Why high grain yield can be achieved in single seedling machine-transplanted hybrid rice under dense planting conditions?

This study was conducted to identify the factors associated with high grain yield in single seedling machine-transplanted hybrid rice under dense planting conditions. Field experiments were done in Yong＇an Town, Hunan Province, China in 2015 and 2016. Two hybrid rice cultivars were grown under single seedling machine transplanting （SMT） and conventional machine transplanting （CMT） at a high planting density in each year. Grain yield and yield attributes were compared between SMT and CMT. Averaged across cultivars and years, grain yield was 12％ higher under SMT than under CMT. Plant height, basal stem width, and shoot and root dry weights were higher in seedlings for SMT than those for CMT. SMT had less maximum tiller number per m2 and consequently less panicle number per m2 than did CMT. Branch number per panicle, especially the secondary branch number per panicle, and spikelet number per cm of panicle length were more under SMT than under CMT, which resulted in more spikelet number per panicle under SMT than under CMT. SMT had higher or equal spikelet filling percentage than did CMT. The difference in grain weight between SMT and CMT was relatively small and inconsistent cross years. SMT had higher or equal total biomass and harvest index than did CMT. Dry weight per stem under SMT was heavier than that under CMT. Larger leaf area per stem was partly responsible for the heavier dry weight per stem under SMT than under CMT. Our study suggests that improvement in seedling quality, panicle size, and dry weight per stem are critical to the high grain yield in single seedling machine-transplanted hybrid rice under dense planting conditions.

A Study of the Factors that Affect Safe Full Heading of Machine-transplanted Rice Seedlings in the Temperate and Cool Rice-growing Areas

This paper studies the factors that affect the safe full heading of machine-transplanted rice seedlings in the temperate and cool ricegrowing areas,and explores the influence of machine-transplanted rice seedling varieties,seedling age,nitrogen fertilizer application rate and management on the safe full heading of machine-transplanted rice seedlings. Results show that for the mechanized production in the temperate and cool rice-growing areas,we should select the mid-early maturity cold-resistant varieties with growth period of not exceeding 180 d,control the seedling age to be 30- 35 d and total amount of pure nitrogen to be not more than 300 kg / ha,and moderately reduce the nitrogen fertilizer postponing ratio. Under this condition,we can achieve safe full heading of machine-transplanted rice seedlings and ensure the yield.

Effects of Seedling Cutivation with Mat-fiber Mulch on Quality and Quantity of Early-season Rice

[Objective] The aim was to explore effects of tray mat of fiber mulch on quality and yield of early rice-season rice transplanted by machine. [Method] Seedling quality, the rate of leaked rice, density of mechanical transplanting rice, mature rate and yield covered with fiber mulch were compared with groups not covered with mulch. Furthermore, different indices of cultivated rice with and without fiber mulch were analyzed and compared. [Result] The rice yield in the group with fiber mulch improved by 11.9% and rice quality enhanced as wel . What＇s more, rice plants were much easier to be col ected, and the rate of leaked rice lowered by machine. [Conclusion] The research provides theoretical references for seedling transplanting and cultivation of early-season rice by machine with tray mats.

Research on A Master - slave Multi - microcomputers Control System for Hollow Spindle Fancy Yarn Spinning Machine

In this paper, a successfully studied and developed master - slave muld - microcomputers control system based on PC - BUS for hollow spindle fancy yarn spinning machine, mainly Its overall scheme, software and hardware construction, is introduced. Spinning experiments show that the system achieves satisfactory result. This system can solve the diftkultles of mechatronical fusion between domestic hollow splndk fancy yarn spuming muchine and its microcomputer control technology.

