Pub Date : 1900-01-01DOI: 10.51202/9783181023617-377
V. Tsukor, S. Hinck, A. Ruckelshausen, W. Nietfeld, T. Mosler, H. Tesch, F. Lorenz, E. Najdenko, A. Moeller, D. Mentrup
With the mobile field laboratory soil2data soil sampling and soil nutrient analysis at the same time can be carried out directly on the field. Besides the advantages of a fast data availability of the soil nutrient contents and the omission of soil material transport to the laboratory, it forms a future basis for new application options, e.g. a verification of the current analysis results with existing results and if necessary repetition of the soil testing during the work on the field or a high sampling density. The developed process flow is fully automatic. The measurement results are immediately available and can be stored on external data platforms for analysis and further use. An innovative key component is the custom-specific ISFET multi sensor module. It measures values for the ions NO3, H2PO4 and K, the pH and electrical conductivity of the soil extraction solution. The ISFET multi sensor module is specially developed for soil nutrient analysis. The phosphorus measurement was further developed for the project "soil2data". The mobile field laboratory can be used with various vehicles. Introduction Small-scale knowledge and spatial distribution of the soil nutrient content in combination with further information (e.g. soil texture, yield level) is an important basis for site-specific crop production for demand-oriented fertilisation in plant production. An agricultural field is not a homogeneous unit. Within a field, geological or pedogenic differences are often noticeable (e.g. soil texture, soil type) [1] and the yield varies [e.g. 2]. It is often observable that the yield level also varies with the variations in soil conditions [e.g. 3]. For effective, site-specific crop production, this detailed information is of fundamental importance for the specific sub-field, such as yield, soil texture and/or soil nutrient status. Soil sampling is used to determine the nutrient status on arable land or on sub-fields. Among other things, the current soil nutrient status has an important influence on the yield [4, 5, 6]. In the case of site-specific fertilisation, the fertiliser application is adjusted to the site-specific yield and to the current soil nutrient status of that specific sub-field [e.g. 7]. The soil nutrient status can show significant variability within an agricultural field due to different nutrient uptake by plants and different soil textures [3]. Knowledge of the current, small-scale distribution of soil nutrients is an important information for economically and ecologically sustainable plant production [e.g. 4, 2]. A combined soil sampling and soil analysis on the field with a mobile field laboratory creates the conditions for a very fast delivery (< 1 day) of the soil nutrient status. The associated digitalisation of the process allows these analysis values to be automatically made available for other processes (e.g. fertiliser quantity calculation) and the data processing speed to be further increased. This makes it possible to d
