In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the in...In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.展开更多
This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standar...This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.展开更多
Objective Our aim is to construct an indicator system for the graduate dissertation quality evaluation,based on Fuzzy Analytical Hierarchy Process(FAHP).Methods First,we reviewed the related literature to identify and...Objective Our aim is to construct an indicator system for the graduate dissertation quality evaluation,based on Fuzzy Analytical Hierarchy Process(FAHP).Methods First,we reviewed the related literature to identify and select possible factors.Second,we developed an analytic hierarchy process framework.展开更多
The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native ba...The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82% of the variance.The second common factor,including ash,the total starch,soluble fiber,VB_(3),Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei.展开更多
激光粉末床熔融(laser powder bed fusion, LPBF)技术作为金属增材制造领域的前沿工艺,已被成功应用于航空航天等高端制造领域。然而多物理场强耦合效应易引发熔池动态失稳,导致制件内部孔隙缺陷频发,严重影响成形质量稳定性。传统监测...激光粉末床熔融(laser powder bed fusion, LPBF)技术作为金属增材制造领域的前沿工艺,已被成功应用于航空航天等高端制造领域。然而多物理场强耦合效应易引发熔池动态失稳,导致制件内部孔隙缺陷频发,严重影响成形质量稳定性。传统监测手段受限于成本高、部署困难等瓶颈,难以满足工业化生产需求。为此,提出声发射-深度学习融合的在线监测与内部质量智能判别方法。研制了基于声发射传感器的LPBF过程在线监测系统,通过工艺过程全周期声发射信号监测揭示声发射信号特征与成形质量间的映射规律,构建了包含逾8万组样本的熔池声发射数据。针对熔池微弱波动特征提取难题,构建了基于自适应傅里叶神经算子(AFNO)的频域特征提取网络和Kolmogorov-Arnold网络(KAN)的高维特征映射分类器,通过多尺度时域特征融合机制解析熔池动态特性,并借助高维流形精确映射高维特征,实现了声发射信号中微弱波动特征的增强表征和高精度质量判别。试验结果表明:研制的监测系统可有效捕获熔池的动态行为,所提方法质量判别精度达97%以上。展开更多
基金Supported by Heilongjiang Provincial Fruit Tree Modernization Agro-industrial Technology Collaborative Innovation and Promotion System Project(2019-13)。
文摘In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.
文摘This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.
文摘Objective Our aim is to construct an indicator system for the graduate dissertation quality evaluation,based on Fuzzy Analytical Hierarchy Process(FAHP).Methods First,we reviewed the related literature to identify and select possible factors.Second,we developed an analytic hierarchy process framework.
基金Supported by Chnia Agriculture Research Systemthe Scientific Research Fund of the Key Technology and Research and Development of Barley Characteristic Agricultural Products Processing(XZ201901NA04)Development and Industrialization Application of Xizang Highland Barley Baijiu(XZ202001ZY0017N)。
文摘The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82% of the variance.The second common factor,including ash,the total starch,soluble fiber,VB_(3),Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei.
文摘激光粉末床熔融(laser powder bed fusion, LPBF)技术作为金属增材制造领域的前沿工艺,已被成功应用于航空航天等高端制造领域。然而多物理场强耦合效应易引发熔池动态失稳,导致制件内部孔隙缺陷频发,严重影响成形质量稳定性。传统监测手段受限于成本高、部署困难等瓶颈,难以满足工业化生产需求。为此,提出声发射-深度学习融合的在线监测与内部质量智能判别方法。研制了基于声发射传感器的LPBF过程在线监测系统,通过工艺过程全周期声发射信号监测揭示声发射信号特征与成形质量间的映射规律,构建了包含逾8万组样本的熔池声发射数据。针对熔池微弱波动特征提取难题,构建了基于自适应傅里叶神经算子(AFNO)的频域特征提取网络和Kolmogorov-Arnold网络(KAN)的高维特征映射分类器,通过多尺度时域特征融合机制解析熔池动态特性,并借助高维流形精确映射高维特征,实现了声发射信号中微弱波动特征的增强表征和高精度质量判别。试验结果表明:研制的监测系统可有效捕获熔池的动态行为,所提方法质量判别精度达97%以上。