DK7732-1 Electric Spark CNC Wire-Cuffing Machine

The machine tool is one of the new products developed and produced by the Shanghai No.8 Machine Tool Plant. It adopts a lift adjustable wiretrame and molybdenum filament tensioning mechanism with large cutting thickness and high machining precision. It is equipped with an advanced IBM-PC 386 microcomputer-controlled system, with strong performance and CRT display. Man/

Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis

Computational intelligence is one of the most powerful data processing tools to solve complex nonlinear problems, and thus plays a significant role in intelligent fault diagnosis and prediction. However, only few com- prehensive reviews have summarized the ongoing efforts of computational intelligence in machinery condition moni- toring and fault diagnosis. The recent research and devel- opment of computational intelligence techniques in fault diagnosis, prediction and optimal sensor placement are reviewed. The advantages and limitations of computational intelligence techniques in practical applications are dis- cussed. The characteristics of different algorithms are compared, and application situations of these methods are summarized. Computational intelligence methods need to be further studied in deep understanding algorithm mech- anism, improving algorithm efficiency and enhancing engineering application. This review may be considered as a useful guidance for researchers in selecting a suit- able method for a specific situation and pointing out potential research directions.

Plasma microRNA-15a/16-1-based machine learning for early detection of hepatitis B virus-related hepatocellular carcinoma

Background and aims:Hepatocellular carcinoma(HCC),which is prevalent worldwide and has a high mortality rate,needs to be effectively diagnosed.We aimed to evaluate the significance of plasma microRNA-15a/16-1(miR-15a/16)as a biomarker of hepatitis B virus-related HCC(HBV-HCC)using the machine learning model.This study was the first large-scale investigation of these two miRNAs in HCC plasma samples.Methods:Using quantitative polymerase chain reaction,we measured the plasma miR-15a/16 levels in a total of 766 participants,including 74 healthy controls,335 with chronic hepatitis B(CHB),47 with compensated liver cirrhosis,and 310 with HBV-HCC.The diagnostic performance of miR-15a/16 was examined using a machine learning model and compared with that of alpha-fetoprotein(AFP).Lastly,to validate the diagnostic efficiency of miR-15a/16,we performed pseudotemporal sorting of the samples to simulate progression from CHB to HCC.Results:Plasma miR-15a/16 was significantly decreased in HCC than in all control groups(P<0.05 for all).In the training cohort,the area under the receiver operating characteristic curve(AUC),sensitivity,and average precision(AP)for the detection of HCC were higher for miR-15a(AUC=0.80,67.3%,AP=0.80)and miR-16(AUC=0.83,79.0%,AP=0.83)than for AFP(AUC=0.74,61.7%,AP=0.72).Combining miR-15a/16 with AFP increased the AUC to 0.86(sensitivity 85.9%)and the AP to 0.85 and was significantly superior to the other markers in this study(P<0.05 for all),as further demonstrated by the detection error tradeoff curves.Moreover,miR-15a/16 impressively showed potent diagnostic power in early-stage,small-tumor,and AFP-negative HCC.A validation cohort confirmed these results.Lastly,the simulated follow-up of patients further validated the diagnostic efficiency of miR-15a/16.Conclusions:We developed and validated a plasma miR-15a/16-based machine learning model,which exhibited better diagnostic performance for the early diagnosis of HCC compared to that of AFP.

Verifying the accuracy of interlocking tables for railway signalling systems using abstract state machines

Railway transportation system is a critical sector where design methods and techniques are defined by international standards in order to reduce possible risks to an acceptable minimum level. CENELEC 50128 strongly recommends the utilization of finite state machines during system modelling stage and formal proof methods during the verifi- cation and testing stages of control algorithms. Due to the high importance of interlocking table at the design state of a sig- nalization system, the modelling and verification of inter- locking tables are examined in this work. For this purpose, abstract state machines are used as a modelling tool. The developed models have been performed in a generalized structure such that the model control can be done automatically for the interlocking systems. In this study, NuSMV is used at the verification state. Also, the consistency of the developed models has been supervised through fault injection. The developed models and software components are applied on a real railway station operated by Metro Istanbul Co.

