New cotton grading score app aims to improve yield stability

Fred Bourland has another score to settle with cotton, and this time it’s coming with a technical punch.

The professor of plant breeding and genetics for the Arkansas Agricultural Experiment Station is working on his third cotton grading score to help cotton breeders in their unceasing selection process to maintain and improve cotton varieties. The experiment station is part of the University of Arkansas System Division of Agriculture.

Following development of the Q-Score for fiber quality and the S-Score to characterize optimal seed and lint indices into a single index, the 50-year veteran of cotton breeding is on the verge of finalizing a new scoring system to add to breeders’ toolboxes for evaluating potential cotton varieties.

YIELD SCORE — Fred Bourland’s Yield Component Score is being developed into an app with Cotton Incorporated to help cotton breeders and growers improve yield stability. (U of A System Division of Agriculture photo by Paden Johnson)

The Yield Component Score, or YC-Score for short, represents how much a cotton variety favors lint production relative to seed production to produce lint yield.

″If the cotton line has a high YC-Score, then it’s relying more on lint per seed rather than seed per acre, which is more favorable because the production of lint requires less plant energy than the production of seed,″ Bourland said.

Cotton lint yield is equal to the number of seeds per acre multiplied by the weight of lint per seed. Lint yield may be improved by increasing either seeds per acre or the weight of lint per seed, but Bourland noted the latter is more efficient by requiring less plant energy to increase, and has a higher heritability. In other words, cotton breeders can more easily carry lint per seed characteristic forward through variety selection.

Bourland is working in partnership with Cotton Incorporated to release an app for breeders to calculate the YC-Score.

A long labor of love

The YC-Score app is made possible after 20 years of documenting cotton lines that have a higher lint index relative to seeds per acre. Bourland said the program was validated by having a strong association between the objective YC-Scores generated by the program and the subjective yield component rating generated by his team for cotton lines in different tests and years. Criteria included lint yield, seed per acre and lint index.

The YC-Score app is still under development but is expected to be released by Cotton Inc. in the coming year, along with an associated publication.

Analyzing their high-performing varieties, breeders may use the YC-score to differentiate those that produce lint more efficiently, which should lead to high yield stability. Bourland explained that as a general rule, lower yielding lines often have high yield stability, but breeders want to identify lines that produce high yields and rely more on lint index than on seed per acre.

″The way the app works is that you find lines that are good yielding, then see how they’re getting their yield — that’s what the YC-Score will tell you,″ Bourland said.