Potential for using low-cost spectral sensors to predict yield in small-scale rice fields in northwest Cambodia - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Poster Communications Year : 2020

Potential for using low-cost spectral sensors to predict yield in small-scale rice fields in northwest Cambodia

Abstract

Smart technology is playing a vital role in making crop management decisions (Awan et al., 2018). However, advanced high throughput technologies may be a significant adoption challenge for small-scale rice growers in Cambodia due to cost and accessibility. Hence, developing algorithm to predict yield in-season using cost-effective technologies is a better intervention to support Cambodian rice growers. GreenSeeker-NDVI and Canopeo are potentially emerging affordable tools that can produce a working algorithm to support small-scale rice growers. Thus, we hypothesized that low-cost sensors can predict yield in small-sale rice fields. Therefore, the objective of the study is to calibrate a working algorithm for predicting yield in small-scale rice fields in northwest Cambodia.
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Dates and versions

hal-02950269 , version 1 (27-09-2020)

Identifiers

  • HAL Id : hal-02950269 , version 1

Cite

Onwuchekwa-Henry Chinaza, Floris van Ogtrop, Robert Martin, Daniel Tan. Potential for using low-cost spectral sensors to predict yield in small-scale rice fields in northwest Cambodia. ICROPM2020: Second International Crop Modelling Symposium , Feb 2020, Montpellier, France. ⟨hal-02950269⟩
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