## 1 Introduction  
According to the Food and Agriculture Organization of the United Nations (FAO), Mexico is a leading producer of citrus fruits, including lemons, limes, graprefruits, tangerines, mandarins, clementines, and oranges. In 2022, it ranked fourth in the world for orange production, with 4,850,083.04 tons. About 88% of this production is for domestic consumption, while the remaining is exported to other countries [1]. The demand for this fruit is attributed to its versatility in various forms, such as juices, jams, essential oils, concentrated formulas, and pastes [2; 3; 4; 5]. Additionally, this citrus is considered a functional food due to its nutritional benefits, including flavonoids, vitamin C, phenolic compounds, carotenoids, and sugars. It also has protective effects against cardiovascular diseases, hypertension, type 2 diabetes, various types of cancer, asthma, obesity, cognitive impairment, and depression [6; 7; 8; 9; 10; 11]. The agri-food industry gives priority to measuring the quality criteria set by the consumer, as color is generally considered to be a quality attribute associated with ripeness and freshness, and consumers prefer fruits and vegetables that are uniform in appearance and vivid color [12; 13; 14; 15; 16]. Furthermore, the agri-food sector is required to evaluate the organoleptic characteristics of oranges through sensory analysis. This type of analysis is linked to consumer perception since food is analyzed through the senses using organoleptic properties, such as appearance, smell, aroma, texture, sound, and flavor [17; 18]. In addition, the physical-chemical properties are analyzed to assess the nutritional value of the orange. This includes the content of nutrients such as fats, vitamins, carbohydrates, proteins, and total acidity, which is an effective indicator of the quality of the fruit [19; 20; 21; 22; 23]. The quality of the orange fruit is also influenced by climatic conditions and production methods, with the latter being particularly significant [24]. Traditionally, the quality of oranges was typically assessed in laboratories using invasive devices, such as high-performance liquid chromatography (HPLC), refracometers, penetrometers, pH meters, and durometers [25]. These devices offer versatility, sensitivity, and the ability to separate and identify mixtures, as well as determine sugar content, acidity, color, and firmness. However, one disadvantage of these devices is that they require operation by specialized personnel under controlled conditions, as some devices require the use of solvents for sample analysis, which can be inconvenient and potentially hazardous [25; 26; 27; 28; 29; 30]. Currently, non-invasive methods have been proposed to determine the quality of oranges based on their color. Therefore, computer vision (CV) is a technique used to measure color, which is a perceptual phenomenon resulting from the stimulation of the visual system by the visible spectrum of light reflected or emitted by the sample. It is important to note that color is not an intrinsic property of the sample, and its perception is sensitive to changes in the incident light source, which can be used to determine the ripeness of various fruits, including persimmon, strawberry, pomegranate, tomato, bell pepper, pineapple, and orange [15; 31; 32; 33; 34]. These methods have also been used to measure physicochemical properties, such as pH, total soluble solids (TSS), tittatable acidity (TA), maturity index (MI), total anthocyanin content (TAC), and carotenoids [14; 28; 35; 36; 37; 38]. These properties can be determined using the color space models RGB, HSV, CIE L*a*b*b, and CIE XYZ, along with the indices CI = a/b, CCI = (1.00 \(\times\) a)/(L \(\times\) b), CR = 200[(1.277X \(-\) 0.213Z)/Y \(-\) 1]. It should be noted that the CII is one of the most important indicators as to when the crop should be harvested or what treatment should be applied to it [14].