猪繁殖与呼吸综合征免疫学研究进展

分别在苹果采收前一个月和两个月时用不同浓度的烯效唑(S3307)喷施寒富苹果果实,研究S3307对苹果果皮花色素形成和果实品质的影响。目的是找到有效促进苹果果皮着色并提高果品品质的最佳S3307浓度,并揭示其作用机理。结果表明:50mg·L-1S3307喷果后,苹果着色效果明显,可溶性糖含量增加,有机酸含量减少,抗坏血酸(ASA)含量和蛋白质含量升高。这说明50mg·L-1的S3307有良好的着色作用并能改善苹果的品质,因此这种试剂在生产上可能有一定的应用价值。另外研究发现,花色素含量与可溶性糖含量和糖酸比显著正相关,花色素含量与有机酸含量和叶绿素含量显著负相关。     

雾培对番茄植株生长、产量和品质的影响

以土壤栽培为对照,采用山崎番茄营养液配方研究了雾培对番茄的生长、产量和品质的影响。结果表明:雾培番茄植株长势旺盛,叶片叶绿素含量和净光合速率增加,每穗果的单果重和单株产量提高。而茎粗和单株结果数变化不大。此外,果实VC含量、可溶性糖含量与有机酸含量,以及糖酸比均下降,风味降低。这说明雾培可促进植株叶片光合作用的提高,并促进光合产物的运转,增加番茄果实产量,但不利于果实的品质的改善。     

不同水分亏缺程度对番茄生长发育、产量和果实品质的影响

试验设置5个灌水处理:每桶浇水量分别为2000(CK),1500(T1),1000(T2),500(T3),300mL(T4),研究不同水分亏缺程度对番茄生长发育、产量和果实品质的影响。结果表明:随着浇水量的减少番茄株高、株幅、茎粗、干物重、单株产量均明显下降,总灌水量与番茄的第1、第2穗果的单果重和单株产量之间均呈极显著相关关系,与果实中Vc、可溶性糖呈极显著负相关关系,与有机酸含量呈显著负相关关系。T1、T2处理产量下降幅度较小,而果实中Vc、可溶性糖含量较对照有显著的增加,是较好的处理。     

不同浓度NaCl处理对番茄果实生长、产量和品质的影响

番茄定植栽培在营养液槽中,采用不同浓度的NaCl进行盐胁迫处理试验。结果表明:盐胁迫抑制番茄植株株高和茎粗的生长,降低果实的横径与纵径长度;降低番茄的单株产量和单果重;但0.08mol.L-1和0.16mol.L-1 NaCl处理可以提高番茄果实中Vc、可溶性固形物及有机酸的含量,0.16mo.lL-1 NaCl处理可以提高番茄果实中可溶性糖的含量,盐胁迫处理使番茄的糖酸比降低。     

不同基肥对日光温室土壤肥力、番茄产量和品质的影响

针对北京郊区日光温室中基肥施用状况,设计了长期施用秸秆有机肥、膨化鸡粪和缓释肥3个处理,对日光温室土壤肥力及番茄品质的影响进行测定。结果表明:秸秆有机肥处理土壤速效养分含量较高,土壤有机质含量在3个处理中表现最高,为32.0g.kg-1;长期施用膨化鸡粪土壤酸化快,土壤养分含量处于中等;缓释肥作为基肥施用,可加速土壤速效养分积累,但土壤有机质含量较低;从番茄果实品质结果看,秸秆有机肥处理果实中Vc、可溶性固形物、可溶性糖、游离氨基酸及糖酸比值分别为13.60μg.g-1、54.4mg.g-1、37.6mg.g-1、62.22μg.g-1、9.68,都显著高于其他两个处理。缓释肥处理的果实各种营养品质都不如有机肥处理果实含量高。实验还分析了土壤养分含量与番茄果实品质、产量的相关性,结果表明:土壤有机质、速效钾、全氮含量与果实中多项营养品质指标和产量呈极显著正相关。     

鲜食粉果番茄可溶性固形物含量及遗传分析

鲜食粉果番茄果实的可溶性固形物含量（SSC）为3．15-6．20％，其主要成分是可溶性糖和有机酸，其中，可溶性糖含量占SSC的61．887％，可溶性糖中99％以上成分为果糖和葡萄糖；果实中有机酸含量占SSC的8．635％，其主要成分是柠檬酸，占有机酸含量的80％左右。SSC受环境的影响较大，在露地比保护地有较大的变异范围，果实转色期到商品成熟期SSC变化最快。SSC遗传符合加一显模式，广义遗传力为0．971，狭义遗传力为0．401，显性基因约为6组，显性基因少于隐性基因，控制SSC性状的基因多为效基因。     

