Suppr超能文献

利用可见及近红外光谱预测猪肉最长肌的嫩度稳定性。

Use of visible and near-infrared spectroscopy to predict pork longissimus lean color stability.

机构信息

USDA-ARS, Roman L. Hruska US Meat Animal Research Center, Clay Center, NE 68933-0166, USA.

出版信息

J Anim Sci. 2011 Dec;89(12):4195-206. doi: 10.2527/jas.2011-4132. Epub 2011 Aug 5.

Abstract

This study evaluated the use of visible and near-infrared (VISNIR) spectroscopy to predict lean color stability in pork loin chops. Spectra were collected immediately after and approximately 1 h after rib removal on 1,208 loins. Loins were aged for 14 d before a 2.54-cm chop was placed in simulated retail display. Spectra were collected on aged loins immediately after removal from the vacuum package and on chops 10 min after cutting. Instrumental color measurements [L*, a*, b*, hue angle, chroma, and E (overall color change)] were determined on d 0, 1, 7, 11, and 14 of display. Principal components analysis of display d 0 and 14 values of these traits identified a factor (first principal component; PC1) explaining 67% of the variance that was related to color change. Partial least squares regression was used to develop 3 models to predict PC1 values by using VISNIR spectra collected in the plant, on aged loins, and on chops. Loins with predicted PC1 values less than 0 were classified as having a stable color, whereas values greater than 0 were classified as having a labile lean color. Loins classified as stable by the in-plant model had smaller (P < 0.05) L* values than those classified as labile. Hue angle and ΔE values were less (P < 0.05) and a* and chroma values were greater (P < 0.05) after d 7 of display in loins predicted to have a stable color than in loins predicted to have a labile lean color. Similarly, chops from loins classified as stable using the aged loin model had smaller (P < 0.05) L* values than those from loins classified as labile. Furthermore, loins predicted to be stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display than did loins predicted to be labile. Results for the chop model were similar to those from the 2 loin models. Chops predicted to have a stable lean color had smaller (P < 0.05) L* values than did those predicted to have a labile lean color. Chops classified as stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display compared with chops classified as labile. All 3 models effectively segregated chops based on color stability, particularly with regard to redness. Regardless of the model being used, d 14 display values for a*, hue angle, and ΔE in loins classified as stable were similar to the d 7 values of loins classified as labile. Thus, these results suggest that VISNIR spectroscopy would be an effective technology for sorting pork loins with regard to lean color stability.

摘要

本研究评估了可见近红外(VISNIR)光谱法预测猪里脊肉嫩色稳定性的应用。在去除肋骨后立即和大约 1 小时后采集 1208 个里脊肉的光谱。里脊肉在老化 14 天后,切成 2.54 厘米的肉块进行模拟零售展示。在从真空包装中取出后和切割后 10 分钟,立即对老化的里脊肉进行光谱采集。在展示的第 0、1、7、11 和 14 天,对 d0 时的仪器颜色测量[L*、a*、b*、色调角、色饱和度和 E(整体颜色变化)]进行测定。通过对展示第 0 和 14 天这些特征的主成分分析,确定了一个因子(第一主成分;PC1),该因子解释了 67%的与颜色变化相关的方差。使用在工厂、老化的里脊肉和肉块上采集的 VISNIR 光谱,采用偏最小二乘回归建立了 3 个模型,以预测 PC1 值。预测 PC1 值小于 0 的里脊肉被归类为具有稳定的颜色,而大于 0 的里脊肉被归类为具有不稳定的浅色。通过工厂模型分类为稳定的里脊肉的 L值比分类为不稳定的里脊肉小(P<0.05)。在预测为稳定的里脊肉中,色调角和ΔE 值在展示第 7 天后较小(P<0.05),a和色饱和度值在展示第 7 天后较大(P<0.05)。同样,通过老化里脊模型分类为稳定的肉块的 L值比分类为不稳定的肉块小(P<0.05)。此外,预测为稳定的里脊肉在展示第 7 天后的色调角和ΔE 值较小(P<0.05),a和色饱和度值较大(P<0.05),而预测为不稳定的里脊肉则较小。切块模型的结果与 2 个里脊模型的结果相似。预测为稳定的浅色里脊肉的 L值比预测为不稳定的浅色里脊肉小(P<0.05)。与分类为不稳定的肉块相比,分类为稳定的肉块的色调角和ΔE 值较小(P<0.05),a和色饱和度值较大(P<0.05)。所有 3 个模型都能有效地根据颜色稳定性对肉块进行分类,特别是在红色方面。无论使用哪种模型,分类为稳定的里脊肉在展示第 14 天的 a*、色调角和ΔE 值与分类为不稳定的里脊肉在展示第 7 天的值相似。因此,这些结果表明,可见近红外光谱法将是一种有效的技术,可用于根据嫩色稳定性对猪里脊肉进行分类。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验