可见光催化合成异喹啉酮生物碱的创新实验及课程转化实践思考

为有效拓展现阶段本科有机化学教学实验开设的范围,让学生了解学科前沿研究热点与新合成技术,本实验以异喹啉酮生物碱的光化学合成为导向,将有机光化学和连续流动化学融合运用于本科实验教学。本实验选择氮化碳半导体材料作为非均相光催化剂,氧气作为绿色、经济的氧化剂,在可见光介导下实现异喹啉酮生物碱的合成。实验主要由间歇光反应和连续流光反应合成异喹啉酮生物碱以及合成高附加值天然产物corydaldine三部分组成,涉及搭建简易连续流光化学反应装置、反应监测、分离纯化、产物表征等多个重要环节,指导学生认识光化学反应知识,也让学生熟悉微量有机反应中薄层分析法、柱层析及相关仪器的操作,并将所学的红外、核磁共振波谱法等理论知识运用到产物的结构分析中,提升学生的主观能动性、综合实践能力和环保意识。本创新实验竞赛项目符合实验绿色化、微型化的新理念,适合于在化学化工专业本科生的有机化学实验和综合化学实验中开展,将其转化本科实验教学项目,可充分体现“以赛促建”“以赛促教”“以赛促学”的重要意义。

Model for estimating the weight-loss ratio of damaged Korla fragrant pears

To predict the weight-loss ratio of Korla fragrant pears effectively,improve commodity value and study the variation laws of the weight-loss ratio of damaged fragrant pears during storage,this study predicted the weight-loss ratio of fragrant pears by utilizing the generalized regression neural network(GRNN),support vector regression(SVR),partial least squares regression(PLSR)and error back propagation neural network(BPNN).The prediction performances of GRNN,SVR,PLSR and BPNN models were compared comprehensively,and the optimal model was determined.In addition,the optimal prediction model was verified.The results show that weight-loss ratio of fragrant pears increases gradually with the extension of storage time.During storage,the weight-loss ratio of fragrant pears is positively related to the degree of damage.The trained GRNN,SVR,PLSR and BPNN models can be used to predict the weight-loss ratio of fragrant pears.The BPNN model is the most accurate in predicting the weight-loss ratio of damaged fragrant pears(R^(2)=0.9929;RMSE=0.2138).It has also been proved to have good predictive effect in production practice(R^(2)=0.9377,RMSE=0.7138).The research findings can provide references to predict the delivery quality and time of delivery of Korla fragrant pears.

Mechanical properties and finite element analysis of walnut under different cracking parts

In order to reduce mechanical damage and improve extraction quality of walnut kernel during walnut cracking,the Wen-185 walnut cultivar was selected as the research object,and the mechanical properties of walnut under different cracking parts were assessed by combining compression tests and finite element analysis(FEA)method.The compression test results showed that the relationships between rupture force and deformation of walnut were nonlinear,and the cracking process of shell mainly consisted of three stages(elastic stage,plastic stage and composite elastic-plastic stage).The best method to crack walnut was the spherical compression,and the peak value of rupture force and corresponding deformation were 211.83 N and 1.68 mm,respectively.In condition of spherical compression,the shell-breaking rate,first-grade kernel rate and whole kernel rate were(91.67±2.89)%,(88.33±2.89)%,(80.00±5.00)%,respectively.The FEA results indicated that spherical compression was also the suitable way to rupture walnut,which resulted in the obvious propagation trends of shell cracks and further a better integrity of extracting walnut kernel.Therefore,the spherical contact form between walnut and cracking parts may be considered to design the structural shape of key components of walnut cracking machines,which was consistent with the analysis of compression test results.The comparison between experiment results and FEA results showed that the established FEA model can be used to analyze the mechanical properties of walnut.The research results can provide references for the structural design and optimization of key components of cracking machines for walnut or other nut crops.