不同育苗方式对机插秧苗素质、栽插质量及水稻产量的影响

为探明常规育苗、托盘育苗和漂浮育苗3种方式对水稻育苗及大田生长的影响,以‘南粳9108’为供试材料,比较相同播量下3种方式所育秧苗素质差异及对栽插质量、大田生长和产量的影响。结果表明:3种育苗方式成苗率在71.7%-75.0%,其中漂浮育苗最高,三者的地上部性状无显著差异,但常规育苗根系数量及长度较托盘育苗和漂浮育苗分别增加21.4%、16.1%和3.3%、9.8%;漂浮育苗的空穴率和伤秧率分别为0.39%、0.78%,栽插质量最优;漂浮育苗分蘖高峰期分蘖数较托盘育苗和常规育苗分别增加9.8%和24.0%,但单株生物量积累有所降低;漂浮育秧最终成穗数较托盘育苗、常规育苗增加7.2%和8.1%,但每穗实粒数降低4.9%、4.6%,在最终产量上三者之间无显著差异。综合来看,3种育苗方式都可育出健壮秧苗,并且栽插质量、大田生长和产量表现良好,在生产上可根据实际情况进行选择。

基于DE-SVM的穴盘苗自动取苗机构故障诊断方法

为解决穴盘苗取苗机构早期机械故障识别困难的问题,提高故障诊断的准确率,提出一种基于DE-SVM的穴盘自动苗取苗机构故障诊断方法。首先,采用经验模态分解(Empirical Mode Decomposition,EMD)、变分模态分解(Variational Mode Decomposition,VMD)等预处理方法挖掘潜藏在取苗机构原始振动信号中的故障信息;其次,分别从原始振动信号和预处理信号中提取时域统计特征,再运用距离评估(Distance Evaluation,DE)技术获得表征取苗机构故障的敏感时域统计特征,构建特征向量序列;最后,结合支持向量机(Support Vector Machine,SVM)分类算法对取苗机构运行状况进行识别。室内试验结果表明:此方法可有效区分取苗机构滑道故障、凸轮故障、弹簧故障和正常状况等4种工况,具有运算复杂度低、识别准确率高的优点,可为自动移栽取苗机构工况监测提供一种参考。

水稻硬质育秧盘全自动起盘机提升与叠盘装置研究

针对现有叠盘暗室育秧模式下全自动起盘机存在起盘合格率和工作稳定性下降,输送阶段易造成秧苗、秧盘损伤等问题,改进设计一种具有轴向辅助推送秧盘功能的钩杆式提升装置,并构建仿真试验平台确定影响其工作性能的主要参数及取值范围;确定关键部件循环叠盘装置的结构参数,建立多情形目标评价结果函数,并通过Matlab插值法对评价指标进行标准化;采用二次旋转正交组合试验,以托盘间距、横向输送速度、抬起角为试验因素,起盘合格率、叶损伤率、硬盘损伤率和伤秧数为性能评价指标,对试验结果进行响应曲面分析、回归分析。应用Design-Expert 11进行多目标参数组合优化。在托盘间距为190 mm、横向输送速度为0.20 m/s、抬起角为72°的条件下,田间验证试验得到起盘合格率为97.5%,叶损伤率为0.52%,硬盘损伤率0.45%,伤秧数为9,与理论优化值误差小于1%,比优化前合格率提升5.6个百分点,叶损伤率降低3.5个百分点,减少秧苗损伤,硬盘损伤率降低3.8个百分点。

轻简化栽培稻田杂草发生趋势与防控技术

随着水稻轻简化栽培技术的应用与推广,东北稻区、西北稻区、长江流域稻区和华南稻区等水稻主产区的杂草种群演替加快,稗草、千金子和马唐等恶性杂草频繁发生,杂草抗药性水平上升迅速。若杂草防控不及时、不彻底,极易对水稻生产构成严重威胁。为此,对水稻直播、机插和抛秧等轻简化栽培稻田杂草的草相特征、发展趋势和防除方法等进行了概述,以期为制定合理、高效的轻简化栽培稻田杂草综合防控技术、水稻用农药减量增效除草方案,延缓杂草抗药性产生与发展提供借鉴。

