Ortuño Jordi, Stergiadis Sokratis, Koidis Anastasios, Smith Jo, Humphrey Chris, Whistance Lindsay, Theodoridou Katerina
Institute for Global Food Security, Queen's University Belfast, Belfast, BT9 5DL, Northern Ireland, UK.
Department of Animal Sciences, School of Agriculture, Policy and Development, University of Reading, New Agriculture Building, Earley Gate, P.O. Box 237, Reading, RG6 6EU, UK.
Plant Methods. 2021 Feb 6;17(1):14. doi: 10.1186/s13007-021-00715-8.
The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopastoral systems. The development of quick, safe and robust analytical techniques to monitor CT's full profile is crucial to suitably understand CT variability and biological activity, which would help to develop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000-550 cm) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization-mDP, procyanidins:prodelphidins ratio-PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods.
The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD [coefficient of determination for prediction (RP) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (RP = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: RP = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: RP = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (RP = 0.66; RPD = 1.86; RER = 7.16).
MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.
树木饲料中缩合单宁（CT）的存在对反刍动物营养具有一系列生产、健康和生态效益。目前用于全面表征CT的湿分析方法既耗时又耗费资源，因此限制了其在林牧系统中的适用性。开发快速、安全且稳健的分析技术以监测CT的全貌对于充分理解CT的变异性和生物活性至关重要，这将有助于制定基于有效证据的决策，以最大限度地发挥CT带来的益处。本研究调查了傅里叶变换中红外光谱（MIR：4000 - 550 cm）结合多变量分析来测定橡树、挪威槭和沙棘叶中CT浓度和结构（平均聚合度 - mDP、原花青素：原翠雀素比率 - PC：PD和顺式：反式比率）的适用性，使用盐酸：丁醇：丙酮：铁（HBAI）和硫解 - HPLC作为参考方法。
首先使用主成分分析探索获得的MIR光谱，然后基于偏最小二乘回归建立多变量校准模型。MIR在测定PC：PD方面显示出出色的预测能力[预测决定系数（RP） = 0.96；预测偏差比（RPD） = 5.26，范围误差比（RER） = 14.1]和顺式：反式比率（RP = 0.95；RPD = 4.24；RER = 13.3）；在CT定量方面表现一般（HBAI：RP = 0.92；RPD = 3.71；RER = 13.1；硫解：RP = 0.88；RPD = 2.80；RER = 11.5）；而在mDP方面较弱（RP = 0.66；RPD = 1.86；RER = 7.16）。
MIR结合化学计量学能够快速表征树叶中CT的全貌，这将有助于更好地评估植物生态变异性并改善反刍家畜的营养管理。
