北方农业学报 ›› 2023, Vol. 51 ›› Issue (5): 75-83.doi: 10.12190/j.issn.2096-1197.2023.05.08

• 植物保护 · 园艺 • 上一篇    下一篇

番茄营养成分与感官品质评价指标多元统计分析

赵燕, 邱鹏程, 吴凌波, 王乐, 刘景雷   

  1. 鄂尔多斯市农牧技术推广中心,内蒙古 康巴什 017000
  • 收稿日期:2023-08-29 出版日期:2023-10-20 发布日期:2024-01-04
  • 通讯作者: 邱鹏程(1986—),男,高级农艺师,硕士,主要从事农作物品种选育、推广工作。
  • 作者简介:赵 燕(1984—),女,农艺师,硕士,主要从事农作物新品种、农业技术推广工作。
  • 基金资助:
    鄂尔多斯市蔬菜新品种示范展示和种苗标准化安全生产项目(2022113)

Multivariate statistical analysis of tomato nutrients and sensory quality evaluation

ZHAO Yan, QIU Pengcheng, WU Lingbo, WANG Le, LIU Jinglei   

  1. Ordos Agriculture and Animal Husbandry Technology Promotion Center,Kangbashi 017000,China
  • Received:2023-08-29 Online:2023-10-20 Published:2024-01-04

摘要:

【目的】研究与番茄感官品质评价指标相关的营养成分,建立番茄感官品质简便测定模型。【方法】测定19种番茄的8种营养成分,问卷调查5个感官评价指标,并运用相关性分析、主成分分析、回归分析进行综合评价。【结果】8种营养成分中,除锌以外的7种营养成分与感官品质指标的相关系数均大于0.300。大番茄和樱桃番茄中的可溶性固形物与得分、投票、滋味口感、香气浓郁程度、果肉细腻度、汁水丰沛度的相关系数均大于0.400,相关性稳定而突出;大番茄的可溶性糖与得分、投票、滋味口感、香气浓郁程度均呈显著或极显著正相关,樱桃番茄则相关性不明显;大番茄和樱桃番茄的水分与得分、投票、汁水丰沛度均呈负相关。主成分分析将11个评价指标归纳至3个主成分,累计方差贡献率为74.939%。通过多元线性回归分析得出一个简易模型:番茄感官品质推测得分=93.039-0.304×VC含量-0.179×番茄红素含量-0.621×铁含量+2.314×可溶性固形物含量-1.585×可滴定酸含量。【结论】建立了基于营养成分推断番茄感官品质的快速、简便、定量测定模型。

关键词: 番茄, 营养成分, 感官品质, 多元统计分析

Abstract:

【Objective】Study the relevant nutrients of tomato sensory quality evaluation to establish a simple model for the determination of tomato sensory quality.【Methods】19 tomato varieties were tested for 8 nutrients,and 5 sensory evaluation indexes were investigated by questionnaires. Correlation analysis,principal component analysis (PCA) and regression analysis were used for comprehensive evaluation.【Results】Except zinc,7 of the 8 nutrients had correlation coefficients greater than 0.300 with sensory quality. The correlation coefficients between soluble solid and score,vote,taste,aroma intensity,pulp texture,and juice abundance in both large and cherry tomatoes were greater than 0.400,and the correlations were stable and prominent. Soluble sugar was significantly or extremely significantly positively correlated with score,vote,taste and aroma intensity in large tomatoes,while the correlation were not obvious in cherry tomatoes. Water content was negatively correlated with score,vote,and juice abundance in both large and cherry tomatoes. Principal component analysis summarized the 11 evaluation indicators into 3 principal components,with an accumulated variance contribution rate of 74.939%. A simple model was obtained through multivariate linear regression analysis:tomato sensory quality predicted score =93.039-0.304 × vitamin C content -0.179 × lycopene content -0.621 × iron content +2.314 × soluble solid content -1.585 × titratable acid content.【Conclusion】A rapid,simple and quantitative determination model of tomato sensory quality based on nutrients was established.

Key words: Tomato, Nutrient, Sensory quality, Multivariate statistical analysis

中图分类号: 

  • S614.2