To understand the relationship of optical properties with soluble solids content (SSC) and moisture content of strawberry during ripening, a single integrating sphere system was built to estimate the absorption coefficient (μ_a) and reduced scattering coefficient (μ_s') of strawberry in white, color turning and red ripening stages over the wavelength range of 550−850 nm and 950−1650 nm. The relationship between optical properties and SSC and moisture content was analyzed, and the determination models for SSC and moisture content were established by using partial least squares regression and support vector machine methods based on the spectra of μ_a, μ_s', and μ_a together with μ_s'. The results showed that the absorption peaks of strawberry were at 675, 975, 1197 and 1411 nm, and the μ_s' generally decreased with increased maturity of strawberry. The μ_a was positively correlated with SSC and negatively correlated with moisture content, while the μ_s'was positively correlated with moisture content and negatively with SSC. The best correlations of μ_a with SSC and moisture content were found at 1411 nm with the correlation coefficients of 0.72 and -0.74, respectively. The established support vector machine models based on the μ_a spectra in 950−1650 nm and 550−850 nm had the smallest root-mean-squares error of calibration set of 0.98 % and 0.89 % for SSC and moisture content, respectively. This study indicates that SSC and moisture content mainly affect the absorption property of strawberry, and μ_a has greater potential than μ_s' and μ_a together with μ_s' in determining the internal quality of strawberry.

为了理解与可溶性固形物含量（SSC）和草莓的水分含量的光学特性的成熟过程中的关系，一个单一的积分球系统建来估计吸收系数（μ_一个），并减少散射系数（μ_小号'在草莓）在550-850 nm和950-1650 nm的波长范围内具有白色，变色和红色成熟阶段。光学性质和SSC和含水量之间的关系进行分析，并且通过使用基于所述谱偏最小二乘回归和支持向量机的方法建立SSC和水含量的测定模型μ_一个，μ_小号'，和μ_一个连同μ_小号'。结果表明，草莓的吸收峰在675，975，1197和1411纳米，且μ_小号'通常与增加草莓的成熟降低。所述μ_一个呈正SSC相关，与水分含量呈负相关，而μ_小号'与水分含量和负SSC呈正相关。的最佳相关性μ_一个与SSC和水分含量在与分别为0.72和-0.74，相关系数1411纳米被发现了。基于μ建立的支持向量机模型_一个在950-1650纳米和550-850纳米的光谱具有分别校准组的0.98％和SSC 0.89％和水分含量，最小的根均方误差。这项研究表明，SSC和水分含量主要影响草莓的吸收特性，并且μ_一个具有大于势μ_小号“和μ_一个连同μ_小号”在确定草莓的内部质量。