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| 1 | Predicting the growth performance of growing-finishing pigs based on net energy and digestible lysine intake using multiple regression and artificial neural networks models显示文摘Backgrounds:Evaluating the growth performance of pigs in real-time is laborious and expensive,thus mathematical models based on easily accessible variables are developed.Multiple regression(MR)is the most widely used tool to build prediction models in swine nutrition,while the artificial neural networks(ANN)model is reported to be more accurate than MR model in prediction performance.Therefore,the potential of ANN models in predicting the growth performance of pigs was evaluated and compared with MR models in this study.Results:Body weight(BW),net energy(NE)intake,standardized ileal digestible lysine(SID Lys)intake,and their quadratic terms were selected as input variables to predict ADG and F/G among 10 candidate variables.In the training phase,MR models showed high accuracy in both ADG and F/G prediction(R^(2)_(ADG)=0.929,R^(2)_(F/G)=0.886)while ANN models with 4,6 neurons and radial basis activation function yielded the best performance in ADG and F/G prediction(R^(2)_(ADG)=0.964,R^(2)_(F/G)=0.932).In the testing phase,these ANN models showed better accuracy in ADG prediction(CCC:0.976 vs.0.861,R^(2):0.951 vs.0.584),and F/G prediction(CCC:0.952 vs.0.900,R^(2):0.905 vs.0.821)compared with the MR models.Meanwhile,the“over-fitting”occurred in MR models but not in ANN models.On validation data from the animal trial,ANN models exhibited superiority over MR models in both ADG and F/G prediction(P<0.01).Moreover,the growth stages have a significant effect on the prediction accuracy of the models.Conclusion:Body weight,NE intake and SID Lys intake can be used as input variables to predict the growth performance of growing-finishing pigs,with trained ANN models are more flexible and accurate than MR models.Therefore,it is promising to use ANN models in related swine nutrition studies in the future. | Li Wang Qile Hu Lu Wang Huangwei Shi Changhua Lai Shuai Zhang | 2022 | Journal of Animal Science and Biotechnology2022，13，6： | 5 |
| 2 | Hydrogenase as the basis for green hydrogen production and utilization显示文摘Hydrogenase is a paradigm of highly efficient biocatalyst for H_(2) production and utilization evolved in nature. A dilemma is that despite the high activity and efficiency expected for hydrogenases as promising catalysts for the hydrogen economy, the poor oxygen tolerance and low yield of hydrogenases largely hinder their practical application. In these years, the enigmas surrounding hydrogenases regarding their structures, oxygen tolerance, mechanisms for catalysis, redox intermediates, and proton-coupled electron transfer schemes have been gradually elucidated;the schemes, which can well couple hydrogenases with other highly efficient(in)organic and biological catalysts to build novel reactors and drive valuable reactions, make it possible for hydrogenases to find their niches. To see how scientists put efforts to tackle this issue and design novel reactors in the fields where hydrogenases play crucial roles, in this review,recent advances were summarized, including different strategies for protecting enzyme molecules from oxygen, enzyme-based assembling systems for H_(2) evolution in the photoelectronic catalysis, enzymatic biofuel cells for H_(2) utilization and storage and the efficient electricity-hydrogen-carbohydrate cycle for high-purity hydrogen and biofuel automobiles. Limitations and future perspectives of hydrogenasebased applications in H_(2) production and utilization with great impact are discussed. In addition, this review also provides a new perspective on the use of biohydrogen in healthcare beyond energy. | Haishuo Ji Lei Wan Yanxin Gao Ping Du Wenjin Li Hang Luo Jiarui Ning Yingying Zhao Huangwei Wang Lixin Zhang Liyun Zhang | 2023 | Journal of Energy Chemistry2023，，10： | 0 |
| 3 | Effects of Salt Stress on Stipa breviflora Seedlings and Antioxidant Isozymes显示文摘Stipa breviflora seeds,collected from Inner Mongolia,were sowed on MS medium containing 0,50,100,150,200 mmol/L NaC l,to investigate the effects of salt stress on the physiological phenotype and antioxidant enzyme activity of S.breviflora seedlings.The results showed the germination rate,root length and fresh weight of seedlings were all influenced by salinity.Germination rate,root length and fresh weight of seedlings were significantly inhibited by 100,150 and50 mmol/L NaC l,and were 62%,1.30 cm,0.299 g,respectively.With NaC l content increasing,the trend of superoxide dismutase( SOD) and peroxidase( POD) activity was rising at first and then falling,and the activity of SOD and POD reached the maximum at 150 and 100 mmol/L,48.6 and 6 766 U/g,respectively.The activity of catalase( CAT) continued to increase and reached the maximum at 150 mmol/L,299 U/g.The isozyme zymogram showed that SOD 2-4,POD 1-2,and CAT 1-2 were positively correlated with salinity tolerance of S.breviflora seedlings. | Jing WANG Hongzhou ZI Huangwei LI Yanxia NING Ling LUO | 2018 | Agricultural Biotechnology2018，7，6： | 0 |
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