肽聚糖对肉制品中产气荚膜梭菌芽孢萌发率影响及预测

该研究利用产气荚膜梭菌(Clostridium perfringens,C.perfringens)营养体及其芽孢肽聚糖以芽孢萌发率S、浑浊度OD_(600)%、Ca~(2+)-DPA%变化率等为指标比较不同肽聚糖对C.perfringens芽孢萌发的影响;并针对芽孢萌发率检测耗时、费力等问题,提出一种基于近红外光谱技术(near infrared spectroscopy,NIR)定量预测不同浓度肽聚糖诱导芽孢萌发率研究。首先原始光谱经不同方式预处理,获得最佳方法为标准正态变换,然后使用主成分分析和遗传-联合区间偏最小二乘法进行光谱数据降维及特征变量筛选,分别对不同浓度肽聚糖诱导芽孢S、OD_(600)%、Ca~(2+)-DPA%进行快速预测。结果表明:营养体肽聚糖可有效诱导芽孢萌发,而芽孢肽聚糖效果不明显。利用GA-si PLS筛选芽孢萌发特征变量的最佳特征区间分别是[3,9,11,14]、[1,7,12,15]和[7,8,12,17],其预测集R和RMSEP分别为0.872 6,0.861 1,0.884 1和0.769,0.218%,42.34%。研究结果表明,利用NIR结合GA-siPLS可定量预测肽聚糖诱导C.perfringens芽孢的萌发率,实现芽孢萌发的快速预测,为保证肉制品安全提供有效手段。     

基于SERS技术的基底增强效应对比及食源性芽孢快速检测

为了实现食源性芽孢的快速识别,该研究利用表面增强拉曼光谱技术,以产气荚膜梭菌芽孢(C.perfringens spores)、艰难梭菌芽孢(C.difficile spores)和生孢梭菌芽孢(C.sporogenes spores)为研究对象,将3种不同纳米溶胶材料Au NPs、Ag NPs和Au@AgNPs作为表面增强拉曼散射(Surface-enhanced Raman scattering,SERS)基底对食源性芽孢的增强效应进行对比,确定较佳增强效果的纳米材料,进一步开展基于较优纳米溶胶材料为基底的SERS技术对不同种属食源性芽孢的光谱解析及快速识别研究。结果表明,Au@Ag NPs对食源性芽孢的SERS增强效果最较好,其增强因子达3.49×10⁴,且光谱特异性和重现性良好。经拉曼光谱解析,Ca²⁺-DPA的拉曼峰是三种食源性芽孢的共有标志特征峰,拉曼振动峰在1 017、1 440和1 570 cm^-1波段显示且峰强度不同。C.perfringens芽孢在740、787、821、1 203、1 308和1 62...     

精油对熟制鸡胸肉中产气荚膜梭菌抑制效果预测模型研究

为研究不同香辛料精油对熟制鸡胸肉中产气荚膜梭菌(C.perfringens)的影响,该文以肉桂精油、艾草精油和茴香精油为研究对象,对C.perfringens标准株(ATCC13124)和分离株(C1)抑菌效果,筛选出抑制最佳浓度,采用BP神经网络构建C.perfringens的生长/残存动力学模型,并以相关系数(R~2)和均方根误差(RMSE)评价模型精度,以期快速预测不同精油浓度条件对C.perfringens影响。结果表明:经肉桂精油处理后的ATCC13124和C1浓度最低,抑制效果最强;采用BP神经网络模型构建不同精油对熟制鸡胸肉中C.perfringens的预测模型,肉桂精油对ATCC13124和C1的R~2分别为0.963和0.976,RMSE分别为0.327和0.271CFU/g,预测效果最佳;利用验证集对模型鲁棒性进行验证,结果表明R~2均在0.917以上,RMSE在0.200～0.640 CFU/g之间,结果表明,BP神经网络模型可以较好的预测熟制鸡胸肉中产气夹膜梭菌的生长/残存情况;为肉类加工过程中控制C.perfringens提供理论依据。     

