Solanum lycopersicum PIN-FORMED1 (SlPIN1), a major auxin efflux facilitator, contributes to the establishment of auxin maxima during organ initiation and development in tomato. However, the functions of SlPIN1 during organ abscission remain unclear. In our study, SlPIN1 expression decreased immediately after flower removal and increased following IAA treatment, indicating a high sensitivity to auxin depletion. 1-MCP (an ethylene inhibitor) delayed abscission and down-regulated SlPIN1, indicating that ethylene may positively regulate SlPIN1 and that low expression levels of SlPIN1 may delay abscission. The SlPIN1 protein levels were not consistent with the expression pattern, implying that in addition to transcription, protein degradation also affects SlPIN1 levels during abscission. The phosphorylation of SlPIN1 at Ser418, which significantly declined during abscission, was found to play roles in SlPIN1 localization and auxin transport. We also identified the interaction proteins of SlPIN1, which were involved in phosphorylation and ubiquitylation. Therefore, complex mechanisms mediate SlPIN1 auxin transport capability during abscission. The silencing of SlPIN1 expression accelerated abscission by increasing auxin accumulation in the ovary and decreasing the auxin content in the abscission zone (AZ), indicating that SlPIN1 plays a major role in mediating auxin source-sink transport and the establishment and maintenance of auxin maxima in the AZ.

Background Wood basic density (WBD) is one of the most crucial wood property in tree and mainly determined the end use of wood for industry. However, the measurement WBD is time- and cost-consuming, which an alternatively fast and no-destructive measurement is needed. In this study, capability of NIR spectroscopy combined with partial least squares regression (PLSR) to quantify the WBD were examined in multiple wood species. To obtain more accurate and robust prediction models, the grain angle (0° (transverse surface), 45°, 90° (radial surface)) influence on the collection of solid wood spectra and a comparison of found variable selection methods for NIR spectral variables optimization were conducted, including significant Multivariate Correlation (sMC), Regularized elimination procedure (Rep), Iterative predictor weighting (Ipw) and Genetic algorithm (Ga). Models made by random calibration data selection were conducted 200 times performance evaluation. Results These results indicate that 90° angle models display relatively highest efficiency than other angle models, mixed angle model yield a satisfied WBD prediction results as well and could reduce the influence of grain angle. Rep method shows a higher efficiency than other methods which could eliminate the uninformative variables and enhance the predictive performance of 90° angle and mix angle models. Conclusions This study is potentially shown that the WBD (g/cm3) on solid wood across grain angles and varies wood species could be measured in a rapid and efficient way using NIR technology. Combined with the PLSR model, our methodology could serve as a tool for wood properties breeding and silviculture study.

The nutrition and quality of bamboo shoots from different species have a large variation, and traditional methods used for the classification of different bamboo shoot species are expensive and time-consuming. Here, the capability of near-infrared reflectance (NIR) spectroscopy to identify bamboo shoot species in a time-and cost-effective manner was examined. The NIR spectra of four bamboo shoot species were collected. Three classification models, a support vector machine (SVM), partial least squaresdiscriminant analysis (PLSDA), and random forest (RF), were calibrated. Several spectra pre-processing methods and their combination were trained before model calibration for the best classification model collection; each model was run 200 times for the calculation of the prediction error and model stability checking. The SVM model combined with the Det+2nd derivative had the best performance with an overall accuracy of 0.95. The use of less than 16% of the full-length NIR spectra produced a similar high accuracy of 0.91. Eight important regions,