Puffy fruit and soluble solid content (SSC)are important indexes for evaluating the quality of citrus.The feasibility was dis-cussed for detecting Puffing disease and SSC of intact citrus simulta-neously by online visible-near infrared (visible-NIR)transmittance spectroscopy.The spectra were recorded with the integration time of 100 ms in the wavelength range of 350~1 1 50 nm when the samples were conveyed at the speed of five samples per second.The feasibility of simultaneous and online detection of puffiness fruit and SSC for in-tact citrus simultaneously was discussed by visible-near infrared transmittance spectroscopy.The response properties of visible-NIR spectra for normal fruit,mild and severe puffiness fruit were ana-lyzed.Then least squares support vector machine (LSSVM)and dis-crimination partial least square (DPLS)were developed for discrimi-nation of puffiness fruit and health citrus.At the same time,the op-timal soluble solids content model of citrus was conducted by partial least squares regression methods.Other 35 samples without develo-ping calibration models were applied to evaluate precision of online sorting.The classification rate was 100% for identifying puffiness fruit,and the accuracy of sorting SSC for health pears was 97%.The results showed that simultaneous detection of puffiness and SSC were feasible by visible-NIR transmittance spectroscopy.%柑橘浮皮果和可溶性固形物是评价柑橘品质的重要指标，在运动速度5个/s、积分时间100 ms 条件下，采集350~1150 nm 范围内的柑橘光谱，探讨在同一条生产线上同时在线检测浮皮果与可溶性固形物的可行性，同时探索柑橘正常果，轻度、重度浮皮果的光谱响应特征，建立柑橘浮皮果与正常果的定性判别模型，并对比分析两种判别模型，同时还建立柑橘可溶性固形物的定量检测模型，最终实现了柑橘浮皮果与可溶性固形物同时在线检测。采用未参与建模的35个样品对模型在线分选的准确性进行评价，其中柑橘浮皮果都被正确的推入预设的浮皮果出口，正确判别率为100%，而可溶性固形物正确分级率为97%。研究可为柑橘在线分选提供分选策略与理论依据。
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