The anatomy of petal drop in sunflowers

Study finds cell division at abscission zone of short-lived cultivar occurs earlier than in long-lived variety

ITHACA, NY - Despite their consumer popularity as cut flowers, some sunflowers are difficult to market because of their tendency to lose petals soon after their flowers open. This characteristic, "petal drop", which in some varieties can occur within a day of the flowers' opening, ruins the appearance of sunflowers and damages their market value. Sunflower growers interested in finding cultivars that are less prone to this condition have had limited information about petal drop, but a new study in the Journal of the American Society for Horticultural Science contains findings can inform both sunflower breeding programs and consumers' choices.

Joyous Suiyigheh Tata and Hans Christian Wien from the Department of Horticulture at Cornell University studied the abscission zone, a differentiated region where petal drop initiates, at the base of petals of sunflower florets in two different cultivars. "We wanted to determine if differences in the abscission zone among sunflower cultivars were correlated with differences in timing of petal drop," the authors said. Two pollen-free hybrid sunflower cultivars were selected for evaluation: Procut Bicolor, which loses its petals easily, and Procut Yellow Lite, which holds its petals much longer.

For the first experiment, the researchers measured separation force for the two sunflower cultivars using a modified soil cone micropenetrometer, an apparatus that measures separation forces in the opposite direction. "The separation force experiments showed that detachment forces switched from an initial high to low in both cultivars because of the maturation of the separation layer. This maturation occurred earlier in the cultivar that is first to lose its petals (Procut Bicolor)," the authors said. They noted that there were no force readings for the short-lived cultivar on day 9 and day 12 because the flower had already wilted.

"In the second experiment, we studied the changes in the anatomy of the petal-achene juncture of the two cultivars," the scientists explained. Three stages from Procut Bicolor (PBC) and four stages from Procut Yellow Lite (PYL) were studied. These stages represent a time course with physiological relevance; when the flower just opens (anthesis), 8 days (the end of flower life for PBC), and 12 days (the end of flower life for PYL). The study also included analyses of petal anatomy at 4 days after harvest. The "end of flower life" was defined as the time when detachment force equals zero; when simply touching the petals caused them to fall off easily. Results of the analyses showed that cell division at the abscission zone of the short-lived cultivar occurred earlier than in the long-lived cultivar. "These results reveal that there was a difference in timing in the formation and maturation of the separation layer between the two cultivars," the authors said.

Interestingly, analyses showed that the mean "break strength" of cultivars in the yellow group was higher and significantly different from cultivars in the orange and bicolor groups, which were in turn higher than cultivars in the red group. Mean vase life (12 days) of the sunflowers in the yellow group was longer than cultivars in the orange group (10 days), while the vase life of the orange group was longer than cultivars in the bicolor group (9 days). The vase life of the red cultivars was shortest at 8 days. "We found that vase life has a strong relationship with flower color; the darker cultivars in the study had a shorter vase life compared with the lighter cultivars," the scientists remarked.

"The anatomy of petal drop in sunflower is similar to the majority of established descriptions in other species; the process involves the separation of four to five rows of smaller transversely oriented cells that lay horizontally across the diameter at the juncture between the petal and the achene, the separation layer," the authors said. "The concept that the timing of the maturation of the separation layer in the abscission zone helps determine the timing of petal drop is strongly supported by both the physical and anatomical investigations."

The authors concluded that the regression equation and results from the petal detachment force experiments can be used to screen sunflower cultivars in order to determine groupings of short-lived vs. long-lived cultivars. They said that the study contains beneficial information for sunflower breeding programs working to improve the breed's longevity, which can ultimately lead to increased sunflower sales.

Source: ASHS

Statistical model predicts performance of hybrid rice

Long-grain rice

Genomic prediction, a new field of quantitative genetics, is a statistical approach to predicting the value of an economically important trait in a plant, such as yield or disease resistance. The method works if the trait is heritable, as many traits tend to be, and can be performed early in the life cycle of the plant, helping reduce costs.

Now a research team led by plant geneticists at the University of California, Riverside and Huazhong Agricultural University, China, has used the method to predict the performance of hybrid rice (for example, the yield, growth-rate and disease resistance). The new technology could potentially revolutionize hybrid breeding in agriculture.

The study, published online in the Proceedings of the National Academy of Sciences, is a pilot research project on rice. The technology can be easily extended, however, to other crops such as maize.

"Rice and maize are two main crops that depend on hybrid breeding," said Shizhong Xu, a professor of genetics in the UC Riverside Department of Botany and Plant Sciences, who co-led the research project. "If we can identify many high-performance hybrids in these crops and use these hybrids, we can substantially increase grain production to achieve global food security."

Genomic prediction uses genome-wide markers to predict future individuals or species. These markers are genes or DNA sequences with known locations on a chromosome. Genomic prediction differs from traditional predictions in that it skips the marker-detection step. The method simply uses all markers of the entire genome to predict a trait.

"Classical marker-assisted selection only uses markers that have large effects on the trait," Xu explained. "It ignores all markers with small effects. But many economically important traits are controlled by a large number of genes with small effects. Because the genomic prediction model captures all these small-effect genes, predictability is vastly improved."

Without genomic prediction, breeders must grow all possible crosses in the field to select the best cross (hybrid). For example, for 1000 inbred parents, the total number of crosses would be 499500.

"It is impossible to grow these many crosses in the field," Xu said. "However, with the genomic prediction technology, we can grow only, say, 500 crosses, then predict all the 499500 potential crosses, and select the best crosses based on the predicted values of these hybrids."

Xu noted that genomic prediction is particularly useful for predicting hybrids because hybrid DNA sequences are determined by their inbred parents.

"More cost-saving can be achieved because we do not need to measure the DNA sequences of the hybrids," he said. "Knowing the genotypes of the parents makes it possible to immediately know the genotype of the hybrid. Indeed, there is no need to measure the genotype of the hybrid. It is fully predicted by the model."

When the researchers incorporated "dominance" and "epistasis" into their prediction model, they found that predictability was improved. In genetics, dominance describes the joint action of two different alleles (copies) of a gene. For example, if one copy of a gene has a value of 1 and the other copy has a value of 2, the joint effect of the two alleles may be 4, indicating that the two alleles are not additive. In this case, dominance has occurred. Epistasis refers to any type of gene-gene interaction.

"By incorporating dominance and epistasis, we took into account all available information for prediction," Xu said. "It led to a more accurate prediction of a trait value."

Genomic prediction can be used to predict heritable human diseases. For example, many cancers are heritable and genome prediction can be performed to predict disease risk for a person.

Xu was joined in the research by Qifa Zhang and his student Dan Zhu at Huazhong Agricultural University, China.

Next the research team, led by Xu and Zhang, will design a field experiment to perform hybrid prediction in rice.

Source: University of California - Riverside