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1.
Food Chem ; 404(Pt A): 134555, 2023 Mar 15.
Article in English | MEDLINE | ID: mdl-36444034

ABSTRACT

The cryo-protective effects of different concentrations of antifreeze protein (AFP, 0 %, 0.10 %, 0.15 %, 0.20 %, 0.25 %, w/v) on chicken frozen at -18 °C for different storage perispeeods were investigated by monitoring water holding capacity (WHC), water distribution, color, protein properties, microstructure and histological changes. The results showed that AFP significantly maintained the quality traits of frozen chicken. Treatment with 0.20 % AFP represented highest cryo-protective effect on the WHC and protein properties during frozen storage. The carbonyl content with 0.20 % AFP was significantly lower than that of without AFP (P < 0.05). Besides, the myofibrils of chicken supplemented with AFP, especially with 0.25 % AFP, had significantly tighter microstructure, smaller ice crystal area and equivalent diameter than those of without AFP treatment (P < 0.05) after 75 d freezing storage. Overall, AFP had a positive effect to improve the quality of frozen chicken, and it was a potential, safe and efficient cryo-protective agent.


Subject(s)
Chickens , alpha-Fetoproteins , Animals , Freezing , Antifreeze Proteins , Water
2.
Sci Total Environ ; 789: 147803, 2021 Oct 01.
Article in English | MEDLINE | ID: mdl-34052492

ABSTRACT

Drought is pervasive global hazard and seriously impacts ecology. Particularly, vegetation drought, which is chiefly driven by soil moisture (SM) deficiency, has a direct bearing on grain production and human livelihoods. Various drought indices associated with vegetation and SM conditions have been proposed to monitor and detect vegetation drought. In this study, we evaluated the performance of eight drought indices, including Drought Severity Index (DSI), Evaporation Stress Index (ESI), Normalized Vegetation Supply Water Index (NVSWI), Temperature-Vegetation Dryness Index (TVDI), Temperature Vegetation Precipitation Dryness Index (TVPDI), Vegetation Health Index (VHI), Self-calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Evapotranspiration Index (SPEI), for capturing SM dynamic (derived from Copernicus Climate Change Service) across the six main vegetation coverage types of China. Our results showed DSI and ESI had the best overall performance. When exploring the reasons for the uncertainty of these indices (except SC-PDSI and SPEI) in the evaluation, we found that, in the non-arable regions, the time lag effect of drought indices on SM, the average state and rangeability of corresponding variables and the climatic conditions (precipitation and temperature) all impacted the performance of DSI, ESI, NVSWI, TVPDI and VHI. In the arable region, cropland types (paddy field and non-paddy field) and the uncertainty of SM data mainly caused the uncertainties of the above five indices. With regard to the TVDI, abnormalities of dry and wet edges fitting may be the primary factor affecting its performance. These results demonstrated that these drought indices with reliable and robust performance of capturing SM dynamics can be suggested to characterize the trend of SM. Certainly, this study can provide a reference for the improvement of existing drought indices and the establishment of new drought indices.


Subject(s)
Droughts , Soil , China , Climate Change , Humans , Temperature
3.
Sci Total Environ ; 711: 134585, 2020 Apr 01.
Article in English | MEDLINE | ID: mdl-32000314

ABSTRACT

Drought is one of the most frequent disasters occurring in North China and has a great influence on agriculture, ecology and economy. To monitor drought of typical dry areas in North China, Shandong Province, this paper proposed composite drought indices using multivariable linear regression (MCDIs) to integrate Tropical Rainfall Measuring Mission (TRMM) derived precipitation, Global Land Data Assimilation System Version 2.1 (GLDAS-2.1) derived soil moisture, Moderate Resolution Imaging Spectroradiometer (MODIS) derived land surface temperature (LST) and normalized difference vegetation index (NDVI) from 2013 to 2017 (March to September). Pearson correlation analyses were performed between single remote sensing drought indices and in-situ drought indices, standardized precipitation evapotranspiration index (SPEI), in different time scales to assess the capability of single indices over Shandong Province. The multivariable linear regression method was used to established MCDIs, and mediator and moderator variables were introduced to optimize the model. The correlation coefficients (r) between MCDIs and SPEIs was higher than that between each single index and SPEIs. Additionally, when we investigate the correlations of different MCDIs with both standardized precipitation index (SPI) and moisture index (MI), the highest r values with both 1-month SPI and MI were acquired by the MCDI based on 1-month SPEI (MCDI-1). This suggested MCDI-1 was suitable to monitor meteorological drought. Also, the comparison between MCDI based on 9-month SPEI (MCDI-9) and soil moisture showed MCDI-9 was a good indicator for agricultural drought. Therefore, multivariable linear regression and MCDIs were recommended to be an effective method and indices for monitoring drought across Shandong Province and similar areas.

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