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Physicochemical and Sensory Properties of japonica Rice Varied with Production Areas in China 被引量:8
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作者 YANG Xiao-yu LIN Zhao-miao +6 位作者 LIU Zheng-hui Md A Alim BI Jun-guo LI Gang-hua WANG Qiang-sheng WANG Shao-hua DING Yan-feng 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2013年第10期1748-1756,共9页
Northeast of China and Jiangsu Province are major production areas of japonica rice in China.Rice from northeast of China is well-known for its good-eating and appearance quality,and that from Jiangsu Province is view... Northeast of China and Jiangsu Province are major production areas of japonica rice in China.Rice from northeast of China is well-known for its good-eating and appearance quality,and that from Jiangsu Province is viewed as inferior.However,little is known concerning the difference in physicochemical and sensory properties of rice between the major two production areas.Analysis of 16 commercial rice samples showed marked differences in physicochemical properties,including chalky grain rate,contents of amylose and protein and pasting properties between the two main areas.Northeastern rice contained more shortchain amylopectin as compared with Jiangsu rice.However,Jiangsu rice is comparable to northeastern rice in terms of sensory quality including overall acceptability and textural properties of springiness,stickiness and hardness as evaluated by trained panel.Our results indicated the limitation of conventional index of physicochemical properties,and suggested the necessity of identification of new factors controlling rice sensory property.In addition,the taste analyzer from Japan demonstrates limitation in distinguishing the differences between northeastern and Jiangsu rice,and therefore needs localization to fit China. 展开更多
关键词 rice sensory property physicochemical property production environment
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Satellite-derived primary productivity and its spatial and temporal variability in the China seas 被引量:2
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作者 TAN Saichun SHI Guangyu 《Journal of Geographical Sciences》 SCIE CSCD 2006年第4期447-457,共11页
The spatial and temporal variability of primary productivity in the China seas from 2003 to 2005 was estimated using a size-fractionated primary productivity model. Primary productivity estimated from satellite-derive... The spatial and temporal variability of primary productivity in the China seas from 2003 to 2005 was estimated using a size-fractionated primary productivity model. Primary productivity estimated from satellite-derived data showed spatial and temporal variability. Annual averaged primary productivity levels were 564.39, 363.08, 536.47, 413.88, 195.77, and 100.09 gCm2a1 in the Bohai Sea, northern Yellow Sea (YS), southern YS, northern East China Sea (ECS), southern ECS, and South China Sea (SCS), respectively. Peaks of primary productivity appeared in spring (April-June) and fall (October and November) in the northern YS, southern YS, and southern ECS, while a single peak (June) appeared in the Bohai Sea and northem ECS. The SCS had two peaks in primary productivity, but these peaks occurred in winter (January) and summer (August), with the winter peak far higher than the summer peak. Monthly averaged primary productivity values from 2003 to 2005 in the Bohai Sea and southern YS were higher than those in the other four seas during most months, while those in the southem ECS and SCS were the lowest. Primary productivity in spring (March-June in the southern ECS and April-July in the other five areas) contributed approximately 41% on average to the annual primary productivity in all the study seas except the SCS. The largest interannual variability also occurred in spring (average standard deviation = 6.68), according to the satellite-derived estimates. The contribution during fall (October-January in the southern ECS and August-November in the other five areas) was approximately 33% on average; the primary productivity during this period also showed interannual variability. However, in the SCS, the winter (December-March) contribution was the highest (about 42%), while the spring (April-July) contribution was the lowest (28%). The SCS did share a feature with the other five areas: the larger the contribution, the larger the interarmual variability. Spatial and temporal variability of satellite-derived ocean primary productivity may be influenced by physicochemical environmental conditions, such as the chlorophyll-a concentration, sea surface temperature, photosynthetically available radiation, the seasonally reversed monsoon, river discharge, upwelling, and the Kuroshio and coastal currents. 展开更多
关键词 China seas CHLOROPHYLL-A physicochemical environmental factors ocean primary productivity spatiotemporal variability
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