Hyperspectral Models for Estimating SPAD Value of Cotton Leaves under Waterlogging Stress

[Object] To setup the hyperspectral sensing models for estimating SPAD value of cotton leaves under waterlogging stress. [Method] Irrigation and drainage controllable plots were introduced to simulate the waterlogging stress treatment in the flowering and boll forming stage, during which the change characteristics of the cotton leaf spectral reflectance and SPAD value were observed after 1 d, 3 d, 6 d, 9 d waterlogging, respectively. To find out the hyperspectral sensing models for estimating SPAD value of cotton leaves under waterlogging stress, the correlation and regression relationships between SPAD value and spectrum parameters were analyzed. [Result] (1) The SPAD value of the fourth cotton leaf from the top was significantly lower than control when suffers from waterlogging for 3 d, when waterlogged 9 d the SPAD value decreased by around 15% compared with the control. (2) The cotton suffering from waterlogged damage in the flowering and boll forming stage caused the reflection peak in green light wave band became steep, while the near infrared spectral reflectance increased, and caused the reduction of red absorption and red edge position "blue shifts", the red edge position drifts towards short wave with 4～5 nm when suffers from waterlogging for 9 d. With increase of the waterlogged days, the red edge slope and red edge area increased with a maximum value at 6 d of waterlogging, meanwhile, the skewness and kurtosis of red edge increased. (3) After waterlogging, the SPAD value of the fourth cotton leaf from the top (chlorophyll content) had a remarkable correlation with red edge slope(Dr), red edge position(λr), green peak reflection(Rg), green peak position(λg), red well position(λo), blue edge area(SDb), yellow edge skewness(Sy), yellow edge kurtosis(Ky), red edge skewness(Sr), red edge kurtosis(Kr), etc. An experience linear, polynomial and exponential models for estimating SPAD value had been built through using the Sy, Sr, Kr as independent variables, respectively, their determination coefficient (R²) were greater than 0.9, and the root mean square error (RMSE) were less than 1; and an experience binary linear regression equation for estimating SPAD value had been built through multivariate regression using the λg, SDr/SDb(VI3), Sb, Sy, Ky as independent variables, the R² was as high as 0.973, and the RMSE was 0.393. [Conclusion] The model can be remote sensing model used as estimating leaf SPAD of cotton value under waterlogging stress.     

The organic acid profiles in the feces of pigs at Brachyspira hyodysenteriae- or B. pilosicoli-positive farms

We observed a significant difference in the organic acid profile of diarrheal feces between pigs infected with and free from pathogenic spirochetes. Diarrhea and loose feces were collected from growing pigs, held at 15 different commercial farms. A total of 106 samples were measured for organic acid concentration by HPLC and were checked for the presence of B. hyodysenteriae and B. pilosicoli by PCR. B. hyodysenteriae was detected in 3 samples collected from one farm. B. pilosicoli was detected in 5 samples collected from another farm. Lower concentrations of iso-butyrate and iso-valerate were likely associated with development of pathogenic spirochete infection.     

新疆春小麦育成品种耐热性评价

为筛选出耐热性好的小麦种质材料,通过开花期至成熟期人工模拟高温胁迫环境,以千粒重热感指数为主要评价指标,评价了新疆近30年来审定的春小麦品种的相对耐热性,并分析了高温胁迫对小麦籽粒蛋白质、湿面筋含量的影响。结果表明,与自然生长相比,高温胁迫条件下新疆春小麦育成品种的千粒重、籽粒宽度的变化均达到了极显著水平（P<0.01）,籽粒长度变化不显著(P>0.05),不同品种间耐热性存在很大差异。综合三年千粒重热感指数（HSI）分析,耐热性相对较好的品种有17个,连续三年HSI＜1的品种有11个,其中新春37号、新春2号、新春38号在高温胁迫条下千粒重变化较小,产量较稳定,为强耐热品种;对高温敏感品种有26个,连续三年HSI≥1的品种有13个,其中新春13号、新春18号、新春33号耐热性相对较弱。高温胁迫影响小麦籽粒的品质,其中13.95%的品种蛋白质含量降低,6.98%的品种湿面筋含量降低,其他品种高温胁迫后籽粒蛋白质、湿面筋含量均较自然生长有所提高。     

新疆春小麦育成品种遗传演变分析

【目的】研究新疆春小麦育成品种遗传演变规律,提高小麦资源的利用效率,为新疆春小麦品种选育和改良提供参考依据。【方法】以新疆春小麦育成品种为材料,对其主要性状进行综合评价分析,以春小麦90K芯片开展新疆春小麦育成种亲缘关系分析。【结果】新疆春小麦育成种遗传多样性丰富,平均遗传多样性指数2.005,变幅为1.902~2.181。相关性分析结果表明,蛋白质含量、湿面筋含量、穗粒数与育种年代呈极显著正相关。新疆春小麦品种选育主要是通过常规杂交育种、杂交辐射诱变育种、引种3种方式。利用小麦90K芯片将新疆春小麦育成种划分为3个类群,显示了各品种之间的亲缘关系。【结论】新疆春小麦育种遗传基础薄弱、遗传多样性逐渐散失,新疆小麦育种应加强资源收集与利用,扩大育种亲本选择,提高品种变异的丰度和广度,以多抗、高产稳产、优质高效的聚合育种,加快新品种选育进程,提高育种效率。     