利用移动式田间实验室土壤数据，可以直接在田间同时进行土壤取样和土壤养分分析。除了土壤养分含量的快速数据可用性和土壤材料运输到实验室的优点之外，它还为未来的新应用选择奠定了基础，例如，用现有结果验证当前分析结果，并在必要时在现场工作期间重复土壤测试或高采样密度。开发的工艺流程是全自动的。测量结果立即可用，并可存储在外部数据平台上进行分析和进一步使用。一个创新的关键组件是定制特定的ISFET多传感器模块。它测量了土壤萃取液的NO3、H2PO4和K离子、pH和电导率。ISFET多传感器模块是专门为土壤养分分析而开发的。“土壤数据”项目进一步发展了磷的测量。移动式野外实验室可与各种车辆配套使用。土壤养分含量的小规模知识和空间分布与进一步的信息(如土壤质地、产量水平)相结合，是植物生产中以需求为导向的施肥的特定地点作物生产的重要基础。农田不是一个同质的单位。在一块田地里，地质或成土的差异通常是显而易见的(例如土壤质地、土壤类型)[1]，产量也不同[例如2]。通常可以观察到，产量水平也随土壤条件的变化而变化[例3]。为了有效的、特定地点的作物生产，这些详细信息对特定的子田至关重要，如产量、土壤质地和/或土壤营养状况。土壤取样用于确定耕地或分田的养分状况。其中，当前土壤养分状况对产量有重要影响[4,5,6]。在特定地点施肥的情况下，肥料施用应根据特定地点的产量和该特定子田的当前土壤养分状况进行调整[例7]。由于植物对养分的吸收和土壤质地的不同，农田土壤养分状况会表现出显著的变异性[3]。了解当前土壤养分的小规模分布是经济和生态可持续植物生产的重要信息[例如4,2]。结合土壤采样和现场土壤分析，利用移动现场实验室，为土壤养分状况的快速交付(< 1天)创造了条件。该过程的相关数字化允许将这些分析值自动提供给其他过程(例如肥料数量计算)，并进一步提高数据处理速度。这使得在施肥之前直接进行土壤取样和分析成为可能，并根据当前的土壤养分状况优化施肥，以实现基于需求的施肥。土壤样品不再需要运输到实验室，这节省了运输成本和时间。没有更多的“处理成本”，剩余的土壤材料在实验室现场。进一步的其他选择，例如用以前测量的可用土壤养分分析值验证收集的分析结果，如果有必要，在出现无法解释的偏差时，可以立即重复测量。或者在几年或一个植被周期内编制时间序列是可以想象的。[8]“soil2data”跨学科研究项目正在开发一个移动现场实验室，用于即时进行土壤养分分析(见图1)。移动现场实验室的土壤取样、土壤样品制备和土壤样品分析等过程步骤经过修改、调整和自动化(见图2)。移动现场实验室soil2data将“土壤取样”、“土壤制备”和“土壤分析”的处理顺序结合起来。到目前为止，单个过程成为整个“土壤数据”过程的一部分。流程步骤并行操作。系统采用模块化设计。三种平台可用作运载车辆。整体的土壤数据过程可分为3个子过程:1。在实际的田间工作之前，规划土壤取样(例如，选择田地，生成取样线)。土壤取样、准备和分析直接在田间进行;数据管理和抽样后文件。[8]图1:“soil2data移动野外实验室”集成到野外机器人BoniRob(左图)和商用载体平台(右图) 2:移动现场实验室示意图及现场流程步骤子流程2包括“土壤采集”、“土壤制备”和ISFET多传感器模块。在此子流程中组合了以下组件:土壤取样器用于收集土壤样品材料，收集容器用于收集和制备混合样品，测量单元用于测定收集到的土壤体积，线性执行器用于物理制备和均质土壤样品，线性执行器带有搅拌器，用于输送萃取剂，各种泵和阀门带有供应线，用于输送土壤萃取剂，土壤萃取过滤站用于过滤土壤，带有输送系统的清洗系统用于清洗个体采用实时以太网总线控制各器件，并与ISFET多传感器模块的读出电路和载波平台进行通信。[9]为了使流动现场实验室的分析结果与通常的标准实验室分析结果达到高度的可比性和相关性，在土壤数据处理过程中，土壤样品制备的范围和质量是一个重要而基础的过程步骤。如果田间试验结果与标准试验的实验室结果高度相关，则LUFA推荐的肥料可用于评价土壤养分含量。土壤制备的系统方法和所使用的萃取剂对产生可比分析结果具有高度相关性。土壤准备可以用不同的萃取剂分两个阶段进行。对于基本设置，可以修改萃取剂与土壤的混合比例或物理制备时间。在“soil2data”研究项目中，项目合作伙伴LUFA Nord-West是德国下萨克森州农业商会认可的服务实验室，该实验室正在为移动现场实验室开发一种新的土壤制备方法[10]，以实现现场结果与实验室结果的高度可比性。所开发的soil2data制土方法如下(见图3):第一阶段:测定收集容器中土壤物质的质量后，加入第一萃取液(萃取剂1)，用搅拌器大力搅拌规定时间。然后将一定数量的土壤抽离并泵入过滤装置。第二阶段:在收集罐中剩余的土壤萃取物中加入第二种萃取液(萃取剂2)。收集槽中提取的土壤用搅拌器再次大力搅拌。然后，一定数量的土壤提取物再次被泵出并输送到过滤装置，土壤提取的任何残留物质都将留在现场。关键组件“ISFET多传感器模块”Microsens的ISFET多传感器模块(Lab on Chip)用于分析提取的土壤样品(见图4)。这个“Lab on Chip”由4个ISFET传感器和其他组件组成，用于测量提取的土壤样品的营养物质硝酸盐(NO3-)、钾(K+)和磷酸二氢(H2PO4-)以及pH值、温度和电导率。ISFET多传感器模块是专门为土壤养分分析而开发的，而磷的测量则是为soil2data项目进一步开发的。ISFET多传感器模块的控制和读出电子器件也得到了进一步的发展，现在可以使用ISFET多传感器模块进行稳定的测量。[9]图4“soil2data”多传感器模块带有4个ISFET芯片。结论完成了从采集土壤样品到制备土壤样品的不同工艺步骤(例如，将混合的土壤样品移交制备，用不同的提取剂提取养分，过滤过程等)和分析。新开发的两阶段土壤样品制备方法允许同时并行执行必要的工作步骤，以便整个过程序列可以在不停机模式下实现。“土壤数据”移动野外实验室可以直接在现场进行pH、K、NO3和h2po4的养分分析。该项目由联邦粮食和农业部(BMEL)根据联邦共和国议会通过联邦农业和食品办公室(BLE)在创新支持计划下的决定提供资金支持。参考文献[1]Hinck, S.(2009)。Ermittlung pflanzenbaulich relevant bodenkenenddaten mit Hilfe von ausgewählter(借助选定的土壤传感器确定与作物生产相关的土壤数据)。博士论文，马丁-路德大学哈勒维滕贝格。晚上好，安德雷出版社。[2]刘建军，刘建军，刘建军(2011)。 它有助于数据和信息技术吗?想爬上去吗?
