Hongfei Lv

Prof. Hongfei Lv


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2009 in Environmental and Experimental Botany
Verified
Journal Article
Closed access
YDYajuan Dai
Yajuan Dai
ZSZonggen Shen
Zonggen Shen
YLYing Liu
Ying Liu
LWLanlan Wang
Lanlan Wang
DHDavid Hannaway
David Hannaway
HLHongfei Lv
Hongfei Lv


1 June 2011 in LWT
Verified
Journal Article
Open access
HZHong Zheng
Hong Zheng
HLHongfei Lv
Hongfei Lv
In this study, the usefulness of different mathematical models to predict the retention of ascorbic acid (AA), total phenols (TP) and DPPH radical scavenging activity (SA) of pasteurized pineapple juices during storage has been evaluated. The results indicate that first-order kinetic model provided the best prediction of the degradation of AA (MAE = 0.0059; MRE = 0.0117; MSE = 0.0001; R 2 = 0.9995) whereas Weibull model provided the less satisfactory prediction (MAE = 0.2387; MRE = 0.2911; MSE = 0.0769; R 2 = 0.9993). In addition, zero-order (MAE = 0.0016; MRE = 0.0017; MSE = 0.0000; R 2 = 0.9992) and first-order (MAE = 0.0027; MRE = 0.0029; MSE = 0.0000; R 2 = 0.9989) kinetic models are adequate models for application in the prediction of TP loss, and first-order kinetic (MAE = 0.0294; MRE = 0.0549; MSE = 0.0015; R 2 = 0.9845) and Weibull (MAE = 0.0533; MRE = 0.0881; MSE = 0.0044; R 2 = 0.9823) models are recommended to predict the change of SA. These results show that the behaviors of AA, TP and SA during storage of juices can be accurately described by different prediction models. Therefore, the selection of the most adequate model is of great importance to predict nutritional deterioration in food products during storage.

24 July 2012 in PLOS ONE
Verified
Journal Article
Open access
PDF file
PSPeng Sun
Peng Sun
NMNitin Mantri
Nitin Mantri
HLHeqiang Lou
Heqiang Lou
YHYa Hu
Ya Hu
DSDan Sun
Dan Sun
HLHongfei Lv
Hongfei Lv
We investigated if elevated CO2 could alleviate the negative effect of high temperature on fruit yield of strawberry (Fragaria × ananassa Duch. cv. Toyonoka) at different levels of nitrogen and also tested the combined effects of CO2, temperature and nitrogen on fruit quality of plants cultivated in controlled growth chambers. Results show that elevated CO2 and high temperature caused a further 12% and 35% decrease in fruit yield at low and high nitrogen, respectively. The fewer inflorescences and smaller umbel size during flower induction caused the reduction of fruit yield at elevated CO2 and high temperature. Interestingly, nitrogen application has no beneficial effect on fruit yield, and this may be because of decreased sucrose export to the shoot apical meristem at floral transition. Moreover, elevated CO2 increased the levels of dry matter-content, fructose, glucose, total sugar and sweetness index per dry matter, but decreased fruit nitrogen content, total antioxidant capacity and all antioxidant compounds per dry matter in strawberry fruit. The reduction of fruit nitrogen content and antioxidant activity was mainly caused by the dilution effect of accumulated non-structural carbohydrates sourced from the increased net photosynthetic rate at elevated CO2. Thus, the quality of strawberry fruit would increase because of the increased sweetness and the similar amount of fruit nitrogen content, antioxidant activity per fresh matter at elevated CO2. Overall, we found that elevated CO2 improved the production of strawberry (including yield and quality) at low temperature, but decreased it at high temperature. The dramatic fluctuation in strawberry yield between low and high temperature at elevated CO2 implies that more attention should be paid to the process of flower induction under climate change, especially in fruits that require winter chilling for reproductive growth.


1 May 2013 in Chemosphere
Verified
Journal Article
Closed access
XXXiaohong Xu
Xiaohong Xu
LXLingdan Xie
Lingdan Xie
XHXing Hong
Xing Hong
QRQin Ruan
Qin Ruan
HLHongfei Lv
Hongfei Lv
XLXingyi Liu
Xingyi Liu