UV Spectroscopy and Digital Image to Estimate the Antioxidant Capacity and Proline Content of Honeys Produced by Native Bees

被引:1
作者
Guerrero, Maidelen Del Carmen Lozano [1 ]
Lima, Marina Duartes Fernandes de Souza [1 ]
Acorone, Camila [1 ]
Rigobello, Eliane Sloboda [2 ]
Valderrama, Patricia [2 ]
Torres, Yohandra Reyes [1 ]
机构
[1] Univ Estadual Centro Oeste, Dept Quim, BR-85040080 Guarapuava, PR, Brazil
[2] Univ Tecnol Fed Parana, Via Rosalina Maria Dos Santos 1233, BR-87301899 Campo Mourao, PR, Brazil
关键词
Stingless bees; antioxidant capacity; honey; PLS models; PHYSICOCHEMICAL PROFILES; ANTIBACTERIAL ACTIVITIES; STINGLESS; PREDICTION; MELIPONINI;
D O I
10.21577/1984-6835.20230024
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The honey produced by the stingless bees has been used by indigenous communities in Brazil as a nutritional and medicinal source. In accordance with this traditional knowledge, anti-inflammatory, antiviral, healing, and antioxidant properties have been recently described for this natural product. Despite its widely use, there is no specific quality control regulation for this peculiar honey; therefore, its quality is verified by taking into consideration the parameters already standardized to the honey produced by Apis mellifera bees. Among other parameters, antioxidant activity, phenolic and proline contents are tested for quality control following analytical protocols via spectrophotometric methods. Although simple, these methods involve several steps and the use of organic reagents and solvents, then causing some analyst exposure and environmental impact. Looking for environment-friendly methods to estimate important parameters for the quality control of honeys, in the current research, we investigated the application of multivariate calibration models to indirectly estimate the antioxidant capacity and total amino acid content of honeys produced by stingless bees. Then, partial least squares regression (PLS) was applied to UV spectra and digital images of honeys as predictive variables to predict the target properties. The PLS models showed coefficients of calibration and prediction R2 > 0.7 and errors of the same magnitude in both the calibration and validation sets of honey samples, indicating that PLS models are robust and have a good prediction capacity of the study properties. In other words, it is possible to predict accurately the antioxidant capacity and proline content of honeys produced by stingless bees by a simple acquisition of a UV spectrum or a digital photo. Additionally, the information reported in this paper on the antioxidant capacity and proline content of stingless bee honey contributes to the knowledge of the properties of this honey and supports the need to develop adequate technical regulation for this type of honey.
引用
收藏
页码:1092 / 1106
页数:15
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