Targeting NIR Tissue Test Sampling Using Aerial Imagery And Identifying The Factors Causing Variable Rice Growth And Crop Yields.

摘要

The new precision agriculture tool, aerial infrared images has created an opportunity for riceudfarmers to assess crop variability. At ground level variability is difficult to assess. Aerialudinfrared images readily show crop variability.udThe images supplied by Terrabyte Services show 5 colour image zones of crop vigour fromudlow vigour to high vigour. The identified zones can show farmers where to sample crops forudthe NIR Tissue Test at panicle initiation. Previously farmers randomly sampled not reallyudknowing whether the sampled areas were really representative of the crop.udThe ability of the aerial images to show crop vigour differences has led to the issue of howudfarmer crops compare to each other and what factors cause variability within crops.udThis project reports on the use of spatial infrared aerial imagery in the rice industry. It reportsudon two sub-projects. The first is the introduction and farmer use and adoption of aerialudinfrared imaging for identifying variability. The second sub-project reports on theudidentification of factors causing crop growth and grain yield variability.udThe outcomes from the first sub-project have been very successful. After the first season thereudwas great feedback. Farmer quotes include:ud“There was more crop variation than I thought”ud“I was surprised by cut and fill areas showing up after 20 years”ud“The aerial images are an excellent tool at PI meetings”ud“The variation is often not due to nitrogen”ud2udOver the first 2 years the number of farmer participants increased from 270 to 549, cropudnumbers from 484 to 834 and crop area from 14000ha to 29500ha. Although the 2005 riceudcrop area was lower at 44,000 ha compared to 65000 ha in the 2004 season, 29000 ha wasudimaged representing 66% of the total area. This compares to 47% in 2003/04.udPerhaps the key outcome from the project is that aerial imagery has been successfully adoptedudby rice farmers and is now seen as an essential tool for improving the management of riceudcrops.udThe second sub-project has shown there is large yield variability and large factor variabilityudwithin crops and between crops. The yield coefficient of variation (CV) of the monitoredudcrops ranged from 4% to 76% in the 2003/04 season. The variation of measured parametersudwithin the one crop eg plant number, water depth, N uptake has been surprisingly high withudthe CV often as high as 60-80%. There is a need to gain an understanding of the reasons forudthis variability which will be the subject of further analysis of the data.udThe future challenge for the rice industry and rice farming systems is to identify all the factorsudcontributing to rice growth and yield variability and finding ways of overcoming theudvariability leading to more uniform and higher yielding crops.