棉铃虫 JNKs 基因的克隆及表达分析

c-Jun氨基末端激酶(c-Jun N-terminal kinase, JNK)是MAPK家族(mitogen-activated protein kinases, 丝裂原活化蛋白激酶)的重要成员, 具有参与昆虫抗逆反应等多种功能。为明确JNK在棉铃虫 Helicoverpa armigera 中的表达特性及其对Bt杀虫蛋白的应激与免疫反应, 本研究通过PCR克隆得到2个棉铃虫 JNK 基因 HaJNK1 和 HaJNK2; 生物信息学分析结果显示: HaJNK1和 HaJNK2基因开放阅读框分别为1 191、1 143 bp, 分别编码397、381个氨基酸。系统进化树分析结果表明棉铃虫 HaJNK1 与黏虫 Mythimna separata 聚为一支, 亲缘关系较近, HaJNK2与 家蚕 Bombyx mori 聚为一支, 同源性较高。利用实时荧光定量PCR技术分析 HaJNK1 与 HaJNK2 在棉铃虫不同发育时期、不同组织中的表达量, 发现 HaJNK1 与 HaJNK2 在卵中表达量最高, 其次是雌成虫; HaJNK1 在性腺中表达量最高, 其次是唾液腺; HaJNK2 在头部表达量最高, 其次是性腺。取食Cry1Ac的4龄棉铃虫幼虫的中肠组织中, HaJNK1 与 HaJNK2 的表达量均显著升高。推测 HaJNKs 基因可能参与棉铃虫抵御Bt杀虫蛋白伤害的应激和抗逆反应。     

Effects of Cocoa-Derived Polyphenols on Cognitive Function in Humans. Systematic Review and Analysis of Methodological Aspects

Plant Foods for Human Nutrition - The effects of cocoa-derived polyphenols on cognitive functions have been analyzed through numerous studies using different interventions (doses, vehicles, time...     

Profile and Content of Residual Alkaloids in Ten Ecotypes of Lupinus mutabilis Sweet after Aqueous Debittering Process

Plant Foods for Human Nutrition - The evaluation of the level of alkaloids in edible Lupinus species is crucial from a food safety point of view. Debittering of lupin seeds has a long history;...     

基于本体与认知经验的农业机器人视觉分类决策方法

基于小样本数据下认知经验知识辅助计算机进行决策,对实现农业领域机器人智能认知决策与助力智慧农业发展具有重要意义。本文在统计计数、支持向量机（SVM）等图像属性信息学习方法基础上,使用Protégé等工具,基于认知经验构建水果识别分类的专业知识库;然后根据图像颜色与形状信息,进行知识库搜索推理得到分类决策。实验在Fruit360数据集中共选择2091幅葡萄、香蕉、樱桃水果图像作为测试集,并各挑选30幅图像作为属性信息训练集与验证集,结果表明当前数据下葡萄与樱桃识别准确率为100%,香蕉识别准确率为93.30%。仅在知识库添加黄桃知识后,对984幅黄桃图像样本进行测试,其分类准确率为97.05%。表明本文方法能有效完成图像分类决策任务,且具有良好的过程可解释性、能力共享性和可拓展性。     

原子核电四极矩跃迁强度新经验公式

通过分析8≤ Z≤100偶偶原子核电四极矩跃迁强度 B（E2：0＋→2＋）与2＋态激发能 E（2＋）实验数据,提出了原子核电四极矩跃迁强度新经验公式 B（E2：0＋→2＋）＝33.65 Z2 A －0.71 E－1（2＋）．     

The coefficient of dominance is not (always) estimable with biallelic markers

The genetic relationship among individuals at one locus is characterized by nine coefficients of identity. The coefficients of inbreeding, coancestry and dominance (or fraternity) are just linear functions of them. Here, it is shown how they can be estimated using biallelic and triallelic markers using the method of moments, and comparisons are made with other methods based on molecular coancestry or molecular covariance. It is concluded that in the general case of dominance and inbreeding with biallelic markers, only the coefficients of inbreeding and coancestry can be estimated, but neither the single coefficients of identity nor the coefficient of dominance can be estimated. More than two alleles are required for a full estimation as illustrated with the triallelic situation.     

Dendrometric analysis of olive trees for wood biomass quantification in Mediterranean orchards

This work focuses on the development of dendrometric algorithms to calculate the volume and total biomass contained in olive trees. This laid the foundation for the use of this methodology as a tool to manage resources from orchards, establishing adequate prediction models for assessing other parameters such as income from raw materials from the cultivation, fruit production, CO₂ sinks, and waste materials (residual wood) used for energy or industry. Dendrometry has traditionally been applied to forest trees. However, little research has been conducted on fruit trees because of their heterogeneous structure. This issue was the first step of this research. For this, the form factors were calculated. This relates to the actual volume of the branch with a model volume, calculated as a revolution solid from the base diameter and length. The shape more approximated to 1 was the cylinder model with a mean value of 0.76 and standard deviation (SD) of 0.23. On the other hand, volume equations were obtained for the branches. The distribution of biomass in the tree was analyzed. It is estimated that 40 % of biomass is located in the stem and 60 % in the crown, and most of the crown biomass is concentrated in the first branches (60 %). Afterwards, occupation factors were calculated to relate the wood volume in the crown to its apparent volume, the mean being 0.005 dm³/m³ and SD 0.0025 dm³/m³. Also, equations for predicting the whole wood in the crown were obtained. In this regard, the best results were obtained when the crown diameter was used (R ² = 0.74). These results could be correlated with the production and quality of the fruit, amount of residual biomass coming from pruning, and LIDAR data, which may indicate a simple, quick, and accurate method for predicting biomass.