弱光对不同基因型辣椒坐果和果实品质的影响

在塑料拱棚中通过人工遮光模拟弱光环境(35%光强),研究了弱光对8个不同基因型辣椒坐果和果实品质的影响。结果表明:弱光下辣椒单株产量、坐果率、单株坐果数、果实硬度显著下降,可溶性固形物、维生素C和可溶性糖含量减少,但单果重、果形指数和果实含水量增加。弱光下辣椒果实叶绿素和类胡萝卜素含量增加,叶绿素a/b比值下降。不同甜椒(果实味甜)与辣椒(果实味辣)材料对弱光的适应性上存在差异。     

不同氮水平下钾营养对大棚番茄产量及品质的影响

在不同氨水平下钾营养对大棚无土栽培番茄产量及品质的影响结果表明适当提高钾肥浓度,可提高番茄坐果率、产量．以及果实中Vc含量、可溶性糖和有机酸含量,并且果实硝酸盐含量和筋腐果发生率明显降低。但钾肥浓度过高,会使番茄产量、品质降低。氮钾配施十分重要,本试验以N     

钾镁锌硼钼肥对椪柑产量和品质的影响

在成龄椪柑桔园连续3年施肥试验结果表明,施用钾、镁、锌、硼和钼肥对椪柑产量和品质有不同程度的影响。在红泥土和河沙土上氮磷钾平衡施较不施钾显著增加椪柑产量,分别增产14.3%和13.5%。在施用氮磷钾基础上施镁、锌、硼和钼肥,可使红泥土上椪柑果实产量依次平均增产8.6%、7.9%、7.4%和2.7%,可使河沙土上的椪柑果实产量依次平均增产4.3%、4.2%、3.1%和2.2%。施钾能增加果实的维生素C、全糖和可溶性固形物含量,而能降低全酸含量和糖/酸比。在施用氮磷钾基础上施镁、锌和硼能增加椪柑果实的维生素C、全糖和可溶性固形物含量。施钼肥导致果实中全酸含量的提高和糖/酸比的降低。在红泥土和河沙土上施钾使椪柑果皮增厚,施镁使果皮变薄,施锌硼对果皮影响甚微,施钼能明显地使果皮增厚。     

施肥处理对菜用大豆和普通大豆品质形成的影响

菜用大豆生产在东北地区乃至全国都在不断发展,为了给菜用大豆配套生产提供理论依据,探讨菜用大豆和普通大豆的特异性,以普通大豆品种2个、引进菜用品种4个为试材,探讨施肥处理对不同类型大豆籽粒品质形成的影响。结果表明：就不同类型品种来说,普通大豆品种铁丰29号的品质最好,菜用大豆品种沈农引133的品质最好。T2磷酸二铵施肥处理使各品种的蛋白质含量提高,而T3磷酸二铵施肥处理使各品种的蛋白质含量降低;T2和T3磷酸二铵施肥处理使各品种的脂肪含量、蛋脂总量、可溶性糖含量提高。在不同施肥处理下,籽粒脂肪积累呈“S”型曲线。同样施肥水平下,菜用大豆的蛋白质和可溶性糖含量高于普通大豆,而脂肪含量低于普通大豆。蛋白质含量与磷酸二铵施用量呈负相关,脂肪含量与磷酸二铵施用量呈显著正相关,蛋脂总量、可溶性糖含量与磷酸二铵施用量呈不显著的正相关。     

Modeling antimicrobial effect of different grape pomace and extracts on S.aureus and E.coli in vegetable soup using artificial neural network and fuzzy logic system