{"title":"Automated mobile field laboratory for on-the-go soilnutrient analysis with the ISFET multi-sensor module","authors":"V. Tsukor, S. Hinck, A. Ruckelshausen, W. Nietfeld, T. Mosler, H. Tesch, F. Lorenz, E. Najdenko, A. Moeller, D. Mentrup","doi":"10.51202/9783181023617-377","DOIUrl":"https://doi.org/10.51202/9783181023617-377","url":null,"abstract":"With the mobile field laboratory soil2data soil sampling and soil nutrient analysis at the same time can be carried out directly on the field. Besides the advantages of a fast data availability of the soil nutrient contents and the omission of soil material transport to the laboratory, it forms a future basis for new application options, e.g. a verification of the current analysis results with existing results and if necessary repetition of the soil testing during the work on the field or a high sampling density. The developed process flow is fully automatic. The measurement results are immediately available and can be stored on external data platforms for analysis and further use. An innovative key component is the custom-specific ISFET multi sensor module. It measures values for the ions NO3, H2PO4 and K, the pH and electrical conductivity of the soil extraction solution. The ISFET multi sensor module is specially developed for soil nutrient analysis. The phosphorus measurement was further developed for the project \"soil2data\". The mobile field laboratory can be used with various vehicles. Introduction Small-scale knowledge and spatial distribution of the soil nutrient content in combination with further information (e.g. soil texture, yield level) is an important basis for site-specific crop production for demand-oriented fertilisation in plant production. An agricultural field is not a homogeneous unit. Within a field, geological or pedogenic differences are often noticeable (e.g. soil texture, soil type) [1] and the yield varies [e.g. 2]. It is often observable that the yield level also varies with the variations in soil conditions [e.g. 3]. For effective, site-specific crop production, this detailed information is of fundamental importance for the specific sub-field, such as yield, soil texture and/or soil nutrient status. Soil sampling is used to determine the nutrient status on arable land or on sub-fields. Among other things, the current soil nutrient status has an important influence on the yield [4, 5, 6]. In the case of site-specific fertilisation, the fertiliser application is adjusted to the site-specific yield and to the current soil nutrient status of that specific sub-field [e.g. 7]. The soil nutrient status can show significant variability within an agricultural field due to different nutrient uptake by plants and different soil textures [3]. Knowledge of the current, small-scale distribution of soil nutrients is an important information for economically and ecologically sustainable plant production [e.g. 4, 2]. A combined soil sampling and soil analysis on the field with a mobile field laboratory creates the conditions for a very fast delivery (< 1 day) of the soil nutrient status. The associated digitalisation of the process allows these analysis values to be automatically made available for other processes (e.g. fertiliser quantity calculation) and the data processing speed to be further increased. This makes it possible to d","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125123244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-9
X. Tian, A. Vacca, S. Fiorati, F. Pintore
{"title":"An Analysis of the Energy Consumption in the High-Pressure System of an Agricultural Tractor through Modeling and Experiment","authors":"X. Tian, A. Vacca, S. Fiorati, F. Pintore","doi":"10.51202/9783181023617-9","DOIUrl":"https://doi.org/10.51202/9783181023617-9","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129766074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-427
B. Oskarsson, E. Westergaard, T. Langer
{"title":"Optimization of tractor front loader for improved design freedom and increased operability","authors":"B. Oskarsson, E. Westergaard, T. Langer","doi":"10.51202/9783181023617-427","DOIUrl":"https://doi.org/10.51202/9783181023617-427","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"663 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114873474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-463
C. Weltzien, R. Shamshiri
{"title":"SunBot: Autonomous Nursing Assistant for Emission-Free Berry Production, General Concepts and Framework","authors":"C. Weltzien, R. Shamshiri","doi":"10.51202/9783181023617-463","DOIUrl":"https://doi.org/10.51202/9783181023617-463","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116052520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-i