基于高光谱与协同克里金的土壤耕作层含水率反演

为研究土壤耕作层(0~40 cm)含水率的空间分布情况,利用EO-1的Hyperion传感器高光谱数据,对研究区域(106°20′~109°19′E,40°19′~41°18′N)的表层(0~10 cm)含水率进行定量反演,并利用表层含水率反演结果作为协同克里金插值的协变量,同时利用103个采样点实测的耕作层含水率作为主变量,进行协同克里金插值。结果表明:通过特征指数法提取水分反演的敏感波段集中在1 295~2 224 nm波长区间,特征指数法模型校正的相关系数r0.5但模型验证的精度较低(r0.2);通过偏最小二乘法建模,模型校正的r0.8,模型验证的r0.5,效果较好;运用协同克里金插值时,将反演的表层含水率作为协变量,可以弥补主变量耕作层含水率样本点少,变异函数欠稳定的缺点,同时,所提取理论模型的块金值(C0)与基台值(C0+C)的比值均25%,随机因素比例小,模型稳健。此外,协同克里金插值方法与利用表层与耕作层含水率线性拟合进行预测相比,能够有效提高预测精度,决定系数r2和Nash效率系数(nash-sutcliffe modelling efficiency,NSE)分别提高72.6%和89.9%,因此,将高光谱反演与协同克里金方法相结合,可以综合两者优势,节约采样成本,提高预测效率。     

基于dbiPLS-SPA变量筛选的固态发酵湿度近红外光谱检测

为了提高基于近红外光谱技术的固态发酵关键过程参数——湿度快速检测的精度和稳定性,研究采用动态反向区间偏最小二乘（dbiPLS）法结合连续投影算法（SPA）进行最佳光谱子区间和特征组合变量的筛选,通过交互验证法确定偏最小二乘（PLS）模型的主成分因子数,并以预测均方根误差（RMSEP）和相关系数（Rp）作为模型的评价标准。试验结果显示,最佳dbiPLS-SPA模型筛选的组合变量个数为8,其RMSEP和Rp分别为1.1795%（质量分数）和0.9430。试验结果表明,dbiPLS-SPA是一个有效的波长组合变量筛选方法,可简化模型结构、增强模型精度和稳健性。     

拉曼光谱结合UVE-SVR算法预测加热食用油反式脂肪酸的含量

为实现拉曼光谱技术对食用油加热后反式脂肪酸(TFAs)含量的快速预测,将3种食用油在190℃下(常用煎炸温度)进行不同时间加热,每个样品采集36条拉曼光谱。首先,采用多项式平滑与标准正态变量变换(SNN)对原始光谱数据进行预处理,以去除背景和噪音的干扰,然后采用无信息变量消除法(UVE)对光谱数据进行特征变量筛选,最后分别基于全谱数据和筛选的特征光谱变量建立定性和定量分析模型,并对试验结果进行对比分析。结果表明,基于筛选后的变量,运用Fisher判别分析(FDA)建立定性判别模型,其判别正确率由40%~50%提升至90%以上,表明筛选后的变量能较好表征样品的特征信息;分别基于筛选变量和全谱数据,运用偏最小二乘回归(PLSR)、BP神经网络(BPNN)和支持向量回归机(SVR)方法,建立不同样品中TFAs含量的数学预测模型。通过对预测结果对比分析,表明UVE结合SVR方法具有良好的检测效果,菜籽油、大豆油、玉米油的测试集R²分别从0.850 4、0.943 5和0.753 4升至0.952 6、0.954 8和0.958 5。因此,利用UVE-SVR方法不仅简化了预测模型,提高了模型的稳定性和精度,也为食用油中TFA的快速检测提供了一种可行的方法。     

基于近红外光谱的绿茶滋味品质估测模型北大核心CSCD

绿茶中的茶多酚与氨基酸含量之比(即酚氨比)是评价绿茶滋味品质的量化指标。本文提出利用近红外光谱技术快速分析绿茶汤的酚氨比,并对光谱的特征变量进行筛选以提高模型的精度和稳定性。试验采用联合区间偏最小二乘法(siPLS)结合连续投影算法(SPA)筛选特征变量,建立酚氨比的估测模型,并与PLS、iPLS和siPLS方法建立的模型性能相比较。结果表明,应用siPLS结合SPA优选7个特征变量,主成分因子数为4时,所建模型性能最好,模型预测集相关系数(R p)为0.906,预测均方根误差(RMSEP)为0.258。对预测集30个样本的预测值与参考值进行t检验时,预测值与参考值无显著差异,说明模型准确可靠,可实现绿茶滋味品质的近红外光谱快速估测。     

