## 1 Introduction  
Chicken breast meat is considered to be an important protein source in healthy diets, and its consumption is increasing worldwide [1]. Nowadays, chicken breast meat with quality assurance is becoming more expected and pursued by consumers. Water-holding capacity (WHC) is defined as the ability of muscle to retain water or resist water loss and is determined by a series of complicated physical structures and chemical components of chicken meat (i.e., diameter and density of muscle fibers and the integrity of connective tissue, as well as myofibrillar protein and collagen content) [2; 3; 4; 5]. Meanwhile, a change in WHC is usually expressed as a change in texture in the meat to a large extent [6]. WHC is directly related to other sensory and physio-chemical traits, such as tenderness, juiciness, color, and pH value, thereby influencing consumers' willingness to pay for meat products [7; 8; 9]. In addition, WHC is closely related to economic benefits, as it is well-known that chicken meat products are always sold by weight, and any water loss leads to a total weight reduction [10]. Thus, the evaluation of WHC of chicken meat is important for both producers and consumers. However,the conventional methods to determine WHC, such as gravimetric method, centrifugation method, and filter paper wetness method, are laborious, destructive, and extremely time-consuming [11; 12]. There is a need for a rapid and nondestructive method of WHC evaluation, which will bring great benefits for the chicken meat industry. Optical techniques are one of the feasible ways to replace those conventional methods of WHC evaluation based on its advantages of fast, non-invasive, simultaneous detection of multiple traits [13; 14]. Visible and near-infrared spectroscopy (Vis/NIRS) has been widely tested to measure quality traits of meat and meat product, and good results have been achieved [15; 16; 17]. However, the limited capacity to estimate WHC by Vis/NIRS has been confirmed by many researchers [18; 19] because Vis/NIRS can only measure a small sample area with limited spatial information to reflect the heterogeneity of meat, which is related to the values of WHC [20]. On the other hand, computer vision provides abundant information of a sample at the pixel-wise level and has been used for evaluating meat quality [21; 22]. However, computer vision has a limited capacity for detecting chemical components, such as water, fat, and protein, as it only works in the visible spectral range. Hyperspectral imaging (HSI) with its advantage of providing both spectral and spatial information of samples simultaneously is receiving a growing interest and attention in the meat industry [23; 24]. Spectral information can effectively reflect the chemical components within the meat [25; 26; 27], while spatial information can evaluate important physical qualities of meat, such as size, shape, texture, etc. In particular, texture can be used as an effective tool for reflecting the surface information of chicken breast fillets, such as the distribution of muscle fibers, fat, and fascia [28; 29]. Some studies have tested the fusion of spectral and spatial information of HSI for predicting the WHC of fish and red meat [8; 30], and the results demonstrated that the prediction accuracy can be improved. However, there is a lack of relevant research reports on fusion data for predicting the WHC of chicken meat. Thus, HSI is an ideal tool that shows great potential in predicting the WHC of chicken meat. The main objective of this study was to investigate the fusion of spectra and texture data to enhance the hyperspectral prediction ability of the water-holding capacity of intact chicken breast fillets (pectoralis major).