为研究匀强高压静电场(uniform high voltage electrostatic field,UHVEF)对绿芦笋嫩茎的保鲜效果,以绿芦笋为原料,探讨UHVEF处理对采后绿芦笋嫩茎贮藏品质指标的影响。经200 k V/m和250 k V/m对采后绿芦笋嫩茎进行持续15 d处理,每隔2 ...为研究匀强高压静电场(uniform high voltage electrostatic field,UHVEF)对绿芦笋嫩茎的保鲜效果,以绿芦笋为原料,探讨UHVEF处理对采后绿芦笋嫩茎贮藏品质指标的影响。经200 k V/m和250 k V/m对采后绿芦笋嫩茎进行持续15 d处理,每隔2 d取样,统计分析不同处理下其失重率、呼吸强度、可溶性糖含量和过氧化物酶(POD)活性等指标变化,试验设置对照组。结果表明:与对照组相比,采用适当的UHVEF处理对采后绿芦笋嫩茎进行处理,具有良好的保鲜效果。在不同匀强高压静电场的处理下,绿芦笋嫩茎的失重率、呼吸强度、可溶性糖含量和过氧化物酶活性等各项生理指标均表现出抑制性,场强越大,抑制效果越明显。失重率增长速度明显减缓;呼吸强度明显减弱,呼吸跃变时间推迟了4 d,到达峰值的时间推迟了9 d;可溶性含糖量存在先上升后下降趋势,后熟过程推迟2～4 d,后期下降速率平缓。POD酶活性呈先上升又下降的趋势,活性达到峰值点推迟了2 d。经UHVEF处理对采后绿芦笋失重率、呼吸强度、可溶性糖含量和POD酶活性的影响均差异性显著。研究结果为UHVEF用于采后绿芦笋嫩茎保鲜贮藏提供了理论依据。展开更多
Rainfall-triggered landslides have posed significant threats to human lives and property each year in China. This paper proposed a meteorologicalgeotechnical early warning system GRAPES-LFM(GRAPES: Global and Regional...Rainfall-triggered landslides have posed significant threats to human lives and property each year in China. This paper proposed a meteorologicalgeotechnical early warning system GRAPES-LFM(GRAPES: Global and Regional Assimilation and Pr Ediction System; LFM: Landslide Forecast Model),basing on the GRAPES model and the landslide predicting model TRIGRS(Transient Rainfall Infiltration and Grid-based Regional Slope-Stability Model) for predicting rainfall-triggered landslides.This integrated system is evaluated in Dehua County,Fujian Province, where typhoon Bilis triggered widespread landslides in July 2006. The GRAPES model runs in 5 km×5 km horizontal resolution, and the initial fields and lateral boundaries are provided by NCEP(National Centers for Environmental Prediction) FNL(Final) Operational Global Analysis data. Quantitative precipitation forecasting products of the GRAPES model are downscaled to 25 m×25 m horizontal resolution by bilinear interpolation to drive the TRIGRS model. Results show that the observed areas locate in the high risk areas, and the GRAPES-LFM model could capture about 74% of the historical landslides with the rainfall intense 30mm/h. Meanwhile, this paper illustrates the relationship between the factor of safety(FS) and different rainfall patterns. GRAPES-LFM model enables us to further develop a regional, early warning dynamic prediction tool of rainfall-induced landslides.展开更多
文摘为研究匀强高压静电场(uniform high voltage electrostatic field,UHVEF)对绿芦笋嫩茎的保鲜效果,以绿芦笋为原料,探讨UHVEF处理对采后绿芦笋嫩茎贮藏品质指标的影响。经200 k V/m和250 k V/m对采后绿芦笋嫩茎进行持续15 d处理,每隔2 d取样,统计分析不同处理下其失重率、呼吸强度、可溶性糖含量和过氧化物酶(POD)活性等指标变化,试验设置对照组。结果表明:与对照组相比,采用适当的UHVEF处理对采后绿芦笋嫩茎进行处理,具有良好的保鲜效果。在不同匀强高压静电场的处理下,绿芦笋嫩茎的失重率、呼吸强度、可溶性糖含量和过氧化物酶活性等各项生理指标均表现出抑制性,场强越大,抑制效果越明显。失重率增长速度明显减缓;呼吸强度明显减弱,呼吸跃变时间推迟了4 d,到达峰值的时间推迟了9 d;可溶性含糖量存在先上升后下降趋势,后熟过程推迟2～4 d,后期下降速率平缓。POD酶活性呈先上升又下降的趋势,活性达到峰值点推迟了2 d。经UHVEF处理对采后绿芦笋失重率、呼吸强度、可溶性糖含量和POD酶活性的影响均差异性显著。研究结果为UHVEF用于采后绿芦笋嫩茎保鲜贮藏提供了理论依据。
基金supported by The National Basic Research Program of China(973)(Grant No.2013CB430106)National Natural Science Foundation of China(Grant No.41375108)Scientific Research&Innovation Projects for Academic Degree students of ordinary Universities of Jiangsu(Grant No.CXLX13_474)
文摘Rainfall-triggered landslides have posed significant threats to human lives and property each year in China. This paper proposed a meteorologicalgeotechnical early warning system GRAPES-LFM(GRAPES: Global and Regional Assimilation and Pr Ediction System; LFM: Landslide Forecast Model),basing on the GRAPES model and the landslide predicting model TRIGRS(Transient Rainfall Infiltration and Grid-based Regional Slope-Stability Model) for predicting rainfall-triggered landslides.This integrated system is evaluated in Dehua County,Fujian Province, where typhoon Bilis triggered widespread landslides in July 2006. The GRAPES model runs in 5 km×5 km horizontal resolution, and the initial fields and lateral boundaries are provided by NCEP(National Centers for Environmental Prediction) FNL(Final) Operational Global Analysis data. Quantitative precipitation forecasting products of the GRAPES model are downscaled to 25 m×25 m horizontal resolution by bilinear interpolation to drive the TRIGRS model. Results show that the observed areas locate in the high risk areas, and the GRAPES-LFM model could capture about 74% of the historical landslides with the rainfall intense 30mm/h. Meanwhile, this paper illustrates the relationship between the factor of safety(FS) and different rainfall patterns. GRAPES-LFM model enables us to further develop a regional, early warning dynamic prediction tool of rainfall-induced landslides.
