采用双模态联合表征学习方法识别作物病害

基于深度卷积神经网络的视觉识别方法在病害诊断中表现出色,逐渐成为了研究热点。但是,基于深度卷积神经网络建立的视觉识别模型通常只利用了图像模态的数据,导致模型的识别准确率和鲁棒性,都依赖训练数据集的规模和标注的质量。构建开放环境下大规模的病害数据集并完成高质量的标注,通常需要付出巨大的经济和技术代价,限制了基于深度卷积神经网络的视觉识别方法在实际应用中的推广。该研究提出了一种基于图像与文本双模态联合表征学习的开放环境下作物病害识别模型(bimodalNet)。该模型在病害图像模态的基础上,进行了病害文本模态信息的嵌入,利用两种模态病害信息间的相关性和互补性,实现了病害特征的联合表征学习。最终bimodalNet在较小的数据集上取得了优于单纯的图像模态模型和文本模态模型的效果,最优模型组合在测试集的准确率、精确率、灵敏度、特异性和F1值分别为99.47%、98.51%、98.61%、99.68%和98.51%。该研究证明了利用病害图像和病害文本的双模态表征学习是解决开放环境下作物病害识别的有效方法。     

Longitudinal identification of Enterocytozoon bieneusi in dairy calves on a farm in Southern Xinjiang,China

Enterocytozoon bieneusi is the most common species responsible for human and animals microsporidiasis. A total of 250 samples were collected weekly from 25 newborn dairy calves of a farm in Southern Xinjiang, China at one to ten weeks of age. Enterocytozoon bieneusi was identified and genotyped by nested PCR amplification and sequencing of internal transcribed spacer (ITS) region.The cumulative prevalence of E. bieneusi infection was 100% (25/25), and the average infection was 52.0% (130/250). The highest infection rate was recorded at six weeks of age (92.0%, 23/25), and no infection was observed at one and two weeks of age. Sequencing analysis showed nine E. bieneusi genotypes (J, EbpC, PigEBITS5, CHV4, CHC3, CS-9, KIN-1, CH5, and CAM5) were identified. The highest genetic polymorphism was observed at ten weeks of age. Genotype J was the predominant E. bieneusi genotype. Phylogenetic analysis clustered genotype J into Group 2 and other eight genotypes (EbpC, PigEBITS5, CHV4, CHC3, CS-9, KIN-1, CH5, and CAM5), detected in 22 (16.9%, 22/130) samples, into Group 1. Among the genotypes, EbpC, KIN-1, and J have been identified in humans. The highest E. bieneusi infection rate (57.9%, 124/214) was observed in fecal samples with formed feces with no diarrhea (p < 0.01), and high genetic polymorphism was observed in class I fecal samples. The presence of zoonotic E. bieneusi genotypes in dairy calves suggests the possibility of transmitting zoonotic infections to humans. It provides the basic data on dynamic change of E. bieneusi in calves.     

Research of dissolved oxygen prediction in recirculating aquaculture systems based on deep belief network

Recirculating aquaculture has received more and more attention because of its high efficiency of treatment and recycling of aquaculture wastewater. The content of dissolved oxygen is an important indicator of control in recirculating aquaculture, its content and dynamic changes have great impact on the healthy growth of fish. However, changes of dissolved oxygen content are affected by many factors, and there is an obvious time lag between control regulation and effects of dissolved oxygen. To ensure the aquaculture production safety, it is necessary to predict the dissolved oxygen content in advance. The prediction model based on deep belief network has been proposed in this paper to realize the dissolved oxygen content prediction. A variational mode decomposition (VMD) data processing method has been adopted to evaluate the original data space, it takes the data which has been decomposed by the VMD as the input of deep belief network (DBN) to realize the prediction. The VMD method can effectively separate and denoise the raw data, highlight the relations among data features, and effectively improve the quality of the neural network input. The proposed model can quickly and accurately predict the dissolved oxygen content in time series, and the prediction performance meets the needs of actual production. When compared with bagging, AdaBoost, decision tree and convolutional neural network, the VMD-DBN model produces higher prediction accuracy and stability.     

