John Deere公司9R系列新型轮式拖拉机

介绍了John Deere公司的9R系列新拖拉机主要部件的技术性能和结构特点,为我国拖拉机行业科研单位和生产企业进一步研究开发拖拉机新产品提供参考。

大陆赢得John Deere原配轮胎合同

美国《现代轮胎经销商》(www.moderntiredealer.com)2019年7月10日报道:John Deere公司4个型号的中型拖拉机选择大陆Tractor70和Tractor85子午线轮胎为原配轮胎(见图1)。

John Deere林业公司2007年在欧洲和俄罗斯的业务概要

美国：2007年，JohnDeere林业公司的收入有了进一步较大的增长。2007年的收入比去年增长了13％，而且自2001年以来其年平均增长率为16％。与去年相比，JohnDeere在欧洲和俄罗斯的新产品、二手产品和零部件的销售量均呈增长趋势，反映了人们对JohnDeere公司产品的强烈需求。与此相反，在北美，人们对林业设备的总需求量呈下降趋势。与去年相比，2007年JohnDeere公司的总营业利润和纯收入均有所增长，主要原因是销售量的增加，弥补了较高原材料价格、销售价格和其它生产上的花费。JohnDeere林业公司2007年的总营业利润（或称税前收入）为总收入的6％，比去年的4％有所增加。

JohnDeere公司的7030系列拖拉机

JohnDeere公司于2007年初推出7030系列新拖拉机,用以替代该公司于2003年推出的7020系列拖拉机。共有3种机型（7730型、7830型和7930型）,按照97/68EC标准测定,其额定功率为140～162kW,最大功率为152～179kW,发动机装用SurpuissanceActive型功率增加机构后。

Timbermash-Baikal成为John Deere的林业设备在西伯利亚（Siberia）的新经销商

John Deere公司与西伯利亚的Timbermash—Baikal签署了新的经销合同，新的经销商Timbermash—Baikal要负责西伯利亚地区John Deere生产的新旧设备的销售、使用培训和销后服务工作。Timbermash—Baikal位于伊尔库茨克（Irkutsk），但是它的销售和服务业务却包括布拉茨克（Bratsk）和克拉斯诺亚尔斯克（Krasnojarsk）地区。John Deere公司的总经理HannuHietikko说：“西伯利亚是俄国林业发展很快的地方，而中国也需要很多木质原材料，西伯利亚有2亿m^3的木材可砍伐，但目前只有4000万m^3被开发利用了，而且其中90％都需要将整棵树砍倒，John Deere公司拥有伐木及加工原木的设备，

“JOHN DEERE”商标授权使用公告

经迪尔公司总部授权批准,约翰·迪尔佳联收获机械有限公司制造的全部联合收割机产品从公历2007年1月1日开始,使用“JOHN DEERE”(约翰迪尔)商标,不再使用“约翰·迪尔佳联”商标。

Visible Losses to the Mechanical Harvesting of Ratoon Sugarcane Using the Harvester John Deere 3520

The aim of this study was to evaluate the visible loss of sugar cane and the damage to the knuckles, using the John Deere 3520 harvester on three different travel speeds (3.0;4.0 and 5.0 km·h-1), in DIC with five repetitions in Campos dos Goytacazes, Rio de Janeiro/Brazil. Each treatment was composed by six lines of harvested cane stumps, with a length of 290 m each. In these six lines, the remains of sugar cane left in the field were collected by placing the sampling frame in two central lines every 50 m, and separating 40 m of edge. The sampling area was surrounded by 2 m wide and 10 m long, totaling 20 m2. To calculate the damage to stumps, a visual methodology by [1], was used, which classifies the damage grade, ranging from 1 to 4. Fifty stumps were assessed randomly for each speed, in a sampling area of 1800 m2. The data were submitted to ANOVA and Tukey test at 5%, in order to compare the effect of different speeds on the losses and damages. There was no significant difference regarding the loss or damage by comparing the different speeds. Therefore, it is more advantageous to use the speed of 5.0 km·h-1, harvesting more in less time and causing the same level of damage.

