射频识别技术在畜禽养殖中的应用与展望

随着畜禽规模养殖的发展,高度集约化养殖模式将影响畜禽的健康状况、疫病防控和福利水平。一种无接触、无应激的射频识别（Radio Frequency Identifi cation,RFID）技术应运而生,该技术可以在无损状态下采集畜禽的行为、生理生化和养殖环境指标,从而为评估集约化养殖的效果和影响提供基础数据。文章讨论了三种常见类型的RFID系统在畜禽养殖中的应用,系统地比较了各类系统的优缺点及适宜应用场景,进一步提出RFID在畜禽养殖中的未来应用方向,以期为深化畜禽信息采集的研究提供参考。     

灰铸铁生产技术的一些新进展

对灰铸铁的研究现状和生产中的一些新技术做了评述。重点介绍了高强度薄壁灰铸铁的生产现状以及先进的制造工艺和先进的制造手段在灰铸铁生产中应用所取得的技术成果。     

Effects of a Dual‐Frequency Frequency‐Sweeping Ultrasound Treatment on the Properties and Structure of the Zein Protein

We investigated the effects of a dual‐frequency frequency‐sweeping ultrasound (DFFSU) treatment on the functional properties and structure of zein. The solubility of ultrasound‐treated zein proteins increased slightly but significantly as the treatment time increased. The results showed that the DFFSU treatment had an obvious influence on the mean particle size and the size distribution. A significant (P < 0.05) increase in the size of the particles with respect to time was observed after a sonication time of more than 20 min in zein solutions. Differential scanning calorimetry results showed that sonication alters the thermal behavior of zein. Circular dichroism spectra showed a small increase in the percentage of ordered structure elements within the protein molecule. After 60 min of ultrasonication, the percentage of α‐helix structures increased by 0.9%, whereas the percentage of β‐sheets and β‐turns decreased by 0.5%. Microstructural analyses by scanning electron microscopy showed that several microholes appeared in the zein following ultrasonic pretreatment. Under the conditions investigated in this study, DFFSU treatment was found to affect the studied functional properties of the zein protein. This technology could be used to obtain improved functional properties in some protein samples.     

Effects of Vacuum Mixing,Water Addition,and Mixing Time on the Quality of Fresh Chinese White Noodles and the Optimization of the Mixing Process

In this study, the effects of mixing process parameters (degree of vacuum, water addition, and mixing time under vacuum) on the cooking and sensory quality properties of Chinese white noodles were investigated by using one commercial‐scale noodle production line and one typical commercial wheat flour. Noodle appearance, firmness, elasticity, smoothness, and total quality scores were significantly improved as the degree of vacuum increased from 0 to 0.06 MPa, although lower sensory scores and larger cooking losses occurred when noodles were mixed at 0.08 MPa. Noodles with a water addition of 35% had the highest total score and the highest scores for each sensory factor. As mixing time increased, the sensory score of cooked noodles increased initially and then decreased. With a mixing time of 7 min, the sensory score was the highest and cooking loss was the lowest. The results of response surface methodology indicated that fresh noodle quality was most affected by the water addition, followed by vacuum degree. Added water was a more important source of variation for appearance, firmness, stickiness, smoothness, total score, and cooking loss than degree of vacuum and mixing time, whereas degree of vacuum was the predominant source of variation for color and elasticity. The interactions between the factors had little effect on sensory and cooking properties. The optimal mixing conditions were determined to be as follows: degree of vacuum, 0.06 MPa; added water, 35.6%; and mixing time, 7.25 min. Furthermore, vacuum mixing produced a more even, coherent, and closed microstructure for the sheeted dough than nonvacuum mixing.     

基于高斯自适应拟合的苹果目标分割方法研究

苹果目标的准确识别是苹果机械化采摘需要解决的关键问题之一。为此,基于YUV颜色空间模型,提出了一种结合色差分量与高斯自适应拟合算法的苹果目标分割方法。该方法采用首先将苹果目标由RGB颜色空间转换至YUV颜色空间,并利用色差分量V建立果实与背景分割的高斯分布拟合模型,根据拟合结果自动获取分割阈值,以实现自然场景下苹果目标的准确分割。为了验证文中算法的有效性,利用多幅图像进行了试验并与Otsu自适应阈值分割算法进行了比较。试验结果表明,采用文中算法得到的苹果果实的平均检出率达87.08%,识别率领先Otsu算法9.91%。因此,对于着色度较为均匀的苹果目标,采用高斯自适应拟合方法可以有效提高其识别率。     