In this study, antibacterial activities of the grape pomace powders (GPP) and grape pomace extracts (GPE) of Turkeys’ five different grape varieties (Emir, Gamay, Kalecik Karasi, Narince and Okuzgozu grape varieties) were determined against Staphylococcusaureus and Escherichiacoli in vegetable soup at 2, 5 and 10% concentrations. Antibacterial effects of GPE were more effective than those of the GPP against the bacteria. The bacterial counts decreased with increasing extract concentration. The highest antibacterial activity of the GPE was for Gamay and Kalecik Karasi against both bacteria. The 10% concentration of Gamay GPP completely inhibited S.aureus at the end of 120th h. Compared to E.coli, S.aureus was more sensitive to all GPP and GPE. This bacterium was inhibited by 10% concentrations of all the extracts at the initial storage time. Data were analyzed to predict antibacterial effects of the GPP and GPE against both bacteria by adaptive neuro fuzzy inference system (ANFIS) and artificial neural network (ANN) and multiple linear regression (MLR) models. As a result, ANFIS model was found to be better than the ANN and MLR for predicting antibacterial effects of GPP and GPE against S.aureus and E.coli in the soup.     

一种FPGA+多DSP系统复位信号的设计方法

针对FPGA和多DSP系统中各部分所需的复位信号需满足相应的复位时间和正确次序的要求,在介绍了两种传统复位信号产生方法的基础上,提出了一种利用外部器件TPS3307产生原始复位信号,并在FPGA中构建逻辑硬件看门狗,采用异步复位、同步释放的方式复位多DSP的设计方法。给出部分关键设计的源程序,并在一片Xilinx公司的FPGA(XC2V1000)芯片与4片ADI公司的DSP(TS201)组成的系统中进行了验证,结果表明该设计方法能提高系统稳定性和可靠性。     

Identification of grape diseases using image analysis and BP neural networks

Prevention and treatment of diseases are critical to improve grape yield and quality. Automatic identification of grape diseases is important to prevent insect pests timely and effectively. This study proposed an automatic detection method for grape leaf diseases based on image analysis and back–propagation neural network (BPNN). The Wiener filtering method based on wavelet transform was applied to denoise the disease images. The grape leaf disease regions were segmented by Otsu method, and morphological algorithms were used to improve the lesion shape. Prewitt operator was utilized to extract the complete edge of lesion region. Five effective characteristic parameters, namely, perimeter, area, circularity, rectangularity, and shape complexity, were extracted. The proposed recognition model for grape leaf diseases based on BPNN could efficiently inspect and recognize five grape leaf diseases: leaf spot, Sphaceloma ampelinum de Bary, anthracnose, round spot, and downy mildew. Results indicated that the proposed detection system for grape leaf diseases could be used to inspect grape diseases with high classification accuracy.

     

基于叶片形态特征的葡萄品种自动识别

葡萄在全世界种植范围较广,葡萄品种识别对葡萄资源统计、新品种鉴定及遗传资源保护都有重要意义。以成熟叶片为基本材料,不变矩、面积、周长、主叶脉长度和叶柄长度等11维特征向量为基础数据,采用叶片特征选择、图像处理、特征值提取、建立分类模型等方法,运用国际葡萄与葡萄酒组织形态分类方法和改进的欧式距离等技术开发一个基于葡萄叶片数字图像的葡萄品种自动识别软件。共测试17种酿酒和3种野生葡萄,识别率达87%。该方法具有自动化、识别速度快、花费低、省时省力等特点,可应用于葡萄病虫害的识别、杂交新品种双亲的判定等。     

基于HOG的酿酒葡萄叶检测

在酿酒葡萄生长状态与病虫害自动监测中,需要在图像中检测出葡萄叶片,通过提取葡萄叶片图像的方向梯度直方图（HOG）特征投入到支持向量机（SVM）分类器中以实现对葡萄叶片的识别;结合多尺度目标定位和均值漂移算法还可以自动确定图像中葡萄叶片的位置。实验结果表明,使用线性核函数训练后的分类器对葡萄叶片和四种常见杂草的识别率达95.5%。该方法对光照和环境变化有较好的鲁棒性,自然条件下成像的叶片图像的葡萄叶片检出率达到了80%以上。     

Comparative study of data mining techniques for the authentication of organic grape juice based on ICP-MS analysis

