Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform


Autoria(s): Jensen, T.; Apan, A.; Young, F.; Zeller, L.
Data(s)

01/11/2007

Resumo

A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis and partial least squares regression. A high correlation was found between the image and yield (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.

Identificador

Jensen, T. and Apan, A. and Young, F. and Zeller, L. (2007) Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform. Computers and Electronics in Agriculture, 59 (1-2). pp. 66-77.

http://era.daf.qld.gov.au/1195/

Publicador

Elsevier B.V.

Relação

http://dx.doi.org/10.1016/j.compag.2007.05.004

http://era.daf.qld.gov.au/1195/

Palavras-Chave #Grain. Cereals, Includes oats, maize, corn, barley, rice, sorghum, wheat etc #Remote sensing
Tipo

Article

PeerReviewed