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|Title:||Targeting NIR Tissue Test Sampling Using Aerial Imagery And Identifying The Factors Causing Variable Rice Growth And Crop Yields.|
|Series/Report no.:||Program 5|
|Abstract:||The new precision agriculture tool, aerial infrared images has created an opportunity for rice farmers to assess crop variability. At ground level variability is difficult to assess. Aerial infrared images readily show crop variability. The images supplied by Terrabyte Services show 5 colour image zones of crop vigour from low vigour to high vigour. The identified zones can show farmers where to sample crops for the NIR Tissue Test at panicle initiation. Previously farmers randomly sampled not really knowing whether the sampled areas were really representative of the crop. The ability of the aerial images to show crop vigour differences has led to the issue of how farmer crops compare to each other and what factors cause variability within crops. This project reports on the use of spatial infrared aerial imagery in the rice industry. It reports on two sub-projects. The first is the introduction and farmer use and adoption of aerial infrared imaging for identifying variability. The second sub-project reports on the identification of factors causing crop growth and grain yield variability. The outcomes from the first sub-project have been very successful. After the first season there was great feedback. Farmer quotes include: “There was more crop variation than I thought” “I was surprised by cut and fill areas showing up after 20 years” “The aerial images are an excellent tool at PI meetings” “The variation is often not due to nitrogen” 2 Over the first 2 years the number of farmer participants increased from 270 to 549, crop numbers from 484 to 834 and crop area from 14000ha to 29500ha. Although the 2005 rice crop area was lower at 44,000 ha compared to 65000 ha in the 2004 season, 29000 ha was imaged representing 66% of the total area. This compares to 47% in 2003/04. Perhaps the key outcome from the project is that aerial imagery has been successfully adopted by rice farmers and is now seen as an essential tool for improving the management of rice crops. The second sub-project has shown there is large yield variability and large factor variability within crops and between crops. The yield coefficient of variation (CV) of the monitored crops ranged from 4% to 76% in the 2003/04 season. The variation of measured parameters within the one crop eg plant number, water depth, N uptake has been surprisingly high with the CV often as high as 60-80%. There is a need to gain an understanding of the reasons for this variability which will be the subject of further analysis of the data. The future challenge for the rice industry and rice farming systems is to identify all the factors contributing to rice growth and yield variability and finding ways of overcoming the variability leading to more uniform and higher yielding crops.|
|Type of Work:||Other|
|Appears in Collections:||Research Papers|
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