{"title":"Titelei/Inhaltsverzeichnis","authors":"","doi":"10.51202/9783181023617-i","DOIUrl":"https://doi.org/10.51202/9783181023617-i","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133835235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-29
S. Liljenberg, M. Frederiksen, T. Langer
{"title":"Methods to evaluate steering performance of agricultural tractors","authors":"S. Liljenberg, M. Frederiksen, T. Langer","doi":"10.51202/9783181023617-29","DOIUrl":"https://doi.org/10.51202/9783181023617-29","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122430540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-479
D. Engelmann, Simon Becker, R. Stirnimann
Mobile machines are very versatile and different in their design and in the tasks they can handle. Tractors for example can be combined with different implements to work in agricultural processes. This variety must be considered during development, testing and inspection of exhaust gas aftertreatment systems. In this paper, one approach conducts In-Use measurements during field operation of a tractor with implement. While this takes environmental influences into account, In-Use measurements are barely reproducible, although tests on a chassis dynamometer are highly reproducible. Known road load simulation techniques for cars are not transferrable for mobile machines on chassis dynamometers due to different drivetrain topologies and changing parameters during field operation. To transfer field measurements to the roller test bench in the laboratory, a method is proposed to control the vehicle speed and motor torque to the same values recorded in the field.
{"title":"Transferring agricultural machines from field to the laboratory for emission check","authors":"D. Engelmann, Simon Becker, R. Stirnimann","doi":"10.51202/9783181023617-479","DOIUrl":"https://doi.org/10.51202/9783181023617-479","url":null,"abstract":"Mobile machines are very versatile and different in their design and in the tasks they can \u0000handle. Tractors for example can be combined with different implements to work in agricultural \u0000processes. This variety must be considered during development, testing and inspection of \u0000exhaust gas aftertreatment systems. In this paper, one approach conducts In-Use \u0000measurements during field operation of a tractor with implement. While this takes \u0000environmental influences into account, In-Use measurements are barely reproducible, \u0000although tests on a chassis dynamometer are highly reproducible. Known road load simulation \u0000techniques for cars are not transferrable for mobile machines on chassis dynamometers due \u0000to different drivetrain topologies and changing parameters during field operation. To transfer \u0000field measurements to the roller test bench in the laboratory, a method is proposed to control \u0000the vehicle speed and motor torque to the same values recorded in the field.","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130759677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-311
Michele Mattetti, Giovanni Molari, Fiorati Stefano, Lenzini Nicola
{"title":"Idling of agricultural tractors","authors":"Michele Mattetti, Giovanni Molari, Fiorati Stefano, Lenzini Nicola","doi":"10.51202/9783181023617-311","DOIUrl":"https://doi.org/10.51202/9783181023617-311","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128612003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-521
A. Stoll, M. Duttlinger, S. Klasen
{"title":"Investigation of the working precision and economic efficiency of automatically and manually guided hoes in grain","authors":"A. Stoll, M. Duttlinger, S. Klasen","doi":"10.51202/9783181023617-521","DOIUrl":"https://doi.org/10.51202/9783181023617-521","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115314011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.51202/9783181023617-327
M. Darr, M. Qasaimeh, C. Murphy, B. R. Covington, V. Fuchs, T. Schaefer, F. Pardina, B. Reddy, J. Petri, T. Fuege, J. Hinze
{"title":"High Definition Yield Maps for Precision Ag Decision Support","authors":"M. Darr, M. Qasaimeh, C. Murphy, B. R. Covington, V. Fuchs, T. Schaefer, F. Pardina, B. Reddy, J. Petri, T. Fuege, J. Hinze","doi":"10.51202/9783181023617-327","DOIUrl":"https://doi.org/10.51202/9783181023617-327","url":null,"abstract":"","PeriodicalId":106789,"journal":{"name":"LAND.TECHNIK AgEng 2019","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123058859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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