拖拉机自动转向系统设计及仿真

以TN654拖拉机为平台,基于原车液压转向系统,设计一套比例方向电磁阀组和电控单元(ECU),构建了能响应程序控制的自动转向系统。通过建立阀控缸动力系统数学模型,利用Mat Lab对该系统PD控制性能进行仿真分析。仿真结果显示:系统最大迟滞0.24、1.8s内均能达到平衡点,表明系统具有良好的控制精度和响应性,符合拖拉机自动驾驶作业需求。     

玉米播种机排种监测的试验研究与设计

在对目前玉米播种机排种监测方法的研究基础上,设计了一套新的玉米播种机排种监测的试验方法:将4对光电传感器并排安装在导种管内壁以监测空或堵的情况并进行报警;同时,利用安装在排种盘的中心轴上的空心转速编码器,测出排种盘转速连同试验所得的空穴率,从而得出玉米排种量。试验结果表明:该方案模拟实际空或堵的报警率达100%,排种量检测平均精度98.37%,各项性能指标均达到了实际要求。     

三种基因型羽衣甘蓝筛选适合叶绿体转化材料

以3种不同基因型的羽衣甘蓝品种"皱叶红心"、"白鸥"和"红鸥"为试材,以MS培养基为基础培养基,分别添加不同质量浓度的6-BA、NAA、IBA激素,筛选不同品种真叶叶片不定芽的诱导频率,同时确定不同材料对除草剂双丙氨膦和抗生素壮观霉素的致死临界质量浓度,为羽衣甘蓝的叶绿体转化研究筛选受体材料。结果表明:影响羽衣甘蓝叶片诱导不定芽因素中,激素质量浓度的影响比品种的影响更大;当诱导培养基中的6-BA质量浓度为1.0mg/L、NAA质量浓度为0.1mg/L时,诱导效果最佳,是3个品种的最适培养基;按照由高到低的顺序排列,3个品种的不定芽诱导率依次为"红鸥"、"白鸥"和"皱叶红心",因此择优利用品种"红鸥"作为后续转基因研究的受体材料;分别利用双丙氨膦和壮观霉素的不同质量浓度梯度进行筛选,研究二者对"红鸥"品种叶片分化的影响,发现双丙氨膦和壮观霉素的最低抑制质量浓度分别为4mg/L和50mg/L。该研究结果对今后利用叶绿体遗传转化技术改良羽衣甘蓝品种提供了技术支持。     

亚美马褂木不同生根类型硬枝扦插苗生长研究

以珍珠岩基质中亚美马褂木硬枝扦插苗为研究对象,研究了扦插苗生根类型、不定根数、不定根长、苗高、基径、鲜样质量和根芽距等生长指标,为选择高生长和高生根率无性系提供参考。结果表明:亚美马褂木扦插苗不定根形成有3种生根类型即皮部生根类型、中间生根类型和愈伤生根类型,其中愈伤生根类型扦插苗成活数量多,中间生根类型扦插苗生长最好,愈伤生根类型扦插苗生长较好。扦插苗鲜样质量与不定根数、不定根长、苗高和基径等相关系数达极显著正相关,苗高与不定根数和基径、不定根数与基径等相关系数达极显著正相关,不定根数与生根类型相关系数达极显著负相关。     

不同处理方法对小松菜冻藏期保鲜品质的影响

以新鲜小松菜为试材,采用小苏打复合液、乙酸锌复合液2种不同保绿途径对其冻藏前进行烫漂处理,并对小松菜钙、钠、锌元素含量进行测定,比较了2种不同前处理消解方法精确性,研究了不同处理方法对冻藏期小松菜相关品质指标的影响。结果表明:2种保绿途径均显著延缓了小松菜总叶绿素含量的损失(P0.05),不同程度增加了样品中钙、钠、锌离子含量,其中金属离子保绿途径的乙酸锌复合液处理样品的锌离子残留量超标,相比而言,碱保绿途径的小苏打复合液处理对冻藏期小松菜相关元素残留安全性及护绿效果较好,处理时应避免长时间、高温烫漂对产品硬脆度的破坏而抵消复合液中钙离子的保脆效应。