| 3 | Classification of Soybean Pubescence from Multispectral Aerial Imagery显示文摘The accurate determination of soybean pubescence is essential for plant breeding programs and cultivar registration.Currently,soybean pubescence is classified visually,which is a labor-intensive and time-consuming activity.Additionally,the three classes of phenotypes(tawny,light tawny,and gray)may be difficult to visually distinguish,especially the light tawny class where misclassification with tawny frequently occurs.The objectives of this study were to solve both the throughput and accuracy issues in the plant breeding workflow,develop a set of indices for distinguishing pubescence classes,and test a machine learning(ML)classification approach.A principal component analysis(PCA)on hyperspectral soybean plot data identified clusters related to pubescence classes,while a Jeffries-Matusita distance analysis indicated that all bands were important for pubescence class separability.Aerial images from 2018,2019,and 2020 were analyzed in this study.A 60-plot test(2019)of genotypes with known pubescence was used as reference data,while whole-field images from 2018,2019,and 2020 were used to examine the broad applicability of the classification methodology.Two indices,a red/blue ratio and blue normalized difference vegetation index(blue NDVI),were effective at differentiating tawny and gray pubescence types in high-resolution imagery.A ML approach using a support vector machine(SVM)radial basis function(RBF)classifier was able to differentiate the gray and tawny types(83.1%accuracy and kappa=0:740 on a pixel basis)on images where reference training data was present.The tested indices and ML model did not generalize across years to imagery that did not contain the reference training panel,indicating limitations of using aerial imagery for pubescence classification in some environmental conditions.High-throughput classification of gray and tawny pubescence types is possible using aerial imagery,but light tawny soybeans remain difficult to classify and may require training data from each field season. | Robert W.Bruce Istvan Rajcan John Sulik | 2021 | Plant Phenomics2021，3，1： | 1 |
| 5 | High-efficiency circularly polarized emission from liquid-crystalline platinum complexes显示文摘Realizing both a high emission efficiency and luminescence dissymmetry factor(g_(lum))in circularly polarized solution processable organic light-emitting diodes(CP-OLEDs)remains a significant challenge.In this contribution,two chiral phosphorescent liquid crystals based on cyclometalated platinum complexes are prepared,in which the chiral s-2-methyl-1-butyl group is introduced into the cyclometalating ligand and the mesogenic fragment is attached to the periphery of the ancillary ligand.The platinum complexes exhibit both smectic and chiral nematic phases as evidenced by polarized optical microscopy,differential scanning calorimetry and small-angle X-ray diffraction.Remarkably,a high photoluminescent quantum efficiency of over 78%and clear circularly polarized luminescent signal with g_(PL)of about 10^(-2)are observed for the complexes.Further,solution-processed CP-OLEDs show maximum external quantum efficiencies(EQE)of over 15%and strong circularly polarized electroluminescent signals with a g_(EL)≈10^(-2).This research demonstrates that both liquid crystallinity and the number of chiral centers play key roles in improving the chiroptical property,paving the way for a new approach for the design of high-efficiency CPL emitters. | Peng Fan Zhou Fang Shengyue Wang Qiwei Dong Chen Xiao Alice J.McEllin Duncan W.Bruce Weiguo Zhu Yafei Wang | 2023 | Chinese Chemical Letters2023，34，6： | 0 |
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