基于超分辨率重建与机器学习的油菜苗情监测方法

为优化养分管理和确保植株正常生长,以无人机遥感技术高效且非破坏采集田间作物苗情信息,监测油菜苗期的叶面积指数(LAI)与叶绿素相对含量(SPAD)。针对无人机因飞行高度与图像分辨率相互制约,监测效率与监测精度难以兼顾的问题,采用超分辨率重建方法,融合较低飞行高度拍摄高分辨率影像,重建较高飞行高度拍摄影像,建模完成后可通过拍摄飞行影像监测LAI和SPAD。试验设置3个氮肥梯度、3个播期、3个种植密度处理,在苗期利用无人机分别采集20m及40m 2个飞行高度的油菜苗影像,采用SRRestnet方法,对40m影像进行超分辨率重建。基于20m、40m及40m重建影像中提取的3种特征组合,利用偏最小二乘回归(PLSR)、随机森林(RF)、支持向量回归(SVR)3种机器学习方法对LAI和SPAD进行监测。结果表明,超分辨率重建后的图像在表型苗情监测中表现出良好效果,PLSR监测LAI、RF监测SPAD的监测精度最高,且40m重建图像的作业效率相比于20m图像提高48.6%。

Design and test of soft-pot-tray automatic embedding system for light-economical pot seedling nursery machine

Most of the commercially-available pot seedling nursery machines are incompatible with soft-pot-trays and are labor-intensive and low in productivity.A soft-pot-tray automatic embedding system was developed in this study to achieve automatic embedding of the soft pot tray into the hard tray following sowing and covering with soil.A control system was constructed using the Arduino program development environment.An embedded-hard-tray automatic lowering mechanism and conveyor-belt-based pot-tray embedding system were designed.Dynamics analysis was conducted to derive an equation to describe the embedding process of the soft pot tray into the embedded hard tray.A prototype of the soft-pot-tray automatic embedding system was manufactured and tested.The analytical equation suggested that a minimum linear velocity of 0.86 m/s was required for a complete embedding process.The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%.The successful tray embedding rate was 100%and the seed exposure rate was less than 1%with a linear velocity of the conveyor belt of 0.92 m/s.The experiment findings agreed well with the analytical results.The proposed soft-pot-tray automatic embedding system satisfied the technical specifications for a light-economical pot seedling nursery machine.

2ZGF-2型甘薯复式栽植机的设计与试验

为提高甘薯机栽水平,解决传统薯苗机械栽植中下田作业机具多、主要栽插方式短缺、易压垄伤垄、作业质量不高等难题,该文研制出一款与55.13＋80.85 k W大型拖拉机配套的2ZGF-2型甘薯裸苗复式栽植机,该机可一次完成两垄甘薯的旋耕、起垄、破压茬、开沟、栽插、镇压、修垄等作业。该机采用非零速栽插原理,链夹运动轨迹为余摆线,满足了甘薯种植中广泛应用的＂斜插法＂栽插方式作业需求,研究并确定开沟器开沟、链夹放苗与覆土压实三者间协调一致工作的重要结构参数,明确了栽插株距的主要影响因素和调整方法。该文对甘薯栽苗作业质量评价影响最重要的2个指标进行参数优化试验,得出优选参数组合为喂苗露出长度140 mm、开沟深度80 mm、前行速度0.3 m/s,此时立苗角度合格率为97.9%,栽插深度合格率为98.2%,较好的满足了甘薯机械栽插要求。该研究不仅为甘薯栽插市场提供了实用机具,也为甘薯栽插机械创新研发或优化提供了参考。

水稻机械育插秧技术研究进展

比较了我国水稻生产中不同水稻机插秧方式、机插播种育秧方式的优缺点,分析了传统杂交稻机插技术存在的问题,进而创新提出杂交稻精准播种机插技术,并展望了水稻绿色机插技术的发展。

