Singpoonga Natthapong, Rittiron Ronnarit, Seang-On Boonsong, Chaiprasart Peerasak, Bantadjan Yuranan
Department of Biology and Biotechnology, Faculty of Science and Technology, Nakhon Sawan Rajabhat University, Nakhon Sawan 60000, Thailand.
Department of Food Engineering, Faculty of Engineering at Kamphaeng Saen, Kasetsart University, Nakhon Pathom 73140, Thailand.
ACS Omega. 2020 Oct 16;5(42):27235-27244. doi: 10.1021/acsomega.0c03403. eCollection 2020 Oct 27.
Near-infrared (NIRS) spectroscopy, coupled with partial least squares regression, was used to predict adenosine and cordycepin concentrations in fruiting bodies of . The fruiting body samples were prepared in four different sample formats, which were intact fruiting bodies, chopped fruiting bodies, dried powder, and dried crude extract. The actual amount of the adenosine and cordycepin concentrations in fresh fruiting bodies was analyzed by high-performance liquid chromatography. Results showed that the prediction models developed from the chopped samples provided excellent accuracy in both parameters with minimal sample preparation. These optimum models provided a coefficient of determination of prediction, standard error of prediction, bias, and residual predictive deviation, which were respectively 0.95, 16.60 mg kg, -8.57 mg kg, and 5.04 for adenosine prediction, and 0.98, 181.56 mg kg, -1.05 mg kg, and 8.9 for cordycepin prediction. The accuracy and performance of the model were determined by ISO12099:2017(E). It was found that these two equations can be considered to be acceptable at a probability level of 95% confidence. The NIRS technique, therefore, has the potential to be an objective method for determining the adenosine and cordycepin concentrations in fruiting bodies.
近红外（NIRS）光谱结合偏最小二乘回归，用于预测子实体中腺苷和虫草素的浓度。子实体样品以四种不同的样品形式制备，即完整子实体、切碎子实体、干粉和干粗提物。通过高效液相色谱法分析新鲜子实体中腺苷和虫草素浓度的实际含量。结果表明，从切碎样品建立的预测模型在两种参数上都具有很高的准确性，且样品制备最少。这些最佳模型给出的预测决定系数、预测标准误差、偏差和剩余预测偏差，对于腺苷预测分别为0.95、16.60mg/kg、-8.57mg/kg和5.04，对于虫草素预测分别为0.98、181.56mg/kg、-1.05mg/kg和8.9。模型的准确性和性能按照ISO12099:2017(E)进行测定。结果发现，在95%置信概率水平下，这两个方程可被认为是可接受的。因此，近红外光谱技术有潜力成为一种测定子实体中腺苷和虫草素浓度的客观方法。