“JOHN DEERE”商标授权使用公告

经迪尔公司总部授权批准,约翰·迪尔佳联收获机械有限公司制造的全部联合收割机产品从公历2007年1月1日开始,使用“JOHNDEERE”(约翰迪尔)商标,不再使用“约翰·迪尔佳联”商标。约翰迪尔(中国)投资有限公司2007年1月11日背景介绍:约翰·迪尔佳联收获机械有限公司是美国迪尔公司的全资子公司,隶属于约翰迪尔(中国)投资有限公司,是迪尔公司在中国的联合收割机制造基地。1997年,迪尔公司与中国佳木斯联合收割机厂合资建立了约翰·迪尔佳联收获机械有限公司。2004年,约翰·迪尔佳联收获机械有限公司成为外商独资企业。

自由节点差分法寻点策略研究及验证

混合网格具有良好的贴体性,适用于Navier-Stokes方程的计算,但在网格交界面处需要通过插值进行流场信息交换,而这一过程会引入误差。陈洁等提出了一种适用于无序网格点的自由节点差分计算方法,该方法可对重叠网格交界面流场进行差分计算,无须采用插值方法进行流场信息传递,解决了插值方法引入误差的问题。但该自由节点差分法的计算模板需要从中心点周围的点云中选择网格点构成,不同选点策略对计算结果的影响不同。针对自由节点差分法的选点需求,本文综合考虑角度、正交性、距离等因素,提出了几种不同选点策略,并利用数值实验进行了验证。结果表明,本文提出的选点策略符合自由节点差分法的构造思想,均能获得稳定的收敛解,其中模板点与中心点距离对计算精度影响最大,是选点策略的首要影响因素。

Impact on Soil Organic C and Total Soil N from Cool- and Warm-Season Legumes Used in a Green Manure-Forage Cropping System

Annual forage legumes are important components of livestock production systems in East Texas and the southeastern US. Forage legumes contribute nitrogen (N) to cropping systems through biological N fixation, and their seasonal biomass production can be managed to complement forage grasses. Our research objectives were to evaluate both warm- and cool-season annual forage legumes as green manure for biomass, N content, ability to enhance soil organic carbon (SOC) and soil N, and impact on post season forage grass crops. Nine warm-season forage legumes (WSL) were spring planted and incorporated as green manure in the fall. Forage rye (Secale cereale L.) was planted following the incorporation of WSL treatments. Eight cool-season forage legumes (CSL) were fall planted in previously fallow plots and incorporated as green manure in late spring. Sorghum-sudangrass (Sorghum bicolor x Sorghum bicolor var. sudanense) was planted over all treatments in early summer after forage rye harvest and incorporation of CSL treatments. Sorghum-sudangrass was harvested in June, August and September, and treatments were evaluated for dry matter and N concentration. Soil cores were taken from each plot, split into depths of 0 to 15, 15 to 30 and 30 to 60 cm, and soil C and N were measured using combustion analysis. Nylon mesh bags containing plant samples were buried at 15 cm and used to evaluate decomposition rate of above ground legume biomass, including change in C and N concentrations. Mungbean (Vigna radiata L. [Wilczek]) had the highest shoot biomass yield (6.24 t DM ha-1) and contributed the most total N (167 kg∙ha-1) and total C (3043 kg∙ha-1) of the WSL tested. Decomposition rate of WSL biomass was rapid in the first 10 weeks and very slow afterward. Winter pea (Pisum sativum L. spp. sativum), arrow leaf clover (Trifolium vesiculosum Savi.), and crimson clover (Trifolium incarnatum L.) were the most productive CSL in this trial. Austrian winter pea produced 8.41 t DM ha-1 with a total N yield of 319 kg N ha-1 and total C production of 3835 kg C ha-1. The WSL treatments had only small effects on rye forage yield and N concentration, possibly due to mineralization of N from a large SOC pool already in place. The CSL treatments also had only minimal effects on sorghum-sudangrass forage production. Winter pea, arrow leaf and crimson clover were productive cool season legumes and could be useful as green manure crops. Mungbean and cowpea (Vigna unguiculata [L.] Walp.) were highly productive warm season legumes but may include more production risk in green manure systems due to soil moisture competition.

Arabic Sign Language Gesture Classification Using Deer Hunting Optimization with Machine Learning Model

Sign language includes the motion of the arms and hands to communicate with people with hearing disabilities.Several models have been available in the literature for sign language detection and classification for enhanced outcomes.But the latest advancements in computer vision enable us to perform signs/gesture recognition using deep neural networks.This paper introduces an Arabic Sign Language Gesture Classification using Deer Hunting Optimization with Machine Learning(ASLGC-DHOML)model.The presented ASLGC-DHOML technique mainly concentrates on recognising and classifying sign language gestures.The presented ASLGC-DHOML model primarily pre-processes the input gesture images and generates feature vectors using the densely connected network(DenseNet169)model.For gesture recognition and classification,a multilayer perceptron(MLP)classifier is exploited to recognize and classify the existence of sign language gestures.Lastly,the DHO algorithm is utilized for parameter optimization of the MLP model.The experimental results of the ASLGC-DHOML model are tested and the outcomes are inspected under distinct aspects.The comparison analysis highlighted that the ASLGC-DHOML method has resulted in enhanced gesture classification results than other techniques with maximum accuracy of 92.88%.