利用光谱反射率预测烤烟叶片烟碱含量

以ASD Field spee FR 2500光谱仪测定了不同生育期不同氮钾处理的烤烟叶片光谱反射率,通过光谱反射率、一阶导数光谱和光谱特征变量与烟碱含量的相关分析和逐步回归模型筛选出特征波长,并对回归模型的预测效果进行检验.结果表明,一阶导数光谱回归方程预测效果最好、光谱反射率回归方程次之、特征变量回归方程最差.筛选出光谱反射率特征波长为1792 nm、一阶导数光谱特征波长为810 nm.光谱反射率和一阶导数光谱在427～712、741～810、1382～1879、1905～1969、2067～2338 nm范围内与烟碱含量相关性强.本研究为采用高光谱技术预测烟叶烟碱含量提供了理论参考.     

农杆菌介导的洋桔梗遗传转化体系的建立

以洋桔梗叶片为外植体,建立了植株再生体系,并在此基础上,用根癌农杆菌介导法,研究了影响洋桔梗转化的若干因素。结果表明,诱导最佳培养基为MS+6-BA 1.0mg/L+NAA 0.15mg/L,不定芽诱导率达74.5%;不定芽生根培养基为1/2MS+IBA 0.5 mg/L,生根率达90%。不定芽分化阶段和生根阶段的Km筛选浓度分别为45mg/L和15mg/L;根癌农杆菌菌液浓度OD600值为0.6,侵染时间10min,共培养时间3d,有利于抗性芽的产生。Km筛选得到的抗性植株经过PCR和Southern检测表明,八氢番茄红素合成酶基因(PSY)已经整合到洋桔梗基因组中。     

近红外透反射光谱测定单粒稻种的蛋白质含量

为探索NIR光谱技术在水稻种子蛋白质含量分析中的应用,本研究细致分析了单粒稻种在不同光谱采集方式下的近红外光谱(NIRS)特征,并利用离子束诱变育种得到的水稻9311突变体库的种子,建立准确性较好的单粒糙米和单粒稻种的蛋白质定量模型。结果表明,与漫反射光谱采集方式下的单粒糙米蛋白质模型相比,透反射和透射光谱采集方式下能得到相关性较好的糙米蛋白质模型,其中单粒糙米蛋白质最优定量模型的决定系数(R²)为0.97,预测均方根误差(RMSEP)为0.27%。在单粒稻种中,由于种壳的反射作用,漫反射光谱采集方式下依然无法建立准确性高的蛋白质模型,透反射光谱采集方式下能够建立具有一定预测能力的蛋白质定量模型(RMSEP=0.81%),透射光谱采集方式下能够建立准确性高的蛋白质定量模型(R²=0.96,RMSEP=0.24%)。本研究结果为无损快速分析单粒稻种提供了一种解决方法。     

基于可见/近红外光谱的菠萝水心病无损检测

水心病近年严重危害菠萝产业,探究一种菠萝水心病的无损检测方法对保证上市果品、指导采后处理、促进产业提升具有重要意义。该研究采用自行搭建的菠萝可见/近红外光谱无损智能检测平台,考虑实际应用成本与效果,搭载覆盖不同波段（400～1 100、900～1 700和400～1 700 nm）的检测器对菠萝样本进行采样,随后人工标定水心病发生程度。研究结果表明,3种不同光谱波段对菠萝水心程度检测的较优方法均为：采用全波段进行多项式平滑（Savitzky Golay,SG）处理,再进行标准正态变量校正（Standard Normal Variate,SNV）,最后结合概率神经网络（Probabilistic Neural Network,PNN）建模识别。其中,400～1 100 nm所建模型对菠萝水心病训练集的回判正确率为98.51%,对验证集的检测正确率为91.18%;900～1 700 nm所建模型对菠萝水心病训练集的回判正确率为100%,对验证集的检测正确率为62%;400～ 1 700 nm所建模型对菠萝水心病训练集的回判正确率为100%,对验证集的检测正确率为91.18%。主成分分析（Principal Component Analysis,PCA）和偏最小二乘回归（Partial Least Squares Regression,PLSR）分析结果均显示,采用400～ 1 700 nm能轻微提升400～1 100 nm的检测效果。综合考虑实际应用成本与效果,实际应用建议采用400～1 100 nm光谱结合SG + SNV + PNN对菠萝水心病进行识别。研究结果证明可见/近红外光谱技术可为菠萝水心病无损、快速、智能检测提供有效的解决方案,为相关领域提供参考。     

