Estimation of harvest index in wheat crops using a remote sensing-based approach
Field Crops Research, ISSN: 0378-4290, Vol: 256, Page: 107910
2020
- 25Citations
- 69Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This paper presents an operational methodology for the estimation of the harvest index (HI) in commercial fields planted with wheat crops ( Triticum aestivum L.) using a Remote Sensing based approach. The approach proposed variants from the methodologies reported by Kemanian et al., (2007) and Sadras and Connor (1991) for the estimation of the HI using the ratio between variables related with biomass production, i.e. absorbed photosynthetically active radiation (APAR), crop transpiration (T) and crop transpiration coefficient (K t ) as defined in the FAO-66 manual. The estimation of these variables along the growing season integrates time series of Remote Sensing satellite images and meteorological data into the crop growth models. The proposed models for estimation of HI were calibrated using an extensive HI dataset obtained from 19 commercial fields (empirical data) planted with wheat. The fields were subject to different water and nutrient management, resulting in empirical HI values from 0.23 to 0.55. Future applications of the proposed approach are the operational estimation of wheat production at both regional and local scales and the estimation of the within-field variability of crop production considering the variability of HI values within the field.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0378429020311941; http://dx.doi.org/10.1016/j.fcr.2020.107910; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85088049660&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0378429020311941; https://dx.doi.org/10.1016/j.fcr.2020.107910
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know