农业用地土壤重金属样本点数据精化方法——以北京市顺义区为例

样本点空间分布是样点数据检测评价和挖掘分析的关键因素。以北京市顺义区为例，研发了一种农业用地土壤重金属样本点数据精化方法：首先构建样本点均匀变异指数和均匀因子离散图来共同检测样本点数据均匀性，进一步将样本点类型划分为均匀样本点、聚集样本点和稀疏样本点并确定其数量；其次删除聚集样本点，基于研究区历史数据加密稀疏样本点；最后基于地理空间样本点均匀变异指数、特征空间偏离指数和插值误差共同评价数据精化效果。结果表明，研究区样本点的均匀变异指数为0.429，存在一个聚集样本点和一个稀疏样本点，空间偏离指数为0.327，空间属性插值误差为6.538；冗余数据精化后进行均匀性检测没有发现聚集样本点和稀疏样本点，均匀变异指数下降到0.406，特征空间偏离指数微弱下降，空间属性插值误差下降到6.357。研究表明该方法可以对提高采样数据的均匀性和代表性提供理论指导，可以服务于土壤污染防治行动计划（土十条）、土壤污染状况详查等，为更加精确研究土壤空间信息变化提供一定的基础条件。     

支持转速现场标定的玉米精密排种器电驱控制系统研究

针对现有玉米精密电驱排种控制系统无法快速适应多类型排种器排种控制的问题,在玉米CAN总线电动排种的基础上,设计了一种对玉米排种器排种驱动进行现场标定的电驱控制系统。系统在排种驱动电动机控制信号与排种盘转速之间的对应关系中,采用分段线性插值的方法现场获取排种器驱动曲线,实现排种盘转速标定与控制。以国产气吸式玉米精密排种器和指夹式玉米精密排种器为试验对象,在模拟车速下,对系统排种盘转速现场标定的控制准确性进行试验。电驱气吸式排种器排种盘转速控制性能试验中,株距设定为25 cm,车速设定为3~12 km/h(间隔3 km/h),结果表明,系统调节时间最长为0.80 s,稳态误差最大为0.81 r/min,控制精度最低为97.42%。电驱指夹式排种器排种盘转速控制性能试验中,株距分别设定为20、25、32 cm,车速设定为4~9 km/h(间隔1 km/h),结果表明,总体排种盘转速平均调节时间为1.09 s,标准差为0.26 s;总体平均稳态误差为0.38 r/min,标准差为0.23 r/min;总体平均控制精度为98.30%,标准差为1.01%。与分段PID排种转速控制系统控制性能进行对比得出,支持转速现场标定的系统具有更好的适应性,平均调节时间减少0.51 s,平均稳态误差增大0.16 r/min,平均控制精度降低0.63个百分点。选用指夹式排种器,进行了播种均匀性田间试验,株距为20 cm,车速范围为4~7 km/h(间隔1 km/h),结果表明,播种合格指数大于等于84.26%,变异系数小于等于18.29%,说明系统能够完成对玉米精密排种器排种转速控制曲线的高控制精度现场标定,能够精准控制电驱排种转速。     

Evaluation of optical sensor measurements of canopy reflectance and of leaf flavonols and chlorophyll contents to assess crop nitrogen status of muskmelon

Nitrogen losses from intensive vegetal production systems are commonly associated with contamination of water bodies. Sustainable and optimal economic N management requires correct and timely on-farm assessment of crop N status to detect N deficiency or excess. Optical sensors are promising tools for the assessment of crop N status throughout a crop or at critical times. We evaluated optical sensor measurement of canopy reflectance and of leaf flavonols and chlorophyll contents to assess crop N status weekly throughout a muskmelon crop. The Crop Circle ACS 470 was used for reflectance measurement, the SPAD 502 for leaf chlorophyll, and the DUALEX 4 Scientific for leaf chlorophyll and flavonols. Four indices of canopy reflectance (NDVI, GNDVI, RVI, GVI), leaf flavonols and chlorophyll contents and the nitrogen balance index (NBI), the ratio of chlorophyll to flavonols contents, were linearly related to crop N content and to crop Nitrogen Nutrition Index (NNI) throughout most of the crop. NBI most accurately predicted crop N status; in five consecutive weekly measurements, R² values were 0.80–0.95. For NDVI during the same period, R² values were 0.76–0.87 in the first three measurements but R² values in the last two measurements were 0.39–0.45. Similar relationships were found with the three other reflectance indices. Generally, the relationships with NNI were equal to or slightly better than those with crop N content. These optical sensor measurements provided (i) estimation of crop N content in the range 1.5–4.5%, and (ii) an assessment of whether crop N content was sufficient or excessive for optimal crop growth for NNI ranges of 0.8–2.0. Composite equations that integrated the relationships between successive measurements with the optical sensors and crop N content or NNI for periods of ≥2 weeks (often 2–3 weeks) were derived for most indices/parameters. Overall, these results demonstrated the potential for the use of these optical sensor measurements for on-farm monitoring of crop N status in muskmelon.     

Application of digital photogrammetry to measure distribution of tree postions

The application of digital photogrammetry to measure distribution of tree positions with stereo image couple is introduced in detail, and the procedure of stereo vision applied in forestry environment is explored. Nonlinear error in measure model is adopted in the camera calibration; the interactive correlation matching is used under constraint of epipolar line and edge of tree detected by Canny operator. Results prove that application of digital photogrammetry technology to measure distribution of tree positions can meet demand of precision in experimental conditions.     

