## 1 Introduction  
Tropical fruits contain many biologically active compounds such as polysaccharides, polyphenols, vitamins, dietary fiber, and carotenoids [1]. Cherimoya (_Annona cherimola_) fruit is rich in fermentable carbohydrates, especially glucose and fructose [2]. This species is probably native to the area between Ecuador and Peru and has been cultivated since 1200 BC during the Inca Empire period [3]. Similarly, soursop (_Anonma muricata_ L.) is native to tropical America and Africa [4]; its pulp constitutes more than 80% of the fruit and is composed mainly of water, non-reducing sugars, and carbohydrates [5]. Pineapple (_Ananas comosus_ L. [PERSON]) is one of the most popular fruits in the world, widely distributed in tropical regions, and highly dependent on its attractive aroma and sweet taste [6]. Pineapple is an economically important crop in tropical and subtropical regions, and its sweetness determines its quality [7]. Moreover, its soluble sugars such as sucrose, glucose, and fructose are responsible for the sweet taste of fresh-cut pineapple [6]. However, they also have other phytochemical components that can cause differences among these three fruits. Traditionally, the most commonly used techniques for quantifying sugars in food are liquid and gas chromatography, nuclear magnetic resonance, infrared spectroscopy,spectrophotometry, polarization measurement, and hyperspectral imaging [8; 9], which are limited by their invasiveness, intensive use of resources, and negative environmental impact [10; 11]. Therefore, in recent years, there has been an increasing need to explore non-destructive and in situ methods that have been reported to work as well as high-performance liquid chromatography [12]. One such non-destructive method is Raman spectroscopy (RS), that enables to detect the internal quality of fruits and vegetables without destroying them [11; 12; 13]. In addition, the use of RS is increasing, especially in food safety. This technology makes it possible to detect peak signals by exposing the sample to a laser light [14]. This new technology is based on the detection of frequency changes and variations in the intensity of scattered light when a sample interacts with a laser light source [13], obtaining more selective spectra because it provides narrower spectral bands with abundant and well-resolved chemical information that is easy to interpret [12; 13]. [PERSON] et al. [15] mention that RS has become a robust method to assess the content of individual sugars; for example, previous studies have been reported on the application of RS in the quantification of sugars from aqueous solutions, allowing the discrimination of fructose, glucose, maltose, and sucrose with laser excitation at 785 nm [9; 12]. This technique is promising because it does not require pretreatment of fruit samples such as berries [9; 15]. In addition, RS provides spectroscopic fingerprints that provide information related to specific chemical bonds or functional groups that are useful for analyzing samples qualitatively and quantitatively [11], which is used with chemometric methods to discriminate foods according to their composition [16; 17]. In addition, the combination of RS and chemometric methods, was used for the identification of agricultural product varieties in grains, edible oils, and honey [18]. Also, they were used for the discrimination of foreign fats and oils in milk cream, and yogurt [19]; for the rapid quantification of starch in agricultural products [20]; and for the differentiation of conventional and transgenic cotton seed genotypes [21]. Regarding chemometric tools for food discrimination based on spectral data [16; 22], principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) are considered robust linear classification methods [23]. PCA is an unsupervised method that reduces the data to find similarities between samples [24].