Optimizing pollencounter for high throughput phenotyping of pollen quality in tomatoes

Abstract

The macro “PollenCounter” in ImageJ was initially developed to assess pollen viability in grapevine. We set out to see if PollenCounter could be used to assess pollen number and viability in tomatoes. • We tested different optimization scenarios by adjusting the pollen size (100–900, 200–900 pixel2) and circularity of pollen grains (0.4–1, 0.5–1, and 0.6–1) on 31 microscopic images of stained tomato pollen. Both total pollen number and proportion of viable pollen were positively and significantly correlated with the outputs from manual counting. The scenario with 100–900 pixel2 pollen size and 0.4–1 circularity had the highest association for pollen number (r = 0.99) and pollen viability (r = 0.86). PollenCounter is 32-fold faster than manual counting. • We added a command to the macro to automatically save the outputs containing the number of total and viable pollen, avoiding transcription errors inherent to manual counting. • We successfully applied the optimized PollenCounter to discriminate tomato genotypes based on pollen number and pollen viability under heat stress. Our results show that PollenCounter, as an open-access macro, can be customized and improved to meet users’ needs. The use of PollenCounter can save time and money in pollen quality assessment. We outline the steps to optimize the macro for other samples or crop species. The optimized macro could allow efficient screening of a large germplasm collection for pollen thermo-tolerance and selection of best thermo-tolerant individuals in breeding programs.

Keywords

• Heat-tolerance
• ImageJ
• Solanum lycopersicum
• Pollen viability