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Implementation and Evaluation of an Image Analysis System for Determining Viability of Pollen Grains in Temperate Rice
- Ortega B, Rodrigo, Aresti E, Macarena, Pereira R, Iris
- Chilean journal of agricultural research 2011 v.71 no.1 pp. 16-22
- Oryza sativa, air, air temperature, anthers, breeding programs, climatic factors, computer software, field experimentation, flowering, image analysis, panicles, pollen, rice, spikelets, viability, water temperature, Chile
- Geographical and climatic factors limit the production of temperate rice (Oryza sativa L.) in Chile. Large thermal fluctuations of air and water temperatures affect the viability of pollen, causing high levels of spikelet sterility ("blanking"), resulting in reduced yields per hectare. Counting viable pollen grains, at the time of anthesis, may allow determining, ahead, whether there will be yield losses by spikelet sterility; besides, knowing the potential pollen viability serves as a powerful tool for material selection in breeding programs, and for determining which management factors may influence "blanking". If performed manually, counting total and viable pollen grains can be extremely tedious, producing highly variable results. The present work had for objectives to develop and evaluate a system, based on imagery analysis, for counting total and viable pollen in rice anthers. At the time of anthesis, three panicles were collected from plot treatments of two field experiments in which the effects of different management factors (variety, water height, N rate, and spatial arrangement) on spikelet sterility were evaluated. Two spikelets and four anthers were sampled from each panicle; pollen grains were extracted from anthers and photographed. Manual and digital counts were made on the images to determine total and viable pollen. Digital count was performed with the software SigmaScan Pro, setting some parameters on the imagery before counting. Precision and accuracy of the digital method were estimated. The results indicated that the digital pollen count showed a very good precision and accuracy and could be used to estimate pollen viability, and as a response variable to compare management treatments.