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Title: Cultivar evaluation and essential test locations identification for sugarcane breeding in China

Author
item LUO, JUN - FUJIAN AGRICULTURAL & FORESTRY UNIVERSITY
item Pan, Yong-Bao
item XU, LIPING - FUJIAN AGRICULTURAL & FORESTRY UNIVERSITY
item ZHANG, HUA - FUJIAN AGRICULTURAL & FORESTRY UNIVERSITY
item YUAN, ZHAONIAN - FUJIAN AGRICULTURAL & FORESTRY UNIVERSITY
item DENG, ZUHU - FUJIAN AGRICULTURAL & FORESTRY UNIVERSITY
item CHEN, RUKAI - FUJIAN AGRICULTURAL & FORESTRY UNIVERSITY
item QUE, YOUXIONG - FUJIAN AGRICULTURAL & FORESTRY UNIVERSITY

Submitted to: The Scientific World
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/1/2014
Publication Date: 5/20/2014
Publication URL: https://handle.nal.usda.gov/10113/58976
Citation: Luo, J., Pan, Y.-B., Xu, L., Zhang, H., Yuan, Z., Deng, Z., Chen, R., Que, Y. 2014. Cultivar evaluation and essential test locations identification for sugarcane breeding in China. The Scientific World Journal. 2014:1-10. Article ID 302753. DOI: 10.1155/2014/302753.

Interpretive Summary: Due to high genetic complexity of the crop and extreme level of gene x environment interaction, sugarcane breeders need to conduct variety evaluation tests in several years and across multiple locations to obtain critical data for variety release recommendations. The traditional statistical model relies on two-way data, which tends to overlook either high yielding but poor stability varieties or low yielding but highly stable varieties. The model often encounters more difficulty when dealing with varietal data obtained under hazardous climate conditions such as severe drought, cold, and tropical storm. To circumvent this problem, a new method called genotype main effect plus genotype-environment interaction (GGE) biplot, which has been a proven useful tool on many crops, is introduced to analyze sugarcane evaluation data of both plant cane and first ratoon crop from the 8th Chinese National Sugarcane Varietal Area Trials Program. Six varieties were evaluated at seven locations in two major sugarcane production provinces, Guangxi and Yunnan. Based on GGE-Biplot analysis, variety FN38 ranked the first in sugar yield and the second in cane yield. The variety was also stable in sugar production. Variety GAN02-70 had lower sugar yield but high stability. Variety YZ06-407 had a relatively high but less stable sugar yield as a result of very high cane yield. Varieties YZ05-51 and LC03-1137 also had high but less stable sugar yield. Variety FN39 had stable high sugar yield with less stable cane yield, especially in the ratoon crops. It has been demonstrated that the GGE-Biplot program can be used to determine both yielding ability and stability over all test sites of sugarcane varieties in multi-year and multi-location varietal trials.

Technical Abstract: Using a genotype main effect plus genotype-environment interaction (GGE) biplot software, the yield performance data of seven sugarcane cultivars in the 8th Chinese National Sugarcane Area Trials were analyzed to identify cultivars recommended for commercial release. Cultivar FN38 produced a high and stable sugar yield. GAN02-70 had the lowest cane yield with high stability. YZ06-407 was a high cane yield cultivar with poor stability in sugar yield. YZ05-51 and LC03-1137 were unstable, relatively high sugar yielding cultivars. FN39 yielded stable high sugar with low and unstable cane production. Significantly different sugar and cane yields were encountered across seasons due to strong cultivar-environment interactions. Three areas, including Guangxi Chongzuo, Guangxi Baise, Guangxi Hechi, showed better representativeness of cane and sugar yields than the other four areas. On the other hand, areas Guangxi Chongzuo, Yunnan Lincang, and Yunnan Baoshan showed strong discrimination ability, while areas Guangxi Hechi and Guangxi Liuzhou showed poor discrimination ability. It is concluded that the GGE-Biplot software is an intuitive and effective tool for evaluating yielding ability and stability of sugarcane cultivars in multi-area varietal trials.