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Soluble solids content (SSC) and blackheart are main quality evaluation indexes and physiological disease for ‘Yali’ pear, respectively. The feasibility of simultaneous and online detection of blackheart and SSC was investigated by using visiblenear infrared (NIR) diffuse transmittance spectroscopy. The visibleNIR energy spectra of blackheart and healthy ‘Yali’ pears were collected at the speed of five samples per second. The response properties of visibleNIR spectra for blackheart and healthy ‘Yali’ pears were analyzed, and the discrimination models of peak ration (PA) with wavelengths of 674nm and 634nm and the discrimination partial least square (DPLS) were developed for discrimination of blackheart and healthy pears. DPLS was superior to PA with relative higher classification rate of 100%. The influence of blackheart to SSC determination was also explored by using partial least square (PLS) regression models, and PLS model was employed with healthy ‘Yali’ pear samples. Then a novel strategy was proposed for simultaneous and online detection of blackheart and SSC for ‘Yali’ pears. With this strategy the blackheart pears were removed and healthy pears were sorted by SSC values simultaneously in the sorting line. The new samples were applied to evaluate precision of online sorting of blackheart and SSC for ‘Yali’ pear, which were not used to develop calibration models. The classification rate was 100% for identifying blackheart pears, stand error of prediction (SEP) was 0.45°Brix, and accuracy of sorting for healthy pears was 98%. The results suggest that diffuse transmittance visibleNIR technique combining with DPLS and PLS methods has significant potential to simultaneous and online detection of blackheart and SSC of ‘Yali’ pears; moreover, it may have commercial and regulatory potential to avoid time consuming work, costly and laborious chemical analysis for ‘Yali’ pears trade.