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Monitoring wheat fields by RapidScan: accuracy and limitations

Published online by Cambridge University Press:  01 June 2017

D. J. Bonfil
D. J. Bonfil*
Affiliation:
Field Crops and Natural Resources Department, Agricultural Research Organization, Gilat Research Center, 85280 MP Negev 2, Israel
*
† E-mail: bonfil@volcani.agri.gov.il
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Abstract

Simple active radiometer sensors, such as RapidScan, enable agronomic decision-making and phenotyping within commercial wheat fields and experiments. The objectives of this study were: 1 - to evaluate the accuracy of quantitative biomass and nitrogen uptake estimation by the RapidScan, and 2 - to evaluate yield loss estimation based on NDVI. The RapidScan sensor was used as an assessment tool in the following studies: (i) over 3 years, 518 wheat samples were monitored during the vegetative growth period for biomass and aboveground nitrogen uptake and (ii) wheat cultivars were tested in an additional 4 field experiments, which were scanned weekly and correlated with grain yield. Results showed that accurate biomass estimation is limited up to about 100 g DM m−2. Grain yield, actual and potential, estimation is highly affected by the emergence date. The results showed that the use of a proximal-sensing technique allows for rapid and accurate crop monitoring and yield estimation, but emphasizing limitations in future use as well.

Keywords

Crop monitoringProximal sensing
Type
Precision Nitrogen
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 333 - 337
Copyright
© The Animal Consortium 2017 

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References

Bonfil, DJ 2016. Wheat phenomics in the field by RapidScan: NDVI vs. NDRE. Israel Journal of Plant Sciences 1–14.Google Scholar
Bonfil, DJ and Gitelson, AA 2014. RapidScan and CropCircle radiometers: opportunities and limitation in assessing wheat biomass and nitrogen, In Proceedings of the 12th International Conference on Precision Agriculture Sacramento, CA, USA.Google Scholar
Bonfil, DJ, Karnieli, A, Raz, M, Mufradi, I, Asido, S, Egozi, H, Hoffman, A and Schmilovitch, Z 2004. Decision support system for improving wheat grain quality in the Mediterranean area of Israel. Field Crops Research 89, 153–163.Google Scholar
Bonfil, DJ, Karnieli, A, Raz, M, Mufradi, I, Asido, S, Egozi, H, Hoffman, A and Schmilovitch, Z 2005. Rapid assessing water and nitrogen status in wheat flag leaves. Journal of Food, Agriculture and Environment 3, 207–212.Google Scholar
Gnyp, ML, Miao, Y, Yuan, F, Ustin, SL, Yu, K, Yao, Y, Huang, S and Bareth, G 2014. Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages. Field Crops Research 155, 42–55.Google Scholar
Li, F, Miao, Y, Feng, G, Yuan, F, Yue, S, Gao, X, Liu, Y, Liu, B, Ustin, SL and Chen, X 2014. Improving estimation of summer maize nitrogen status with red edge-based spectral vegetation indices. Field Crops Research 157, 111–123.Google Scholar
Mulla, DJ 2013. Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps. Biosystems Engineering 114, 358–371.CrossRefGoogle Scholar
Pimstein, A, Karnieli, A, Bansal, SK and Bonfil, DJ 2011. Exploring remotely sensed technologies for monitoring wheat potassium and phosphorus using field spectroscopy. Field Crops Research 121, 125–135.Google Scholar
Pimstein, A, Eitel, JUH, Long, DS, Mufradi, I, Karnieli, A and Bonfil, DJ 2009. A spectral index to monitor the head-emergence of wheat in semi-arid conditions. Field Crops Research 111, 218–225.CrossRefGoogle Scholar
Samborski, SM, Tremblay, N and Fallon, E 2009. Strategies to make use of plant sensors-based diagnostic information for nitrogen recommendations. Agronomy Journal 101, 800–816.Google Scholar