Detection of agriculturally relevant lime concentrations in soil using mid-infrared spectroscopy

Geoderma ◽  
2022 ◽  
Vol 409 ◽  
pp. 115639
Author(s):  
Ruby Hume ◽  
Petra Marschner ◽  
Rhiannon K. Schilling ◽  
Sean Mason ◽  
Luke M. Mosley
2021 ◽  
Vol 164 ◽  
pp. 106029
Author(s):  
Diego Maciel Gerônimo ◽  
Sheila Catarina de Oliveira ◽  
Frederico Luis Felipe Soares ◽  
Patricio Peralta-Zamora ◽  
Noemi Nagata

2021 ◽  
Vol 162 ◽  
pp. 103894
Author(s):  
Thao Pham ◽  
Cornelia Rumpel ◽  
Yvan Capowiez ◽  
Pascal Jouquet ◽  
Céline Pelosi ◽  
...  

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jordi Ortuño ◽  
Sokratis Stergiadis ◽  
Anastasios Koidis ◽  
Jo Smith ◽  
Chris Humphrey ◽  
...  

Abstract Background 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−1) 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. Results 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 (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (R2P = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: R2P = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: R2P = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (R2P = 0.66; RPD = 1.86; RER = 7.16). Conclusions 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.


2015 ◽  
Vol 50 (6) ◽  
pp. 997-1005 ◽  
Author(s):  
Florian Capito ◽  
Romas Skudas ◽  
Harald Kolmar ◽  
Christian Hunzinger

2010 ◽  
Vol 719 (1) ◽  
pp. 425-450 ◽  
Author(s):  
Dario Fadda ◽  
Lin Yan ◽  
Guilaine Lagache ◽  
Anna Sajina ◽  
Dieter Lutz ◽  
...  

2011 ◽  
Vol 13 (1) ◽  
pp. 101-105 ◽  
Author(s):  
Manuel Mora ◽  
María Isabel López ◽  
César Jiménez-Sanchidrián ◽  
José Rafael Ruiz

2014 ◽  
Vol 5 ◽  
Author(s):  
Asier Largo-Gosens ◽  
Mabel Hernández-Altamirano ◽  
Laura García-Calvo ◽  
Ana Alonso-Simón ◽  
Jesús Álvarez ◽  
...  

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