Integration of Remote Sensing and Crop Modeling for the Early Assessment of Durum Wheat Harvest at the Field Scale. Issue 3 (1st May 2015)
- Record Type:
- Journal Article
- Title:
- Integration of Remote Sensing and Crop Modeling for the Early Assessment of Durum Wheat Harvest at the Field Scale. Issue 3 (1st May 2015)
- Main Title:
- Integration of Remote Sensing and Crop Modeling for the Early Assessment of Durum Wheat Harvest at the Field Scale
- Authors:
- Orlando, Francesca
Marta, Anna Dalla
Mancini, Marco
Motha, Ray
Qu, John J.
Orlandini, Simone - Abstract:
- ABSTRACT: In the Mediterranean, durum wheat is one of the major crops, but a high variability of grain yield and protein concentration (GPC) prevents an adequate agronomic planning at the farm or consortium level. Although there are many studies on monitoring of crop production and early prediction of yields, little has been done at the local scale. The aim of this study was to assess simplified integration algorithms (SIAs) for integrating remote sensing information with a crop model, to forecast the GPC and grain yield at the field scale. To this end, the CERES‐Wheat model was run to simulate the seasonal average of grain yield (AVE) and GPC in Val d' Orcia (Tuscany Region, Italy) during the 2009–2010 and 2010–2011 growing seasons. The performances of different vegetation indices from MODIS imagery in harvest forecasting were assessed and compared. The SIA formulation was based on the simulated AVE and GPC, and on their spatialization in relation to the intraannual variability between the fields described by vegetation indices. The simulated AVE traced the observed trend. The fraction of absorbed photosynthetically active radiation (fPAR) was the best index in describing grain yield, and the related SIA showed at validation good performance at the field scale ( r 2 = 0.74). Conversely, the SIA was unable to predict GPC due to the low performance of CERES‐Wheat in capturing the interannual variability and to the failure of the fPAR in describing the GPC interfieldsABSTRACT: In the Mediterranean, durum wheat is one of the major crops, but a high variability of grain yield and protein concentration (GPC) prevents an adequate agronomic planning at the farm or consortium level. Although there are many studies on monitoring of crop production and early prediction of yields, little has been done at the local scale. The aim of this study was to assess simplified integration algorithms (SIAs) for integrating remote sensing information with a crop model, to forecast the GPC and grain yield at the field scale. To this end, the CERES‐Wheat model was run to simulate the seasonal average of grain yield (AVE) and GPC in Val d' Orcia (Tuscany Region, Italy) during the 2009–2010 and 2010–2011 growing seasons. The performances of different vegetation indices from MODIS imagery in harvest forecasting were assessed and compared. The SIA formulation was based on the simulated AVE and GPC, and on their spatialization in relation to the intraannual variability between the fields described by vegetation indices. The simulated AVE traced the observed trend. The fraction of absorbed photosynthetically active radiation (fPAR) was the best index in describing grain yield, and the related SIA showed at validation good performance at the field scale ( r 2 = 0.74). Conversely, the SIA was unable to predict GPC due to the low performance of CERES‐Wheat in capturing the interannual variability and to the failure of the fPAR in describing the GPC interfields variability at intermediate canopy reflectance values. … (more)
- Is Part Of:
- Crop science. Volume 55:Issue 3(2015)
- Journal:
- Crop science
- Issue:
- Volume 55:Issue 3(2015)
- Issue Display:
- Volume 55, Issue 3 (2015)
- Year:
- 2015
- Volume:
- 55
- Issue:
- 3
- Issue Sort Value:
- 2015-0055-0003-0000
- Page Start:
- 1280
- Page End:
- 1289
- Publication Date:
- 2015-05-01
- Subjects:
- Crop science -- Periodicals
Cultures -- Périodiques
Cultures de plein champ -- Périodiques
Crop science
Nutzpflanzen
Zeitschrift
Pflanzenbau
Periodicals
633 - Journal URLs:
- http://catalog.hathitrust.org/api/volumes/oclc/1565498.html ↗
https://search.proquest.com/publication/30013 ↗
http://crop.scijournals.org/ ↗
http://link.springer.de/link/service/journals/10088/index.htm ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.2135/cropsci2014.07.0479 ↗
- Languages:
- English
- ISSNs:
- 0011-183X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12970.xml