Optimizing pollencounter for high throughput phenotyping of pollen quality in tomatoes

Area of Science:

• Plant Science
• Agricultural Technology
• Bioinformatics

Background:

• The ImageJ macro PollenCounter was developed for grapevine pollen viability assessment.
• Tomato pollen analysis requires efficient methods for quantifying pollen number and viability.

Purpose of the Study:

• To evaluate and optimize the PollenCounter macro for assessing tomato pollen number and viability.
• To compare the macro's performance against manual counting methods.

Main Methods:

• Optimized PollenCounter parameters for pollen size (100-900 pixel²) and circularity (0.4-1).
• Analyzed 31 microscopic images of stained tomato pollen.
• Validated results by comparing macro output with manual counts.

Main Results:

• Optimized PollenCounter showed high correlation with manual counts for pollen number (r=0.99) and viability (r=0.86).
• The macro is 32 times faster than manual counting.
• Successfully discriminated tomato genotypes based on pollen traits under heat stress.

Conclusions:

• PollenCounter can be customized for efficient pollen quality assessment in tomatoes and other crops.
• The optimized macro facilitates rapid screening of germplasm for pollen thermotolerance.
• This tool can reduce time and cost in plant breeding programs.