avec le rendement (r= -0.85 rx= -0.41, pour les champs SVP et SVS). Deux ZA ont ete consideres comme optimales pour les deux champs. Celles-ci ont montre un equilibre entre la variation spatiale des proprietes du sol, le rendement et une representation spatiale gerable. Abstract The use of management zones MZ in potato production is an alternative in the localized management of the soil properties. The objective of this study was to evaluate the ability of three proximal soil sensors (PSS) to delineate MZ for two commercial potato fields (referred as field SVP and field SVS, 12 hectares) (Solanum tuberosum L.) in New Brunswick, Canada. Soil electrical conductivity (EC) was measured with tho PSS, i.e, VERIS (model MSP3) and DUALEM (model 21 S). Additionally, high frequency EM was measured using a ground penetrating radar (GPR system; GSSI model SIR-3000; 400 MHz antenna) to determine the thickness of the soil horizons and the depth to bedrock. The physicochemical properties (texture, organic matter, pH, Mehlich-3) of 154 soil samples for the field SVP and 141 soil samples for the field SVS were analyzed. The total yield of tuber was measured for the years 2013, 2014 and 2016 for the field SVP and 2014 and 2016 for the field SVS using a yield monitor. The fuzzy k-means algorithm was used to delineate MZ. A significant correlation between the yield and the PSS was obtained (r = - 0.52, 0.19 for the field SVP and SVS, respectively). Clay was the property most correlated with the yield (r =-0.85, please and r = - 0.41, for the fields SVP and SVS, respectively). Two MZ were considered as optimal for both sites. These showed a balance between the spatial variation of soil properties, yield and a manageable spatial representation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".