## 1 Introduction  
The total soluble solid content (TSS) is an important parameter for fruit. Sugar contributes 75%-85% of TSS, while acids, fructans, proteins, dissolved vitamins, minerals, phenolic compounds,and pigments constitute the remainder [1]. TSS is a key parameter which largely determines the flavor of fruit and is usually used to determine the commercial value of fruit. While consumer fruit quality assessment is still highly determined by external appearance, previous research and experience has shown that the visual appearance quality of fruit often does not match the fruit flavor quality [2]. Thus, an efficient TSS detection method is necessary for the fruit industry. Sensory and physicochemical detection methods are two conventional flavor detection methods. Sensory detection [3] is destructive, time and labor consuming, and can often not detect TSS accurately. Physicochemical detection [4] measures TSS from extracted juice using a refractometer, which is an accurate detection method, but is also a destructive and invasive measurement requiring much labor force and time. Thus, a nondestructive and intelligent TSS detection method is needed. Visible/near infrared (VIS/NIR) spectrum is considered one of the most efficient, nondestructive, and automated TSS detection methods for fruit, like peach [5], apple [6], orange [7], watermelon [8], and persimmon [9] etc. However, VIS/NIR spectrum can be divided into transmitted spectrum [10] and reflection spectrum [11]. Transmitted spectrum usually provides rich internal information with high accuracy for TSS detection but has a complicated optical structure and large equipment size because the light source and the fiber-optics probe have to be on the opposite sides of the fruit sample. Thus, transmitted spectrum equipment is not portable, and the technique is commonly applied for fruit TSS detection in an indoor environment. Previous research has shown the high detection accuracy for orange TSS using transmitted spectrum [12]. On the other hand, a spectrometer using the reflection spectrum method has been created for use as a portable TSS detection device, with a compact light source and the fiber-optics probe. However, reflection spectrum focuses more on the surface of the sample, and the deeper the parts of sample have a weaker signal acquisition. That is, reflection spectrum has lower detection accuracy than transmitted spectrum in fruit TSS detection, especially for thick peeled fruit. [PERSON] et al. found that orange TSS can be feasibly detected by reflection spectrum, but with only mediocre results [13]. In practical applications, a portable spectrometer is more suitable than a non-portable one for many applications, such as fruit TSS detection in an orchard or market. Thus, improving the accuracy of detectors based on the reflection spectrum method needs to be further explored, especially in the case of unsatisfactory detection results. Electronic nose (E-nose) is another portable, nondestructive, and intelligent food quality detection method, which has been widely reported on in the past years [14; 15]. Previous researches showed that the E-nose is a feasible means to detect TSS of many thin peeled fruit like mango [16], persimmon [17], and strawberry [18] etc., because the TSS of fruit is related to its volatile 'fingerprint' which can be acquired by E-nose. However, whether the E-nose can nondestructively detect the TSS of thick peeled fruit efficiently has not yet been reported. The 'Aiyuan 38' orange, a new orange cultivar, has become very popular in China in recent years, due to its great flavor and high juice content, but has been less investigated so far. In this research, we find the detection ability of the TSS of 'Aiyuan 38' based on the reflection spectrum to be unsatisfactory. Thus, the detection ability of E-nose for TSS of 'Aiyuan 38' orange was checked. Then, we tried to find a portable method which improved the accuracy for 'Aiyuan 38' orange TSS detection based on VIS/NIR reflection spectrum and E-nose.