嫁接机作业质量监测试验研究

嫁接作业质量监测是提高茄果类嫁接机作业成功率的重要技术手段。为此,采用机器视觉的方法对嫁接过程中番茄嫁接苗的倾斜角度、弯曲角度、有无接穗等信息进行检测,以此为基础来判断嫁接苗的作业质量,进而为嫁接机嫁接作业和生产质量管理提供信息。试验结果表明:针对嫁接苗倾斜角度、弯曲角度,机器视觉测量相对人工测量的最大角度误差不超过2.15°;针对试验所选180株嫁接苗判断合格与否,与人工判断对比,视觉判断成功率为92.2%,故提出的方法可以对番茄嫁接苗的特征信息进行有效识别。此检测方法还可以调整相关参数,用于其他贴接类嫁接苗的作业质量特征识别应用。

基于改进YOLOv3-Tiny的番茄苗分级检测

为了提高番茄苗分选移栽分级检测精度,该研究提出了YOLOv3-Tiny目标检测改进模型。首先建立了番茄穴盘苗数据集,使用K-means++算法重新生成数据集锚定框,提高网络收敛速度和特征提取能力;其次为目标检测模型添加SPP空间金字塔池化,将穴孔局部和整体特征融合,提高了对弱苗的召回率;同时加入路径聚合网络(PANet),提升细粒度检测能力;引入了SAM空间注意力机制,提高对番茄苗的关注,减少背景干扰;增加了ASFF(Adaptively Spatial Feature Fusion)自适应特征融合网络,能够使目标检测模型对多个级别的特征进行空间滤波;采用CIoU损失函数策略,提高模型收敛效果。改进的YOLOv3-Tiny目标检测模型经过数据集训练,在测试集上能够达到平均精度均值为97.64%,相比YOLOv3-Tiny模型提高了3.47个百分点。消融试验验证了网络结构改进和训练策略是有效的,并将改进的YOLOv3-Tiny目标检测算法与5种目标检测算法进行对比,发现改进的YOLOv3-Tiny目标检测模型在重合度阈值为50%的条件下平均精度均值为97.64%。单张图像处理时间为5.03ms,较其他目标检测算法具有明显的优势,验证了该模型能够满足番茄苗分级检测精度要求,可以为幼苗分选检测方法提供参考。

2BS-1200型水稻工厂化育秧播种机的研制

针对我国水稻育秧生产现状,在吸收国内外先进技术的基础上,研制了一种半机械化水稻育秧播种机,以满足广大农场、农村、连队等小面积水稻种植户对水稻育秧设备的需求。

水稻田间育秧水肥药变量喷灌装置设计与试验

为解决南方水稻工厂化田间育秧水肥药人工管理作业中存在的灌溉均匀性差、化肥和农药浪费以及劳动强度大等问题,该研究设计了一种水稻田间育秧水肥药变量喷灌装置,阐述了水肥药变量喷灌装置总体结构和工作原理,进行了关键部件设计与试验;以可编程逻辑控制器(programmable logic controller,PLC)为控制核心,构建了注肥量在线调控及整机变量喷灌控制系统。采用Box-Behnken试验设计方法,对装置喷灌均匀性与主要影响因素进行试验研究,应用单目标优化方法对喷灌关键参数进行优化,并通过验证试验,得到最优参数组合为:干管入口水压0.20 MPa、球阀开度90°、喷头喷角80°,此时装置的喷灌均匀性为92.69%;构建了氯化钾肥液质量浓度与电导率(electrical conductance,EC)值的线性模型,开展了装置变量灌溉施肥性能试验,3种喷灌等级下各作业区的肥液EC值分别为1.65、1.66和1.68 mS/cm,平均喷灌强度分别为900.85、1 092.04和1 263.67 mm/h,施肥均匀系数分别为85.21%、87.86%和91.62%。采用水肥药变量喷灌装置开展水稻育秧田间管理试验,华航51常规稻和广8优165杂交稻的秧苗长势均匀度均高于95%,成毯性良好,各项素质指标满足机插作业要求。所设计的水肥药变量喷灌装置能够满足水稻田间育秧水肥药变量喷灌作业要求,对提高水稻工厂化田间育秧机械化水平、保证秧苗质量具有实际应用价值。