Soil chemical attributes,nutrient uptake and yield of no-till crops as affected by phosphogypsum doses and parceling in southern Brazil

This study evaluated soil chemical attributes, leaf nutrient concentrations and grain yield of corn (Zea mays), barley (Hordeum vulgare), common bean (Phaseolus vulgaris) and wheat (Triticum aestivum) as affected by phosphogypsum (PG) rates and split application to a Typic Hapludox under no-till from Southern Brazil. A Randomized complete block design was used, with factorial treatment structure (5 x 2) consisting of increasing PG rates (0, 3, 6, 9 and 12 Mg ha^?1) either in single or split (half dose, two consecutive years) application. PG rates have reduced concentrations of Al³⁺, increasing Ca²⁺, SO₄^2- and pH values in soil layers up to 0.8 m. Leaf concentrations of Ca (between 28 and 42%) and S (between 6% and to 50%) increased in all crops, while leaf levels of Mg decreased on corn (?16%), bean (?22%) and wheat (?14%) by PG rates. Compared to the control, PG rates between 4.0 and 6.1 Mg ha^?1 promoted increases of 11%, 10% and 10% on corn, barley and wheat yields, respectively. There was no effect of PG on common bean’s yield. Phosphogypsum was effective for improving soil fertility, plant nutrition and crop yields. Applying the PG annually at one-half rate gave best overall results.     

Effect of Alkalized Phosphogypsum on Soil Chemical and Biological Properties

Phosphogypsum (PG) was mixed with calcium hydroxide [Ca(OH)₂], ranging from 0 to 5%, to determine the optimal amount of Ca(OH)₂ required to alkalize the acidity of PG. The alkalized PG by 4% of Ca(OH)₂ addition was selected for field tests to evaluate the effects of alkalized PG on soil microbial, chemical properties, and yield of Chinese cabbage. Soil pH increased with increasing application rate of the alkalized PG and decreased with the unmodified PG application. Available phosphorus (P), water‐soluble sulfate (SO₄ ^2?), and exchangeable potassium (K), calcium (Ca), and magnesium (Mg) increased significantly with increasing application rate of alkalized and unmodified PG. Microbial biomass carbon (C) and nitrogen (N) concentrations, soil enzyme activities, and the yield of Chinese cabbage in the alkalized PG application were greater than those of unmodified PG application. We concluded that alkalizing PG by mixing it with an alkaline material such as Ca(OH)₂ can turn it into a useful material for agricultural utilization.     

小麦种子发芽率近红外定量分析模型的优化

The backward interval partial least squares (BiPLS) and the synergy interval partial least squares (SiPLS) were applied to select the characteristic spectral regions representing the germination rate of 84 wheat seeds and build the near infrared (NIR) quantitative analysis model of wheat seed germination rate.Results from comparison showed that the models built by two variable selection methods had better predictive ability than full-spectral partial least squares(PLS) model.The optimal model was obtained by SiPLS with the calibration and prediction correlation coefficient(R) at 0.902 and 0.967 respectively, and ratio of performance to standard deviate (RPD) at 3.75.Based on this, the physical chemistry significance of characteristic spectral regions was analyzed.The characteristic spectral of wheat seed germination rate contained characteristic peaks of water, protein, starch, fiber, which were the internal nutrients of the seed that influence the germination ability, thus explaining the mechanism of measuring wheat seed germination rate using NIR to a certain extent.     

