02346naa a2200277 a 450000100080000000500110000800800410001902400340006010000150009424501280010926000090023752015060024665000200175265000080177265300240178065300150180465300130181965300290183265300360186170000190189770000200191670000160193670000190195270000180197177300790198921038112019-01-14       2018    bl uuuu     u00u1 u    #d7 a10.1177/09670335188052542DOI1 aÁVILA, S.  aA chemometric approach for moisture control in stingless bee honey using near infrared spectroscopy.h[electronic resource]  c2018  aHoney is a product that is often adulterated by the addition of water. Stingless bee honey naturally has a higher moisture content than that produced by the traditional Apis mellifera. In most countries, there is a lack of quality standards and methods to characterise and assure the authenticity of stingless bee honey, which demands for the development of fast methods to assess its main properties, avoiding potential fraud. Thus, this work aimed to develop a non-destructive moisture determination method for stingless bee honey based on diffuse reflectance near infrared spectroscopy combined with chemometrics. Thirty-two honey samples from four stingless bee species (Melipona quadrifasciata, Melipona marginata, Melipona bicolor and Scaptotrigona bipuncata) were used to develop calibration models using partial least squares regression analyses. Results revealed intense absorption bands in C-H, O-H and C-O vibrations in the spectra of stingless bee honey. The calibration model was used to predict the moisture content in honey from an external group. The prediction of the honey's moisture showed good correlation (r2 = 0.93) with the refraction index method and an average error of 2.14%. The statistics variables for the calibration (R2 = 0.947, SEP = 1.005 and RPD = 4.3) revealed that this model can be used to predict the moisture from stingless bee honey and that near infrared spectroscopy is a reliable tool to be applied in quality control with rapid, simple and accurate results.  aQuality control  aMel  aControle de umidade  aMeliponini  aMoisture  aMultivariate calibration  aPartial least square regression1 aHORNUNG, P. S.1 aTEIXEIRA, G. L.1 aBEUX, M. R.1 aLAZZAROTTO, M.1 aRIBANI, R. H.  tJournal of Near Infrared Spectroscopygv. 26, n. 6, p. 379-388, Dec. 2018.