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宁县黄甘桃果实品质综合评价

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[目的]比较分析不同宁县黄甘桃品种(系)果实品质差异,筛选具有代表性的品质指标,建立果实品质评价体系和预测模型,为宁县黄甘桃品质科学评价和优系筛选提供依据.[方法]以17份宁县黄甘桃种质资源和锦绣黄桃(对照)果实为材料,分析测定14项品质指标,运用系统性描述、相关性分析、因子分析对18份材料的品质进行综合评价并排序,通过聚类分析对18份材料的品质进行分类,通过回归分析得到宁县黄甘桃果实品质预测模型和核心指标.[结果]17份宁县黄甘桃果实品质指标变异系数分布在6.53%~98.15%之间,其中色泽指数(CCI)变异系数最大,单宁含量变异系数最小.各品质指标间存在不同程度的相关性.主成分分析提取了6个主成分,累计贡献率达到87.06%,建立了综合评价模型,并依据各品系(种)的综合得分进行优良度排序.应用逐步回归分析建立宁县黄甘桃鲜食品质预测模型,筛选出4项指标可作为宁县黄甘桃品质评价的核心指标.聚类分析将18份试材分为4类.[结论]主成分分析结合回归分析筛选出可溶性固形物含量、糖酸比、单宁含量和固酸比可作为宁县黄甘桃的品质评价核心指标,品质预测模型可简化果实品质评价工作;主成分分析结合聚类分析筛选出宁黄1号、宁黄18号和宁黄19号为优良宁县黄甘桃品系,两种方法相结合使评价结果更科学、合理.研究结果将为宁县黄甘桃的地方品种的开发和利用提供依据.
Comprehensive evaluation of the fruit quality of yellow-flesh peaches in Ningxian
[Objective]The fruit quality of yellow-flesh peaches in Ningxian county was evaluated com-prehensively to explore a quality evaluation system,a prediction model and core indicators were ob-tained for scientifically evaluating the quality and selecting excellent resources of Ningxian yellow-flesh peach.[Methods]Using 17 Ningxian yellow-flesh peach resources and Jinxiu yellow-flesh peach as the test materials for determining the fruit appearance quality and 14 other quality indexes.The 14 quality indexes included single fruit mass,fruit shape index,fruit color values,soluble solids content,sweetness value,titratable acidity,soluble sugar,solid acid ration,sugar acid ration,carotenoid,vitamin C,tannin content and anthocyanin.The quality of 18 resources was comprehensively evaluated and ranked using systematic description,correlation analysis,factor analysis and cluster analysis.Through regression analysis,we obtained the prediction model and core indicators for the fresh food quality of Ningxian yellow-flesh peach.[Results]In fruit apparance quality,the single fruit mass ranged from 69.80 to 254.68 g,the highest was Ninghuang No.1,while the lowest was Ninghuang No.2.The fruit shape index ranged from 0.88 to 1.19,and Ninghuang No.2 was the highest and Ninghuang No.32 was the lowest.In fruit coloration,all materials,except for Ninghuang No.7,exhibited positive values.Nin-ghuang No.7 had a greenish hue with a negative CCI value(-2.92).Ninghuang No.5 had the highest CCI value of 19.97,indicating a more pronounced yellow color.Comparatively,the single fruit mass of Jinxiu was slightly lower than that of Ninghuang No.1,but it had a higher fruit shape index of 0.95.The CCI value of Jinxiu was slightly higher than that of Ninghuang No.7.In fruit flavor quality,Ning-huang No.2,Ninghuang No.19,Jinxiu,Ninghuang No.1 and Ninghuang No.14 had the highest solu-ble total sugar content in the range of 9.015 to 9.589.Ninghuang No.2,Jinxiu,Ninghuang No.1 and Ninghuang No.18 had the highest sweetness values in the range from 101.48 to 105.06.The titratable acids of the fruit ranges from 0.37%to 0.60%,Ninghuang No.15 was the highest,up to 0.603%.The solid acid ratio and sugar acid ratio of Ninghuang No.18 were the highest,and those of Ninghuang No.15 were the lowest.Ninghuang No.19 had the highest tannin content,reaching 991.70µg·g-1,Ning-huang No.14 had the lowest tannin content at 797.90µg·g-1.The anthocyanins of Ninghuang No.15 was the highest.The variation coefficients of 17 Ningxian yellow-flesh peach fruit quality indicators ranged from 6.53%to 98.15%,the highest was found in CCI,while the lowest was in tannin content.The coefficients of variations for the fruit shape index,soluble solids content,sweetness value,soluble total sugar,tannin and anthocyanin were relatively small,all below 10%.The coefficients of variations for titratable acidity,solid acid ratio,sugar acid ratio and vitamin C were relatively small,all below 20%.The coefficients of variations for single fruit mass and polyphenols were moderate,both below 30%.The coefficients of variatiosn for CCI were relatively large,and was 98.15%,indicating that this factor could be considered as key indicator.There were different degrees of correlation between the vari-ous quality indicators.The CCI,carotenoid and anthocyanins showed certain correlations with other in-dicators,although they did not reach a significant level.This suggests that they would be relatively inde-pendent and less influenced by other factors.There was a significant negative correlation between the fruit shape index and single fruit quality,and a significant positive correlation with the content of tan-nins;There was a significantly positive correlation between the soluble solids,sweetness value,and to-tal soluble sugar.There was a highly significantly positive correlation between the sweetness value and total soluble sugar content.There was a highly significantly negative correlation between the titratable acid and sugar acid ratio and solid acid ratio.There was a significantly negative correlation between the vitamin C and Zn,indicating that the changes in vitamin C content in fruit pulp might be influenced by the level of Zn content.The factor analysis extracted six principal components with a cumulative contri-bution rate of 87.06%,being used to establish a comprehensive evaluation model and ranking the quali-ty of each strain(species)based on their comprehensive scores.Using the stepwise regression analysis,a prediction model for the quality of fresh peaches was established,and four indicators were screened as the core indicators for evaluating the quality of peaches.The cluster analysis divided the test materi-als into four categories.[Conclusion]The soluble solids content,sugar acid ration,tannin content and solid acid ratio were selected as core indicators for quality evaluation of Ningxian yellow-flesh peaches through the PCA combined with regression analysis.The quality prediction model could simplify fruit quality evaluation work;Ninghuang No.18,Ninghuang No.1,and Ninghuang No.19 were selected as excellent Ningxian yellow-flesht peach varieties through the PCA combined with cluster analysis.The combination of the two methods would make the evaluation results more scientific and reasonable.The above research results would provide a basis for the development and utilization of Ningxian yellow-flesh peach.

Ningxian yellow-flesh peachFruit qualityPCAComprehensive evaluation

张彦山、肖正璐、顾群英、豆丽萍、何博

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庆阳市农业科学研究院,甘肃庆阳 745000

宁县黄甘桃 果实品质 主成分分析 综合评价

甘肃省科学技术厅民生科技专项

21CX6NM269

2024

果树学报
中国农业科学院郑州果树研究所

果树学报

CSTPCD北大核心
影响因子:1.486
ISSN:1009-9980
年,卷(期):2024.41(1)
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