Authenticity is a substantial matter and a current concern of the organic food industry. Organic foods are appreciated by customers because of their benefits to health and friendliness to the environment. However, currently, the most common way for customers to confirm that the organic food they are buying are organic is by certificates and label information, which can be fraudulent. Furthermore, it is interesting to gain insight into organic food composition and visualize which mineral components are fundamental in the differentiation of organic from conventional food. This work addresses these problems using data mining concepts and techniques in a comparative study of organic and conventional food focusing on grape juice, but the proposed methodology can be adapted and employed for analysis of other types of organic food. This article presents a data mining analysis of the elemental composition of 37 grape juice samples collected from different locations in Brazil. The elemental composition of grape juice samples was determined by inductively-coupled plasma-mass spectrometry (ICP-MS). Forty-four elements were determined in the two types of samples, namely organic and conventional grape juice. Special effort was devoted to selecting the variables (elements) that best described each type of grape juice. Predictive models based on support vector machines, neural networks and decision trees were developed to successfully differentiate organic from conventional grape juice samples. We found that, according to the F-score, Chi-square and Random Forest Importance variable selection measures, the components Na, Sn, P, K, Sm and Nd are among the most important variables in the differentiation of organic and conventional grape juice samples. Particularly, the components Na, Sn and K received first, second or third position according to at least two methods. On the other hand, all variable selection methods considered indicated that Ag, Zn, Cr, Be and Pd were among the least important variables for the differentiation of organic and conventional grape juices. SVM yielded an accuracy of 89.18%, both CART and MLP achieved an accuracy of 86.48%.     

腐植酸复混肥对葡萄养分吸收利用的影响

为明确不同腐植酸复混肥施用量,对葡萄生长及土壤养分的影响,采取以二年生葡萄幼树进行盆栽试验。结果表明,与等养分无机化肥相比,腐植酸复合肥明显提高了葡萄植株对N、P、K肥的利用率,使土壤中的N素释放减缓,P的移动性和K的含量有较明显提高,并使土壤中有机质含量有增加的趋势。     

基于多尺度残差神经网络的葡萄叶片病害识别

葡萄叶片不同程度的病害具有一定的相似性,目前对于葡萄叶片病害的识别多为病害种类识别,对不同程度病害识别的研究较少,且传统识别方法对于不同程度病害识别准确率较低。提出一种基于多尺度残差神经网络（Multi-Scale ResNet）的葡萄叶片病害识别方法。对葡萄叶片病害图像进行数据增强与叶片区域标注后,使用Mask R-CNN提取葡萄叶片部位,通过引入多尺度卷积以改变ResNet底层对不同尺度特征的响应,利用加入的SENet提升网络的特征提取能力,并将图像输入Multi-Scale ResNet中进行识别。实验结果表明,该方法的平均识别准确率达到90.83%,相比ResNet18提高了2.87个百分点。     

干旱荒漠区不同覆盖对酿酒葡萄园土壤的综合效应研究

针对甘肃河西地区大面积栽培酿酒葡萄而水资源短缺的现状,试验研究了地面覆膜、覆麦秸、覆麦壳等节水措施对干旱荒漠地区酿酒葡萄园土壤水分、温度和肥力等因子的效应,结果表明,几种节水措施均有明显增温效应,提高土壤含水量。覆草效果优于覆膜。覆麦秸和麦壳表现前期降温,后期增温保温的双重效应,并增加了土壤有机质及速效N、P、K含量,其中土壤有机质含量增加17.36%~18.51%,全氮增加7.35%~8.82%,速效磷增加8.51%~9.96%,速效钾增加47.5%~53.9%,土壤容重降低0.19gcm-3~0.20g cm-3,可溶性固形物含量提高0.5%~1.7%,产量提高3722.5~4162.5kg hm-2。     

Hybrid electronic tongue for the characterization and quantification of grape variety in red wines

A multisensor system combined with multivariate analysis was applied to the characterization of red wines and to the quantification of the grape variety percentage. The proposed system, known as hybrid electronic tongue, consists of a colorimetric optofluidic system and an array of electrochemical sensors. Three monovarietal red wines were studied: Pinot Noir, Merlot and Cabernet Sauvignon. Homemade mixtures were elaborated from these wines according to a Simplex experimental design with 60 samples. The data obtained were treated using advanced chemometric tools like Principal Component Analysis (PCA) and Soft Independent Modeling Class Analogy (SIMCA) for the classification of the wine mixtures and Partial Least Squares (PLS) regression for the quantification of the grape variety composition. The results have shown a good classification of the grape varieties and the identification of the mixtures with Pinot Noir up to 75%. Besides, using the PLS regression, the system has demonstrated a high potential for quantifying the percentage of each grape variety.