Cocoa bean is the seed obtained from the pod of a tree crop botanically referred to as Theobroma cacao L. It is a famous cash crop with beneficial nutritional and valuable medicinal characteristics. Cocoa has fascinated the world for so many years and is a big component of chocolate and other confectionary foodstuffs. Some of the valuable medicinal benefits of cocoa include enhancement of brain and heart health, reduction in inflammation, control of weight and blood sugar, and development of healthy skin and teeth (Di Castelnuovo et al., 2012). Studies show that cocoa bean contains polyphenols, flavonoids, and procyanidin and it is an intensive source of antioxidants properties that can reduce blood clots and the risk of stroke and cardiovascular attacks (Cooper et al., 2008). Quality valuation

Drying is one of the traditional means of preserving food. However, various drying methods can influence the nutritional and bioactive constituents of the food product. This study is aimed at evaluating the effect of different drying methods on the proximate composition, physicochemical properties, and minor constituents of palm oil fruit mesocarp. Two varieties of fresh oil palm fruit (dura and tenera) were processed to separate the mesocarp from the other part of the fruit. The fresh fruit mesocarp was divided into five groups and subjected to different drying methods. Proximate and physicochemical characteristics of the oil palm fruit mesocarp were determined. The dried mesocarp had low moisture content (1.49-3.28%), high crude fat content (78.10-90.60%), carbohydrate (4.41-15.12%), crude protein (0.93-3.40%), and ash (0.53-1.15%). The free fatty acid (FFA) (1.06-3.54) and acid value (AV) (2.17 to 8.83 mgKOH/g) were lower because the samples were heated at 100°C for 30 min. The lower pH, FFA, AV, titratable acidity, moisture content, and high antioxidant activity of the oil palm fruit products could be an indication of shelf stability against microbial contamination and rancidity.

Coffee is the most consumed beverage and the second valuable traded commodity in the world. In this current study, a pocket sized near-infrared (NIR) spectroscopy and multivariate analyses were used...

Reliable and user-friendly discrimination of coffee bean integrity and quantification of adulteration in the coffee bean processing value chain would be vital for ensuring consumer trust in quality control and traceability management. In this research, a portable short-wave NIR spectroscopy coupled with chemometric data analysis was employed under different pre-treatments to develop a rapid detection technique. Different pre-processing treatments (multiplicative scatter correction; MSC, standard normal variant; SNV, first derivative; FD) together with multivariate techniques; support vector machine (SVM), linear discriminant analysis (LDA), neural network (NN), and random forest (RF) were comparatively assessed using accuracy and correlation coefficient (R) for discrimination and quantification. The results showed that the FD-LDA model had 97.78% and 100 % in both the calibration set and prediction set. In comparison, the SPA-PLS model had R = 0.9711 and 0.9897 in both the calibration set and prediction set. The outcome of this study showed portable short-wave NIR spectroscopic techniques could be used for examining the integrity of coffee.