基于深度学习的玉米拔节期冠层识别

为了满足田间玉米植株快速识别与检测的需求,针对玉米拔节期提出了基于深度学习的冠层识别方法,比较并选取了适于玉米植株精准识别和定位的网络模型,并研制了玉米植株快速识别和定位检测装置。首先拍摄玉米苗期和拔节期图像共计3 000张用于训练深度学习模型,针对拔节期玉米叶片交叉严重的问题,提出了以玉米株心取代玉米整株对象的标记策略。其次在Google Colab云平台训练SSDLite-MobileDet网络模型。为了实现田间快速检测,开发了基于树莓派4B+Coral USB的玉米冠层快速检测装置。结果表明,田间玉米冠层识别模型精度达到91%,检测视频的帧率达到89帧/s以上。研究成果可为田间玉米高精度诊断和精细化作业管理奠定基础。     

吉富品系尼罗罗非鱼（GIFT）摄食节律初探

用投喂添加色素的膨化颗粒饲料和观测排便相结合的方法,研究吉富品系尼罗罗非鱼(Genetic Improvement of Farmed Tilapias;GIFT)的摄食节律.结果发现,6个家系的吉富品系尼罗罗非鱼摄食具有明显的节律性,家系之间的摄食周期存在非常显著差异(P＜0.0001);t检验发现,各家系内摄食周期和排便周期的差异均不显著(P≥0.1097).回归分析发现,摄食周期对生长无显著的影响(P=0.8988),但与摄食量之间存在显著的线性关系(R2=0.9679,P=0.0004).对摄食节律聚类分析,6个家系可分为(1、2、6)、(3、4)、5共3个家系类别.该项研究能为GIFT的养殖投饵和进一步选育提供理论依据,为鱼类摄食节律研究提供方法上的参考.     

变压器负载试验方法改进研究与分析

工程实际中对于小型试验厂或容量有限的变电站而言,如果在额定电流条件下进行变压器负载试验,需要的电源容量较大,即使利用电容补偿弥补电源容量的不足,所需补偿电容器的体积和质量也会给试验实施带来困难。该文分析了变压器常规负载试验方法及其在工程实际中出现的问题,并有针对性的提出了一种改进的负载试验方法。首先通过计算机仿真验证改进方法的可行性,继而对其进行了现场实践,并对改进方法下的负载试验参数重新进行了计算,同时将改进方法与常规方法进行参数误差分析与成本对比分析。结果表明,该文提出的变压器负载试验改进方法可在不提高电源容量的情况下,大幅减少对中间设备如补偿电容器的限制,从而提高试验操作的效率及试验厂站的经济效益,又可满足工程实际精度要求,因此可以作为常规变压器负载试验的一种延伸和发展。     

贵州喀斯特地区棕色石灰土与黄壤有机质剖面分布及稳定碳同位素组成差异

贵州位于全球最大的喀斯特生态系统一中国西南喀斯特生态系统的中心，由于受到亚热带季风气候的冲击和人类不合理社会经济活动的破坏，其喀斯特生态系统已出现不同程度的石漠化，尤以乌江流域最为严重。现已认识到石漠化是一种与脆弱生态地质背景和人类活动相关联的土地退化过程，而土壤退化是土地退化的核心部分。在土壤侵蚀与退化及全球碳循环的过程中，作为土壤重要组成部分和代表一个主要碳库的土壤有机质在生态系统中扮演了一个十分重要的角色，开展对喀斯特地区不同土壤有机质剖面分布及稳定碳同位素组成的研究，将有利于提高对流域土壤侵蚀与退化过程中有机质的生物地球化学循环的认识。本研究选择乌江流域喀斯特地区二种主要土壤类型石灰土和黄壤，根据土壤有机质含量和稳定碳同位素组成，结合土壤pH值、粘粒含量等分析结果，探讨了喀斯特山区石灰土和黄壤有机质的剖面分布和稳定碳同位素组成差异，旨在为喀斯特生态系统土壤有机质的生物地球化学循环研究提供基础资料。     

具有解析式位置正解的2T1R并联机构运动性能分析

求解具有解析式位置正解且部分运动解耦的并联机构,有利于后续的误差分析、动力学分析、运动轨迹规划与控制等。基于方位特征方程(POC)的并联机构设计理论与方法,设计了两种具有解析式位置正解且部分运动解耦的2T1R并联机构,并对这两种机构进行了方位特征、自由度及耦合度等主要拓扑性能分析;提出基于拓扑特征的运动学建模与求解方法,并据此求解了两种机构的解析式位置正解;基于导出的位置反解,分析了两种机构工作空间、奇异位形、动平台的速度与加速度变化规律。最后比较了两种机构的运动性能,选择了优选机型。为优选机型的动力学分析与样机研制提供了理论基础。     

Establishment of Chinese soybean Glycine max core collections with agronomic traits and SSR markers

It is very important to efficiently study and use genetic diversity resources in crop breeding and sustainable agriculture. In this study, different sampling methods and sample sizes were compared in order to optimize the strategies for building a rationally sized core collection of Chinese soybean (Glycine max). The diversity in the core collection captured more than 70% of that in the pre-core collection, no matter what sampling methods were used, at a sampling proportion of 1%. Core collections established with both simple sequence repeat (SSR) marker data and agronomic traits were more representative than those chosen on an independent basis. An optimal sampling method for a soybean core collection was determined, in which strategy ‘S’ (allocating accessions to clusters according to the proportion of square root of the original sample size within each ecotype) was used based on SSR and agronomic data. Curve estimation was used to estimate the allelic richness of the entire Chinese soybean germplasm and a minimum sample size for a core collection, on which a sampling proportion of about 2% was determined to be optimal for a core collection. Further analysis on the core collection with fourteen agronomic traits and allelic constitution at 60 SSR loci suggested that it highly represented the entire collections both on genetic structure and diversity distribution. This core collection would provide an effective platform in proper exploitation of soybean germplasm resources for the study of complex traits and discovering important novel traits for crop genetic development.