基于因子分析的6个大果沙枣新品种果实性状综合评价

Comprehensive evaluation of fruit quality traits of six new Elaeagnus moorcroftii varieties based on factor analysis

【目的】探索一套适合新疆大果沙枣果实品质的评价方法,为大果沙枣优良品种选育及产业发展提供科学理论依据。【方法】以6个大果沙枣新品种为试验材料,对30项果实品质指标进行测定,并采用隶属函数法、因子分析和主成分分析进行综合评价。【结果】6个新疆大果沙枣新品种30项果实品质性状各指标变异系数在2.656%~97.165%。变异系数最大的是原花青素含量(97.165%),其次为钙含量(67.785%),变异系数最小的为可食率(2.656%)。经因子分析提取出3个特征值大于1的公因子,累积贡献率达93.396%。第1主成分的贡献率为40.728%,主要代表单果质量及水分、总糖、粗纤维、单宁、总酚含量6项指标的信息;第2主成分的贡献率为38.214%,主要代表还原糖、多糖、总氨基酸、蛋白质、总黄酮、全P和铜含量;第3主成分的贡献率为14.454%,主要代表总酸和脂肪含量。【结论】综合评价得出红玉得分最高,白沙甜次之;雅丰第3。研究结果为科学评价新疆大果沙枣果实品质及推广优良品种提供理论依据。

【Objective】The purpose of this study is to provide a scientific basis for the breeding and industrial development of superior large-fruit jujube(Ziziphus jujuba)varieties in Xinjiang and to explore a suitable method for evaluating the fruit quality of large-fruit jujubes.【Methods】Six new large-fruit jujube varieties were used as experimental materials to measure 30 fruit quality indicators(individual fruit weight,flesh recovery,moisture content,soluble solids,total acid,total sugars,reducing sugars,glucose,fructose,starch,polysaccharides,total amino acids,vitamin C,protein,fat,crude fiber,tannin,total flavonoids,total phenols,proanthocyanidins,total alkaloids,ash,Na,K,Ca,Mg,Fe,Mn,Zn and Cu).Subordinate function method,factor analysis,and principal component analysis were used for comprehensive evaluation.【Results】The coefficient of variation for the 30 fruit quality traits of the six new Xinjiang large-fruit jujube varieties ranged from 2.656%to 97.165%.The highest variability was in proanthocyanidins(97.165%)and calcium(67.785%),indicating significant differences among varieties in these two components.The variation was less than 10%for moisture content,soluble solids,total sugars,reducing sugars,fructose,starch,polysaccharides,total alkaloids,and copper,indicating low dispersion and relatively consistency of these parameters among varieties.The smallest coefficient of variation was found in flesh recovery(2.656%).The 30 fruit quality traits showed varying degrees of positive and negative correlations.Among them,reducing sugars and total sugars had a very significant positive correlation;starch and individual fruit weight had a significant negative correlation;polysaccharides and total acids had a significant positive correlation;total amino acids had a significant negative correlation with moisture content and significant positive correlations with total acids,total sugars,and reducing sugars;proteins had a significant positive correlation with total acids,a very significant positive correlation with total amino acids,and a very significant negative correlation with moisture content;fat had a very significant negative correlation with polysaccharides;crude fiber had significant positive correlations with total acids and proteins,a very significant positive correlation with total amino acids,and a significant negative correlation with moisture content;tannins had significant negative correlations with reducing sugars,total amino acids,and proteins,and a very significant negative correlation with soluble solids;total flavonoids had a significant positive correlation with tannin;total phenols had significant negative correlations with soluble solids,total amino acids,and proteins,a significant positive correlation with total flavonoids,and a very significant positive correlation with tannins;proanthocyanidins had a significant positive correlation with total flavonoids,a very significant positive correlation with tannins and total phenols,and a significant negative correlation;potassium had significant positive correlations with soluble solids,total amino acids,and proteins,a very significant positive correlation with crude fiber,and a very significant negative correlation with moisture content;magnesium had significant positive correlations with total acids,total amino acids,proteins,and total phosphorus;manganese had a significant positive correlation with calcium;zinc had a very significant positive correlation with starch;copper had a very significant positive correlation with fat and a significant negative correlation with polysaccharides.In the comprehensive evaluation of jujube fruit quality,which is better as the sensory indicators,such as individual fruit weight,flesh recovery,moisture content,and nutritional indicators,such as total sugars,reducing sugars,glucose,fructose,starch,polysaccharides,total amino acids,vitamin C,proteins,fat,total flavonoids,proanthocyanidins,total alkaloids,ash,total phosphorus,potassium,calcium,magnesium,iron,manganese,zinc,and copper become higher values and total acids,crude fiber,tannins,and total phenols become lower,the subordinate function method was used to standardize the data for factor analysis.Principal component analysis was employed to simplify the plethora of raw information into a few synthetic variables for comprehensive evaluation,and five common factors with eigenvalues greater than 1.0 were extracted through factor analysis,accounting for 10%of the cumulative contribution rate,representing the 30 fruit quality indicators of the six types of large-fruit jujube,which can be used as indicators for the comprehensive evaluation of the fruit quality.Within the first principal component(F1)synthesized from 16 indicators(moisture content,soluble solids,total acid,total sugars,reducing sugars,polysaccharides,total amino acids,protein,fat,crude cellulose,tannins,total phenols,total phosphorus,potassium,magnesium,and copper),moisture content,fat,and copper had the greatest weight.The second principal component(F2)was synthesized from 7 indicators:individual fruit weight,fresh recovery rate,glucose,fructose,vitamin C,calcium,and iron,with individual fruit weight and fresh recovery having the greatest weight.The third principal component(F3)included 4 indicators:starch,total flavonoids,proanthocyanidins,and zinc,with starch and proanthocyanidins and weight having the greatest weight.【Conclusion】The results of the study show that the quality of large-fruit jujube can be comprehensively evaluated with a set of factors,including external sensory indicators and nutritional indicators.The use of subordinate function method and principal component analysis provides a systematic approach to the evaluation of fruit quality traits,allowing for the identification of superior varieties and the improvement of breeding programs.The study also highlights the importance of obtaining a wide range of quality traits,as they are interrelated and can affect the overall quality of the fruit.The findings can guide the selection of large-fruit jujube varieties with high fruit quality for consumers and the industry,and support the development of new varieties with better quality traits.