Abstract: Abstract: Navel orange is a very popular fruit in China, which is mainly cultivated along the Yangtze River. Navel oranges are classified into different grades based on external quality and internal quality before they are sold. Soluble solids content is one of the main indices for evaluating the internal quality of navel orange. Therefore, it is very important to improve the detection accuracy of soluble solids content in production. So far, visible and near infrared spectroscopy (Vis-NIR) is one of the most widely used and effective techniques in internal quality assessment of fruits. In this study, 199 Fukumoto navel oranges were taken as experimental samples. The transmission spectra of navel oranges of three positions including pedicle upwards (P1), pedicle horizontal (P2) and pedicle downward (P3) were acquired by using a special visible and near infrared transmission spectrum measurement system designed by ourselves. The average spectra (P4) and weighted spectra (P5) of P1, P2 and P3 were calculated. The transmission spectra, including P1, P2, P3, P4 and P5 were preprocessed by multivariate scattering correction, standard normal variate transformation, first derivative and second derivative respectively. The best pretreatment results were obtained based on first derivative after comparative study. Then the spectra data preprocessed by first derivative were divided into 30 to 50 intervals with step length of 5, and backward interval partial least squares was used to select the optimal band combination. Good results observed when P1, P2, P3, P4 and P5 were divided into 35, 40, 30, 35 and 40 intervals, in which 161, 180, 114, 308 and 170 variables were retained. On this basis, competitive adaptive re-weighted sampling (CARS) was used to select feature variables. After running CARS for 20 times in each selection, 24, 23, 18, 39 and 22 variables were kept respectively. Finally, Five PLS models were established, including P1-PLS, P2-PLS, P3-PLS, P4-PLS and P5-PLS. Among the P1-PLS, P2-PLS and P3-PLS models, P2-PLS model was the best one, as the value of correlation coefficients of prediction was 0.924 and the value of root mean square error of prediction was 0.404. This model can be realized by adjusting the navel oranges to pedicle horizontal in modeling. P4-PLS model and P5-PLS model had achieved good prediction results, as the value of correlation coefficients of prediction was higher than 0.91 and the value of root mean square error of prediction was lower than 0.43. P4-PLS model was based on the average spectra of P1, P2 and P3, and had potential to be realized by rolling the navel oranges in actual application. However, P5-PLS model was based on weighted spectra of P1, P2 and P3, which was difficult to realize in on-line detection. This study can provide a reference for the development of on-line detection equipment for the assessment of internal content of substances in navel orange.