Identification of CIMMYT spring bread wheat germplasm maintaining superior grain yield and quality under heat-stress

Unpredictable temperatures and rainfall associated with climate change are expected to affect wheat (Triticum aestivum L.) production in various countries. The development of climate-resilient spring wheat cultivars able to maintain grain yield and quality is essential to food security and economic returns. We tested 54 CIMMYT spring bread wheat genotypes, developed and/or released over a span of 50 years, in the field for two years under optimum sowing dates, as well as using two delayed sowing dates to expose crops to medium and severe heat-stress conditions. The grain yield and yield components were severely affected as the heat-stress increased. Two contrasting groups of 10 lines each were identified to determine the effect of heat-stress on bread-making quality. The first set included entries that produced high yields in optimal conditions and maintained higher yields under heat-stress (superior-yielding lines), while the second set included genotypes that did not perform well in the environment with high temperature (inferior-yielding lines). We identified genotypes exhibiting bread-making quality stability, as well as the quality traits that had higher correlation with the loaf volume in the environment without stress and under heat-stress. Of all the quality traits tested, dough extensibility (AlvL) and grain protein content had a significant influence in heat-stress adaptation. Most of the lines from the superior-yielding group were also able to maintain and even improve quality characteristics under heat-stress and therefore, could be used as parents in breeding to develop high-yielding and stable quality wheat varieties.     

东北地区春玉米临界氮浓度稀释曲线的建立和验证

过量施氮是目前玉米栽培中存在的普遍现象,基于临界氮浓度稀释曲线计算得出的氮营养指数是诊断氮营养丰缺的重要手段。基于东北地区4个生态点的试验数据,构建了东北地区春玉米临界氮稀释曲线,并在此基础上建立了氮营养指数模型和需氮量模型,结果表明,东北地区春玉米地上部临界氮浓度与生物量符合幂函数关系。利用独立试验资料对建立的临界氮浓度稀释曲线进行检验,发现基于临界氮浓度稀释模型计算的氮营养指数可以准确诊断玉米植株的氮营养状况,并计算出实时的氮素需求量。该研究建立的东北地区春玉米临界氮稀释模型可以为该地区春玉米的氮营养诊断和动态调控提供较好的理论和技术指导。     

Nitrogen use efficiency of cotton (Gossypium hirsutum L.) as influenced by wheat–cotton cropping systems

Wheat–cotton rotations largely increase crop yield and improve resources use efficiency, such as the radiation use efficiency. However, little information is available on the nitrogen (N) utilization and requirement of cotton under wheat–cotton rotations. This study was to determine the N uptake and use efficiency by evaluating the cotton (Gossypium hirsutum L.) N use and the soil N balances, which will help to improve N resource management in wheat–cotton rotations. Field experiments were conducted during 2011/2012 and 2012/2013 growing seasons in the Yangtze River region in China. Two cotton cultivars (Siza 3, mid-late maturity with 130 days growth duration; CCRI 50, early maturity with 110 days growth duration) were planted under four cropping systems including monoculture cotton (MC), wheat/intercropped cotton (W/IC), wheat/transplanted cotton (W/TC) and wheat/direct-seeded cotton (W/DC). The N uptake and use efficiency of cotton were quantified under different cropping systems. The results showed that wheat–cotton rotations decreased the cotton N uptake through reducing the N accumulation rate and shortening the duration of fast N accumulation phase as compared to the monoculture cotton. Compared with MC, the N uptake of IC, TC and DC were decreased by 12.0%, 20.5% and 23.4% for Siza 3, respectively, and 7.3%, 10.7% and 17.6% for CCRI 50, respectively. Wheat–cotton rotations had a lower N harvest index as a consequence of the weaker sink capacity in the cotton plant caused by the delayed fruiting and boll formation. Wheat–cotton rotations used N inefficiently relative to the monoculture cotton, showing consistently lower level of the N agronomic use efficiency (NAE), N apparent recovery efficiency (NRE), N physiological efficiency (NPE) and N partial factor productivity (NPFP), particularly for DC. Relative to the mid–late maturity cultivar of Siza 3, the early maturity cultivar of CCRI 50 had higher N use efficiency in wheat–cotton rotations. An analysis of the crop N balance suggested that the high N excess in preceding wheat (Triticum aestivum L.) in wheat–cotton rotations led to significantly higher N surpluses than the monoculture cotton. The N management for the cotton in wheat–cotton rotations should be improved by means of reducing the base fertilizer input and increasing the bloom application.