中国农业科学 ›› 2023, Vol. 56 ›› Issue (15): 3006-3019.doi: 10.3864/j.issn.0578-1752.2023.15.014

• 园艺 • 上一篇    下一篇

基于多种方法的菠萝果实质地及食味品质综合评价

付山1,2(), 梁邺1,2, 徐玖亮3, 阮云泽1,2, 罗剑4, 李婷玉1,2()   

  1. 1 海南大学三亚南繁研究院,海南三亚 572000
    2 海南大学热带作物学院,海口 570208
    3 中国农业大学资源与环境学院,北京 100083
    4 海南天地人生态农业股份有限公司,海口 570100
  • 收稿日期:2022-10-27 接受日期:2022-12-28 出版日期:2023-08-01 发布日期:2023-08-05
  • 通信作者:
    李婷玉,E-mail:
  • 联系方式: 付山,E-mail:18271660293@163.com。
  • 基金资助:
    海南省院士工作站(SQ2019ysgzz0037); 海南省重点研发计划-菠萝种质资源收集; 鉴定及优良品种绿色栽培技术研究(ZDYF2021XDNY117); 共建绿色凤梨品牌及创新型人才培育合作协议(RH2100006535); 海南高附加值作物专用肥开发及示范(RH2200004932)

Comprehensive Evaluation of Fruit Texture and Taste Quality of Pineapple Based on Multiple Methods

FU Shan1,2(), LIANG Ye1,2, XU JiuLiang3, RUAN YunZe1,2, LUO Jian4, LI TingYu1,2()   

  1. 1 College of Sanya Nanfan Research Institute, Hainan University, Sanya 572000, Hainan
    2 College of Tropical Crops, Hainan University, Haikou 570208
    3 College of Resources and Environmental Science, China Agricultural University, Beijing 100083
    4 Hainan Tiandiren Ecological Agriculture Co., LTD, Haikou 570100
  • Received:2022-10-27 Accepted:2022-12-28 Published:2023-08-01 Online:2023-08-05

摘要:

【目的】 本研究基于多种研究方法,阐明影响菠萝感官品质的关键质构和理化指标,建立菠萝果实质地及食味品质的综合评价方法,为优良菠萝品种的筛选提供科学支撑。【方法】 以7个不同品种的菠萝果实为研究对象,采用感官评价、质构测试和理化分析等方法,结合方差分析和不同维度指标间的相关性分析,明确影响菠萝感官总分的关键质构、理化指标,并进一步采用主成分回归分析法,以筛选出的关键质构特性、理化指标为自变量,感官评价总分为因变量进行回归分析,得到具有统计学意义的预测模型,用于菠萝质地及食味品质综合评价。【结果】 不同品种菠萝部分质构属性及理化指标存在较大的差异,如硬度、咀嚼性、最大剪切力、糖酸比、可溶性蛋白、维生素C及可溶性果胶等在品种间的变异系数均大于25%,而弹性、凝聚性等在品种间的变异较小。不同品种菠萝感官总分从高到低依次为‘台农17号'>‘台农16号'>‘台农4号'>‘金菠萝'>‘台农11号'>‘无刺卡因'>‘巴厘',‘台农17号'的果实质地和食味品质最佳,其固形物含量为16.23%,糖酸比为31.82,可溶性果胶含量为23.72 mg∙g-1,咀嚼性为789.77 mJ,硬度和最大剪切力分别为1 826.55 N、3 491.37 N。相关性分析表明,影响感官总分的关键指标包括质构属性中的硬度、咀嚼性、最大剪切力和理化指标中的可溶性固形物、糖酸比及可溶性果胶。利用主成分回归分析方法建立的菠萝感官预测模型决定系数R 2为0.916,标准偏差为0.11。【结论】 菠萝品种间质地与食味品质差异大,采用单一评价方法不能准确评价各品种菠萝质地与食味品质。本研究明确了影响整体感官满意度的6个关键分析指标,并建立了基于关键质构和理化指标的菠萝感官预测模型,可以较准确地预测菠萝的质地与食味品质,以弥补人工感官分析中客观性不足的缺陷。

关键词: 菠萝, 感官评价, 质构属性, 理化成分, 相关性分析

Abstract:

【Objective】 This study adopted different methodologies to identify the key texture characteristics and physicochemical indexes affecting the total sensory quality of pineapple (Ananas comosus (Linn.) Merr.), and to establish a new comprehensive evaluation method for the precise testing of fruit texture and taste quality.【Method】 In this study, seven different varieties of pineapple were selected for the measurement of sensory attributes, texture characteristics, and physicochemical compositions. Based on the variance and correlation analysis, the key texture properties and physicochemical indexes that affect sensory quality were identified. Further, the principal component regression analysis was performed, with key texture characteristics and physicochemical indexes as independent variables, and the total score of sensory evaluation as dependent variables, to obtain a statistically significant prediction model for the comprehensive evaluation of pineapple quality.【Result】 There were significant differences in some texture properties and physicochemical indexes among different varieties of pineapple, such as hardness, chewiness, maximum shear force, sugar-acid ratio, soluble protein, vitamin C and soluble pectin; the coefficient of variation among varieties was greater than 25%, while the difference in elasticity and cohesiveness was not significant among varieties. The overall satisfaction score of different pineapple varieties from the highest to lowest was Tainong 17>Tainong 16>Tainong 4>MD-2>Tainong 11>Smooth Cayenne>Comte de Paris. Tainong 17 showed the best quality of fruit texture and taste, its total soluble solid content was 16.23%, sugar to acid ratio was 31.82, soluble pectin content was 23.72 mg∙g-1, hardness was 1 826.55 N, Chewiness was 789.77 mJ, and the maximum shear force was 3 491.37 N. Correlation analysis showed that there were six key indexes affecting the overall satisfaction of sensory significantly, including hardness, chewiness, maximum shear force and physicochemical index of soluble solids, sugar-acid ratio and soluble pectin. The determination coefficient R2 of the sensory quality prediction model based on the principal component regression analysis was 0.916, and the standard deviation was 0.11. 【Conclusion】 The texture and taste quality of pineapple vary greatly among different varieties, and a single evaluation method could not accurately evaluate its comprehensive quality. A prediction model was established for pineapple sensory evaluation based on the key texture properties and physicochemical indexes, which could accurately predict the texture and taste quality of pineapple, and made up for the lack of objectivity in artificial sensory analysis.

Key words: pineapple, sensory evaluation, texture properties, physiochemical composition, correlation analysis