Physicochemical and antioxidant properties of raw honeys from Malaysia were used as markers for determining its entomological source of bee species of Apis dorsata, Apis mellifera, Apis cerana, or Heterotrigona itama. Physicochemical properties of moisture content, water activity, specific gravity, viscosity, pH, free acidity, electrical conductivity, colour (L*, a* and b*), colour intensity, and antioxidant properties including the DPPH free radical scavenging activity power (1/IC50), ascorbic acid equivalent antioxidant content (AEAC), ferric ion reducing antioxidant power (FRAP), and total phenolic content (TPC) were measured and analysed. Honeys were classified into two major groups of those from honey bees (Apis spp.) and Trigona stingless bees (Heterotrigona itama) from its physicochemical and antioxidant properties using hierarchical cluster and principal component analyses. The Kelulut honey produced by stingless bees, Heterotrigona itama was differentiable from honeys from the regular honey bee species, the Apis spp. with characteristics of high moisture content of 33.24 g/100 g, free acidity of 136.8 meq/kg, colour intensity of 990.3 mAU, AEAC of 26.64 mg/100 g, and FRAP of 41.95 mg AAE/100 g. Honey classification by its entomological origin helps in honey identification and it reduces honey fraudulence.

Application of ultrasound to osmotic dehydration of guava slices via indirect sonication using an ultrasonic bath system and direct sonication using an ultrasonic probe system was studied. Pre-treatments were designed in three osmotic solution concentrations of 0, 35, and 70 °Brix at indirect ultrasonic bath power from 0 to 2.5 kW for immersion times ranging for 20-60 min and direct ultrasonic probe amplitudes from 0 to 35% for immersion times of 6-20 min. The calculated ultrasound intensities from calorimetric ultrasound power dissipated indicated that direct sonication was more intensive than indirect sonication. The general linear model (GLM) showed that ultrasound input (power and amplitude), osmotic solution concentrations, and immersion time increased the water loss, solid gain, and total colour change of guava slices significantly with P < 0.0005. Indirect sonication in osmotic solutions contributed to high water loss and solid gain with acceptable total colour change than direct sonication. Applying ultrasound pre-osmotic treatment in 70 °Brix prior to hot-air drying reduced the drying time by 33%, increased the effective diffusivity by 35%, and decreased the total colour change by 38%. A remarkable decrease of hardness to 4.2 N obtained was also comparable to the fresh guava at 4.8 N.

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Raw honeys from four different bee species, namely the honey bees and stingless bees, were classified based on its chemical profiles, mineral contents and heavy metals. Chemical profiles including proximate composition, predominant sugars, hydroxymethylfurfural content, and diastase activity were determined following official methods while mineral and heavy metals contents were obtained from atomic adsorption spectrometry (AAS) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements, respectively. Both hierarchical cluster analysis and principal component analysis show high possibility of distinguishing honey by its bee species of honey bees (Apis spp.) and stingless bees (Heterotrigona itama) based on distinctive differences in chemical compositions and mineral contents. Potassium and sodium were the major elements in raw honey samples at average of 904.9 and 617.6 mg/kg, respectively. Honey from stingless bee contained more protein, 0.85 g/100 g and less total sugar of fructose and glucose at 24.99 g/100 g. The information of bee speciation origin of honey bees and stingless bees enhances the identity of honey on the product labelling.

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Modelling studies of guava drying and quality are presented using theoretical and statistical models by varying temperature from 55 to 75 °C and slice thickness from 3 to 9 mm. The quality of dried fruit was measured for its water activity, colour, vitamin C, and texture. The superposition technique with Midilli-Kucuk model showed efficiency in modelling the drying process with R (2)  = 0.9991. The second-order polynomial equations adequately described the quality of dried guava with regression coefficient, R (2) > 0.7. Drying time was a good function of temperature and thickness (P < 0.001); water activity, colour and vitamin C showed strong dependence on temperature (P < 0.1); while texture was mainly influenced by its thickness (P < 0.005). The optimum drying temperature of 70 °C at slice thickness of 6 mm was determined using the desirability function method. Simultaneous modelling using the theoretical and statistical drying models provides information on water diffusion and evaporation with the drying responses and factors.

Summary Four different DNA protocols were compared to obtain the best method for DNA extraction of bees in honey samples. The efficiency was evaluated in terms of DNA concentration and purity, PCR amplification capacity targeting mitochondrial 16S rRNA gene, and execution time. The most efficient DNA extraction method was selected using simple additive weighting (SAW) analysis. The DNeasy method with silica membrane spin‐column format scored highest in the final ranking of SAW compared to CTAB‐based, Wizard and NucleoSpin methods. It yielded extracted DNA with sufficient concentration (second highest), acceptable purity (1.5–2.0), amplifiable for 16S rRNA gene region, and required least extraction time. This recommended DNA extraction protocol suggests that genomic methodologies using a 150 bp amplicon of the 16S rRNA gene of bees enables identification of the entomological origin of honey.

The need for accurate and reliable methods for identification of honey origin is important for reducing honey fraud. This study has identified suitable chemical and genetic markers to determine the origin of honey from its bee source of Apis honey bees or Trigona stingless bee. In the chemical analysis, moisture, fructose, glucose, sucrose, free acidity, and colour intensity were chemical markers identified for differentiating honey by its bee origin. The use of principal component analysis (PCA) and hierarchical cluster analysis (HCA) on honey composition have successfully classified honey into groups of Apis and Trigona. In the DNA-based method, mitochondrial cytochrome c oxidase subunit I (COI) gene was used as a genetic marker to identify honey origin by its bee species accurately from the clear groupings and distinct clusters in phylogenetic trees. The genetic marker of COI gene is accurate and reliable for this identification as it has direct matching to its reference bee species. Incorporating both chemical and genetic markers affirm the identity of honey. 