Comprehensive evaluation of Korla fragrant pears and optimization of plucking time during the harvest period

To optimize the harvest of Korla fragrant pears and to provide a theoretical basis for post-harvest processing,a total of 26 basic indices of Korla fragrant pears,including their morphology,quality,and softening age,were investigated.The harvest period ranged from August 22nd to October 6th,samples were collected every 5 d(totally 10 plucking days,indicated as H1-H10).The results indicated that changes in pectin content were the main causes of softening in fragrant pears.The scavenging of free radicals mainly occurred because of the collaborative effects of superoxide dismutase(SOD)and catalase(CAT).In the harvest periods H1-H3,the hardness,titratable acid(TA),chlorophyll content,density,and diameter of the stone cells,as well as the cellulose and hemicellulose content of the Korla fragrant pears were at their highest.During the periods H7-H10,the single-fruit weight,fruit horizontal and vertical diameter,color coordinates L,a*,b*,soluble-solids content(SSC),SOD activity,CAT activity,and water-soluble pectin were higher than in the other plucking periods.The highest vitamin C(VC)content and moderate values for a variety of indicators were observed during H3-H7.Variations in the Korla fragrant pears during H1-H3 mainly manifested through changes in softening-related parameters.During H3-H10,changes in the softening-related,aging-related,color-related,and quality indices had a dominant role.On this basis,some suggestions for the post-harvest processing of fragrant pears have been proposed.Fruit,during H1-H3,are suitable for transportation and storage;during H7-H10 are suitable for fresh-eating and further processing;and during H3-H7,exhibited moderate values for a variety of indicators and had the highest commercial value.This research provides a systematic evaluation of the characteristics of mature Korla fragrant pears during the harvest period and can form the basis for fruit quality control and processing of Korla fragrant pears.

Construction method of quantitative evaluation model for the maturity of Korla fragrant pear

The maturity variation laws of Korla fragrant pears were explored for a quantitative evaluation of harvest maturity to solve the reasonable matching between harvest maturity of Korla fragrant pears and market quality demands.Korla fragrant pears from different harvesting periods were chosen as the research objects.Some quality indexes were chosen as the evaluation indexes per industry standards,including hardness,soluble solid content(SSC),single-fruit weight,fruit longitudinal diameter,fruit equatorial diameter,pericarp color parameters(L*,a*,and b*),and titratable acid.Variation data of these quality indexes with accumulated temperature were collected.Scores of several quality indexes were gained through principal component analysis.A mathematical model of scores and accumulated temperatures was constructed.On this basis,a quantitative maturity model of Korla fragrant pears was constructed.Results demonstrate that SSC,single-fruit weight,fruit longitudinal diameter,fruit equatorial diameter,L*,a*,and b*are significantly and positively correlated with the accumulated temperature.Meanwhile,hardness and titratable acid showed significant negative correlations with the accumulated temperature.Relations between scores of principal components and accumulated temperature conform to the Sigmoidal model.The constructed quantitative maturity model of Korla fragrant pears can quantify the maturity of pears.Research conclusions can provide insight into the harvest periods,evaluate Korla fragrant pears’maturity,and lay a theoretical foundation for quantitative research on fruit maturity.

新冠肺炎疫情下我国开展应急能力建设文献计量及可视化分析

新型冠状病毒病(corona virus disease 2019,COVID-19)疫情对人类的生命健康和财产安全带来直接威胁,这凸显了公共卫生领域应急能力的重要性和迫切性[1]。"应急能力"一词涵盖主体多元,广泛存在于危机发生的各个阶段,包括危机发生前准确及时的预警反馈能力,危机发生时客观真实的分析处理能力,危机发生后有效解决并恢复常态,是一种综合性危机应对能力[2]。

Non-destructive detection of the fruit firmness of Korla fragrant pear based on electrical properties

In order to achieve the non-destructive detection of the firmness of Korla fragrant pear during the ripening period,the characteristic variables integrating the parallel equivalent inductance(Lp),quality factor(Q),parallel equivalent capacitance(Cp),dissipation factor(D),parallel equivalent resistance(Rp)and impedance(Z)were formulated through principal component analysis(PCA).Further,based on the characteristic variables,the models were established for predicting the firmness of Korla fragrant pear by using the generalized regression neural network(GRNN)and back-propagation neural network(BPNN).The results showed that firmness has significant correlations with the six electrical parameters.The first two principal components(PCs)were selected as the characteristic variables of the electrical parameters.GRNN exhibited the best performance in predicting firmness(R2=0.9628,RMSE=0.383).The results could provide important references for non-destructive detection of the quality of Korla fragrant pear.