Deer Hunting Optimization with Deep Learning Enabled Emotion Classification on English Twitter Data

Currently,individuals use online social media,namely Facebook or Twitter,for sharing their thoughts and emotions.Detection of emotions on social networking sites’finds useful in several applications in social welfare,commerce,public health,and so on.Emotion is expressed in several means,like facial and speech expressions,gestures,and written text.Emotion recognition in a text document is a content-based classification problem that includes notions from deep learning(DL)and natural language processing(NLP)domains.This article proposes a Deer HuntingOptimizationwithDeep Belief Network Enabled Emotion Classification(DHODBN-EC)on English Twitter Data in this study.The presented DHODBN-EC model aims to examine the existence of distinct emotion classes in tweets.At the introductory level,the DHODBN-EC technique pre-processes the tweets at different levels.Besides,the word2vec feature extraction process is applied to generate the word embedding process.For emotion classification,the DHODBN-EC model utilizes the DBN model,which helps to determine distinct emotion class labels.Lastly,the DHO algorithm is leveraged for optimal hyperparameter adjustment of the DBN technique.An extensive range of experimental analyses can be executed to demonstrate the enhanced performance of the DHODBN-EC approach.A comprehensive comparison study exhibited the improvements of the DHODBN-EC model over other approaches with increased accuracy of 96.67%.

Automated Red Deer Algorithm with Deep Learning Enabled Hyperspectral Image Classification

Hyperspectral(HS)image classification is a hot research area due to challenging issues such as existence of high dimensionality,restricted training data,etc.Precise recognition of features from the HS images is important for effective classification outcomes.Additionally,the recent advancements of deep learning(DL)models make it possible in several application areas.In addition,the performance of the DL models is mainly based on the hyperparameter setting which can be resolved by the design of metaheuristics.In this view,this article develops an automated red deer algorithm with deep learning enabled hyperspec-tral image(HSI)classification(RDADL-HIC)technique.The proposed RDADL-HIC technique aims to effectively determine the HSI images.In addition,the RDADL-HIC technique comprises a NASNetLarge model with Adagrad optimi-zer.Moreover,RDA with gated recurrent unit(GRU)approach is used for the identification and classification of HSIs.The design of Adagrad optimizer with RDA helps to optimally tune the hyperparameters of the NASNetLarge and GRU models respectively.The experimental results stated the supremacy of the RDADL-HIC model and the results are inspected interms of different measures.The comparison study of the RDADL-HIC model demonstrated the enhanced per-formance over its recent state of art approaches.

Intelligent Machine Learning with Metaheuristics Based Sentiment Analysis and Classification

Sentiment Analysis(SA)is one of the subfields in Natural Language Processing(NLP)which focuses on identification and extraction of opinions that exist in the text provided across reviews,social media,blogs,news,and so on.SA has the ability to handle the drastically-increasing unstructured text by transform-ing them into structured data with the help of NLP and open source tools.The current research work designs a novel Modified Red Deer Algorithm(MRDA)Extreme Learning Machine Sparse Autoencoder(ELMSAE)model for SA and classification.The proposed MRDA-ELMSAE technique initially performs pre-processing to transform the data into a compatible format.Moreover,TF-IDF vec-torizer is employed in the extraction of features while ELMSAE model is applied in the classification of sentiments.Furthermore,optimal parameter tuning is done for ELMSAE model using MRDA technique.A wide range of simulation analyses was carried out and results from comparative analysis establish the enhanced effi-ciency of MRDA-ELMSAE technique against other recent techniques.

