Nofima AS, Norwegian Institute for Food and Fisheries Research, Muninbakken 9-13, Breivika, NO-9291 Tromsø, Norway.
Nortura SA, Lørenveien 37, NO-0513 Oslo, Norway.
Poult Sci. 2019 Jan 1;98(1):480-490. doi: 10.3382/ps/pey351.
The muscle syndrome woody breast (WB) impairs quality of chicken fillets and is a challenge to the poultry meat industry. There is a need for online detection of affected fillets for automatic quality sorting in process. Near-infrared spectroscopy (NIRS) is a promising method, and in this study we elucidate the spectral properties of WB versus normal fillets. On a training set of 50 chicken fillets (20 normal, 30 WB), we measured NIR, nuclear magnetic resonance (NMR) T2 relaxation distributions, and crude chemical composition. NIRS could estimate protein in the fillets with an accuracy of ±0.64 percentage points. T2 distributions showed that there was a larger share of free water in WB fillets. This difference in water binding generated a shift and narrowing of the water absorption peak in NIR around 980 nm, quantified by a bound water index (BWI). The correlation between BWI and T2 distributions was 0.78, indicating that NIRS contains information about degree of water binding. Discriminant analysis showed that NIRS obtained 100% correct classification of normal versus WB on the training set, and 96% correct classification on a test set of 52 fillets. The main reason for why NIRS can successfully discriminate between WB and normal fillets is the methods sensitivity to both protein content and degree of water binding in the muscle, both established markers for WB. The classification model can be based on NIR spectra only, calibration against protein is not needed. The affected muscle tissue associated with the WB syndrome is unevenly distributed in the fillets, and this heterogeneity was characterized by NIRS and NMR. Clear differences in water binding properties were found between the superficial 1 cm layer and the deeper layer at 1 to 2 cm depth. Significant differences in protein estimates by NIRS at different measurement points along the chicken fillets were obtained for WB fillets. The findings suggest how to obtain optimal sampling with NIRS for best possible discrimination between WB and normal breast fillets.
肌节综合征木质胸（WB）损害鸡胸肉片的质量，是家禽肉行业面临的挑战。需要在线检测受影响的肉片，以便在加工过程中自动进行质量分类。近红外光谱（NIRS）是一种很有前途的方法，本研究阐明了 WB 与正常肉片的光谱特性。在一个由 50 片鸡胸肉片（20 片正常，30 片 WB）组成的训练集中，我们测量了近红外光谱、核磁共振（NMR）T2 弛豫分布和粗化学成分。NIRS 可以准确估计肉片中的蛋白质，误差在±0.64 个百分点以内。T2 分布表明，WB 肉片中有更大比例的游离水。这种结合水的差异在近红外光谱中产生了一个水吸收峰的偏移和变窄，通过束缚水指数（BWI）来量化。BWI 与 T2 分布的相关性为 0.78，表明 NIRS 包含了关于水结合程度的信息。判别分析表明，NIRS 在训练集上对正常和 WB 肉片的分类准确率为 100%，在 52 片测试集上的分类准确率为 96%。NIRS 能够成功区分 WB 和正常肉片的主要原因是该方法对肌肉中的蛋白质含量和水结合程度都很敏感，这两个都是 WB 的标志性指标。分类模型可以仅基于近红外光谱，不需要针对蛋白质进行校准。与 WB 综合征相关的受影响的肌肉组织在肉片内分布不均匀，这种不均匀性可以通过 NIRS 和 NMR 来描述。在 1 到 2 厘米的深度范围内，在 1 厘米的表面层和更深层之间发现了明显的水结合性质差异。对于 WB 肉片，在鸡胸肉片的不同测量点处，通过 NIRS 获得的蛋白质估计值存在显著差异。这些发现表明了如何通过 NIRS 获得最佳采样，以实现 WB 和正常鸡胸肉片之间的最佳区分。