Ca2+对苯丙烯酸胁迫下黄瓜种子萌发特性的影响

以黄瓜（Cucumis Sativus L.）种子为材料,研究钙浸种对苯丙烯酸（CA）胁迫下黄瓜种子萌发的影响及其机理。结果表明,CA对黄瓜种子萌发有明显的抑制作用,且抑制程度随CA浓度（0.25~1.0mmol·L-1）的增加而提高。CA胁迫下,黄瓜种子的发芽势、发芽率下降,膜结构受损,透性增大,呼吸速率、α-淀粉酶和蛋白酶活性降低,淀粉、蛋白质消耗率下降,钙浸种（500 mg·L-1CaCl2）可以缓解CA对种子萌发的抑制作用,表现为发芽率提高,膜透性降低,呼吸速率、α-淀粉酶、蛋白酶活性以及淀粉和蛋白质消耗率提高。     

小麦种子发芽率近红外定量分析模型的优化（英文）

The backward interval partial least squares(Bi PLS)and the synergy interval partial least squares(Si PLS)were applied to select the characteristic spectral regions representing the germination rate of 84 wheat seeds and build the near infrared(NIR)quantitative analysis model of wheat seed germination rate.Results from comparison showed that the models built by two variable selection methods had better predictive ability than full-spectral partial least squares(PLS)model.The optimal model was obtained by Si PLS with the calibration and prediction correlation coefficient(R)at 0.902 and 0.967 respectively,and ratio of performance to standard deviate(RPD)at 3.75.Based on this,the physical chemistry significance of characteristic spectral regions was analyzed.The characteristic spectral of wheat seed germination rate contained characteristic peaks of water,protein,starch,fiber,which were the internal nutrients of the seed that influence the germination ability,thus explaining the mechanism of measuring wheat seed germination rate using NIR to a certain extent.     

基于GA-LSSVM和近红外傅里叶变换的霉变板栗识别

为克服板栗近红外光谱变量多、共线性强等缺点,该文对标准正态变量变换预处理后的板栗近红外光谱进行傅里叶变换,并用不同方法建模,提高识别精度。采用试探法提取近红外光谱傅里叶系数,建立了基于最小二乘支持向量机分类器的霉变板栗识别模型。当提取前35点傅里叶系数时,板栗的平均识别正确率为93.56%;构造GA-LSSVM算法,建立的霉变板栗识别模型所用傅里叶系数减少为13点,对测试集中合格板栗、表面霉变板栗和内部霉变板栗的平均识别正确率分别为95.89%、100%和98.25%,板栗的总体平均识别正确率提高到97.54%。为霉变板栗的识别提供了快速鉴别分析方法。     

Bacteria associated with Glomus clarum spores influence mycorrhizal activity

The effects of bacteria associated with arbuscular mycorrhizal fungal (AMF) spores on spore germination, growth in vitro and on the pea-AMF symbiosis were evaluated. Bacterial colonies were recovered from untreated Glomus clarum NT4 spores and NT4 spores decontaminated with 5% chloramine-T for 30, 45 and 60 min on five different media. Both G+ and G− bacteria were recovered from untreated NT4 spores, whereas only G+ bacteria were isolated from decontaminated spores. An in vitro assessment of the effect of spore-associated bacteria on clean, decontaminated NT4 spores revealed that (i) most of the bacteria isolated from untreated spores generally did not significantly alter spore function, (ii) some bacteria isolated from clean, decontaminated spores inhibited or stimulated NT4 spore germination, (iii) stimulation of spore germination occurred only when bacteria were in contact with spores, and (iv) inhibition of spore germination was the result of volatile bacterial metabolites. A stimulatory bacterial isolate, Bacillus pabuli LA3, significantly (P<0.05) enhanced the shoot growth, AMF-colonization, shoot N content and P use efficiency of NT4-inoculated 6 week-old pea plants over that of plants co-inoculated with an inhibitory bacterial isolate, Bacillus chitinosporus LA6a and NT4.     

山梨醇螯合钙对NaCl胁迫下油菜种子萌发的影响

本文通过控制钙源种类(螯合态钙和游离态钙)、两种形态钙配比(不同螯合率)及螯合态钙浓度等3组试验探究山梨醇螯合钙对NaCl胁迫下油菜种子萌发的影响.结果表明:当培养液中NaCl浓度为150或170 mmol/L时严重影响油菜种子的萌发和胚根生长,添加两种形态钙后均能显著提高NaCl胁迫下种子活力和发芽率,促进胚根的生长...