Regional Copper Deficiency in White-Tailed Deer

Minerals are critical in maintaining health and physiological function in wildlife. Geographic variation in soil and forage mineral concentration may predispose wildlife to mineral imbalances, where a common symptom is restricted somatic growth. We investigated if mineral imbalances could explain localized differences in morphology of white-tailed deer (Odocoileus virginianus) occurring in geographically proximate sites with similar management, climate, and habitat. We collected serum samples and morphological measurements from free-ranging white-tailed deer captured during 2011-2019 from coastal and inland rangeland sites in South Texas, USA. We measured mineral concentrations in serum from captured deer at each location. Asymptotic deer body mass and antler size averaged 8% - 20% smaller for deer at the coastal compared to the inland site. The proportion of deer with deficient levels of serum copper was greater at the coastal site (66% versus 14%). Our results suggest regional mineral deficiencies in deer may limit antler and body development. Wildlife managers should be aware of all aspects of wildlife nutrition and the importance of considering nutrients beyond energy and protein.

国外部分公司的拖拉机用弹性悬架前桥结构简介

近年来,国外一些主要拖拉机公司生产的拖拉机产品,采用弹性悬架前桥的越来越多.装用弹性悬架前桥的好处是极大地提高了驾驶操纵的舒适性和在公路上进行运输作业时的安全性.另外,采用这种新结构也可改进拖拉机在田间的牵引性能.国外各主要拖拉机公司均研制有自己独特的弹性悬架前桥结构,下面将有关公司的拖拉机系列产品所采用的弹性悬架前桥结构特点作一简单介绍.

Mitochondrial DNA Sequences Imply Anhui Musk Deer a Valid Species in Genus Moschus

Anhui musk deer [ Moschus ( moschiferus/berezovskii ) anhuiensis ] has been a taxonomic mystery since its discovery in early 80's.In this paper,with museum samples,we sequenced the complete cytochrome b gene of five Anhui musk deer.When compared with other species in Genus Moschus ,Anhui musk deer showed a rather level of sequence divergence from all the other species in this genus.The phylogenetic trees constructed by multiple methods supported the same topology,in which the monophyly of Anhui musk deer was clearly demonstrated.Therefore,our molecular data suggest a full species status for Anhui musk deer ( Moschus anhuiensis ),rather than a subspecies of either M moschiferus or M berezovskii previously suggested by morphological studies.

Identification of sika deer and red deer using partial cytochrome b and 12s ribosomal RNA genes

A study was conducted on the identifications of the degraded samples of sika deer （Cervus nippon） and red deer （Cervus elaphus） by phylogenetic and nucleotide distance analysis of partial Cytb and 12s rRNA genes sequences. 402 bp Cytb genes were achieved by PCR-sequencing using DNA extracted from 8 case samples, and contrasted with 27 sequences of Cytb gene downloaded from GenBank database. The values of three nucleotide distance between three suspected samples and sika deer were identical （0.026±0.006）, which was smaller than the smallest nucleotide distance between eastern red deer and sika deer （0.036）. Furthermore, phylogenetic analysis of sika deer and red deer indicated that the evidences located within the same cluster as sika deer. The evidences were sika deer materials. As the same way, other three suspected samples were derived from red deer. The results were further confirmed by phylogenetic and nucleotide distance analysis of 387 bp 12s rRNA gene. The method was powerful and less time-consuming and helpful to reduce the related cases with wildlife.

Plasmid DNA Analysis of Pathogenic Escherichia coli in Musk Deer

[Objective] The pathogenic Escherichia coli in musk deer was classified at molecular level to provide basic materials for molecular epidemiology of pathogenic Escherichia coli in musk deer. [Method] Plasmids from 24 pathogenic Escherichia coli in musk deer were extracted by the Lysis Triton method, and then identified by single enzyme digestion with three endonucleases of Hind Ⅲ, EcoR Ⅰ and BamH Ⅰ. [Result] The yield rate of plasmids was 91.6%, and 24 pathogenic Escherichia coli in musk deer had the identical or similar plasmid profiles. [Conclusion] Plasmid DNA analysis offers scientific basis for molecular epidemiology of pathogenic Escherichia coli in musk deer in Sichuan Institute of Musk Deer Breeding.

Status of microsatellites as genetic markers in cervids

Microsatellite loci distributing on genome randomly act as effective genetic markers. To date, about 200 microsatellite loci were found in cervids b y transferring microsatellite PCR primers derived in bovine, ovine to cervids, a s well as a few loci derived directly from deer microsatellite library. These lo ci have been used in parentage determination, genetic diversity and population s tructure, population introgression, as genetic marker gestation length and winte ring survival et al. However, microsatellite loci presently found are untouchabl e to the demand of application. Future work should include: 1) isolating a large number of cervine microsatellite loci, 2) constructing genetic and physical map s of microsatellite loci. So that microsatelites have a strong base for advanced applications in deer.