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1.
Remedial Correction of Yield Map Data 总被引：1，自引：0，他引：1
Many yield maps exhibit systematic errors that attenuate the underlying yield variation. Two errors are dealt with in detail in this paper: those that occur when the harvester has a narrow finish to a land and those that occur when the harvester is filling up at the start of a harvest run. The authors propose methods to correct or remove erroneous data by the use of an expert filter, or alternatively use of an interpolation technique called potential mapping. 相似文献
2.
为深入了解测产方法、产量图重建和动力学模型的研究内容及关键技术,对测产方法、产量图重建、谷物流的动力学模型以及产量测量中的误差等研究成果进行梳理。重点概述了测产方法的分类,介绍了不同测产方法的原理、产量图重建涉及到的关键技术和动力学模型上取得的成果;对测产方法的试验结果和优缺点进行比较;分析了测产方法、产量图重建、水分传感器、切割宽度传感器和GPS定位装置等研究的误差来源。结果表明:1)对不同方式的测产装置进行合理的安装、校准和操作,就能使测产结果达到足够的精度,建议对不同的测产方式加强误差分析并提高试验准确度。2)产量图重建过程中的部分误差通过校准可以减小甚至消除,但基于小面积地块的产量图构建及误差研究还有待加强。3)一阶动力学模型无法确定谷物混合对产量监测的影响,建议在基于非线性组合算法和反褶积算法的动力学模型上加强研究。 相似文献
3.
Yield maps reflect systematic and random sources of yield variation as well as numerous errors caused by the harvest and mapping procedures used. A general framework for processing of multi-year yield map data was developed. Steps included (1) raw data screening, (2) standardization, (3) interpolation, (4) classification of multi-year yield maps, (5) post-classification spatial filtering to create spatially contiguous yield classes, and (6) statistical evaluation of classification results. The techniques developed allow more objective mapping of yield zones, which are an important data layer in algorithms for prescribing variable rates of production inputs. 相似文献
4.
Research findings are reviewed focusing on yield sensing methods, yield reconstruction, mapping, and errors. Yield sensing methods were explained and yield mapping process was briefly introduced. Grain flow through different combines was explained and the effects of combine dynamics on yield measurement accuracy were discussed. Other errors caused by various sensors that are utilized by a yield monitor were included. It was concluded that with proper installation, calibration, and operation of yield monitors, sufficient accuracy can be achieved in yield measurements to make site-specific decisions. Nevertheless, attention must be paid when interpreting yield maps since yield measurement accuracy can vary depending upon the measurement principle, combine grain flow model, size of management area chosen, and the operator's capabilities and carefulness in following instructions to obtain the best accuracy possible under varying field operating conditions. Some of the errors can be filtered out by careful analysis of the raw yield (or flow rate) data provided by yield monitors. Researchers have focused on crop flow models to improve yield reconstruction process. A yield reconstruction algorithm that effectively handles non-linear combine dynamics has not been developed by researchers yet. More efforts towards yield reconstruction should be encouraged. 相似文献
5.
使用Visual Basic6．0编程语言开发了YMapper产量分布图生成软件系统。研究了一种具有粗大误差数据过滤功能的局部平均插值方法，分析了产量分布图生成过程中涉及到的坐标系定义、产量数据分类与统计分析、图形配色与绘制等问题。对谷物和棉花等作物产量数据的处理结果表明，该系统能够对联合收割机测产系统记录的产量数据文件进行处理，通过插值运算将离散分布的产量数据点生成连续的产量分布图；其误差数据过滤功能能够防止产量过低和过高的粗大误差数据点参与插值运算，使产量分布图的精度得到了保证。系统能够按照用户设置的分类和着色方式，将作物产量的空间分布情况以产量数据点图或产量分布图的形式显示。并且能够对作物的产量水平进行统计分析。 相似文献
6.
Grain flow measured at the flow sensor in a commercial yield monitoring system is considered to be the convoluted result of grain entering the harvester at one time being mixed by the internal threshing and transport processes with grain entering at other times. A transfer function describing the flow of grain within a conventional combine harvester was used to deconvolve the recorded signal using Fast Fourier Transformation (FFT). This process of time series analysis was shown to reposition the yield data in a more accurate manner than the simple time-delay process currently employed. The deconvolution increases the variability in the yield data from 10% to 17% which more closely resembles the variation in crop yield expected from small area samples. The spatial structure of yield variation obtained from small area samples was also shown to be more closely estimated by the deconvoluted data set, however the process does display sensitivity to noise introduced by mechanical/electrical sources and procedural errors. 相似文献
7.
A site-specific sugarbeet yield monitoring system was developed and tested. Two weight-sensing systems were developed, tested, and evaluated on a laboratory test conveyor. One system used 152mm (6in.) idler wheels attached to load cells. The instrumented idlers replaced an existing chain supporting idler on each side of the harvester outlet conveyor. The second system replaced two existing idlers on each side of the harvester outlet conveyor with slide bars covered with UHMW plastic. A product flow rate was obtained from the combined load cell outputs and conveyor speed. Laboratory tests to predict accumulated weight showed a 2.5% error for the slide bar system and a 3.5% error for the idler wheel system. As a result, field testing was performed exclusively with the slide bar weight-sensing system. Calibration was obtained by comparing accumulated truckload weight as indicated by the weight-sensing system to measured gross sugarbeet weight on individual trucks. Typical weight errors ranged from 2% to 3% with an average error of 2.3%. Site-specific yield information was derived from the sugarbeet flow, harvester speed and width, and DGPS receiver. Sugarbeet yield maps were developed as a visual management aid. 相似文献
8.
Delineation and Scale Effect of Precision Agriculture Management Zones Using Yield Monitor Data Over Four Years 总被引：1，自引：0，他引：1
LI Xiang PAN Yu-chun GE Zhong-qiang ZHAO Chun-jiang 《中国农业科学(英文版)》2007,6(2):180-188
In this study, precision agriculture management zones were delineated using yield data over four years from the combine harvester equipped with yield monitor and DGPS receiver. Relative yields measured during each year were interpolated to 4 m2 grid size using ordinary kriging. The resultant interpolated yield maps were averaged across years to create a map of the mean relative yield, which was then used for cluster analysis. The mean yield map of post-classification was processed by applying majority filtering with window sizes that were equivalent to the grid sizes of 12, 20, 28, 36, 44, 52 and 60 m. The scale effect of management zones was evaluated using relative variance reduction, test of significant differences of the means of yield zones, spatial fragmentation, and spatial agreement. The results showed that the post-classification majority filtering （PCMF） eliminated lots of isolated cells or patches caused by random variation while preserving yield means, high variance reduction, general yield patterns, and high spatial agreement. The zoned result can be used as yield goal map for preplant or in-season fertilizer recommendation in precision agriculture. 相似文献
9.
A fast normalized cross correlation (FNCC) based machine vision algorithm was proposed in this study to develop a method for detecting and counting immature green citrus fruit using outdoor colour images toward the development of an early yield mapping system. As a template matching method, FNCC was used to detect potential fruit areas in the image, which was the very basis for subsequent false positive removal. Multiple features, including colour, shape and texture features, were combined in this algorithm to remove false positives. Circular Hough transform (CHT) was used to detect circles from images after background removal based on colour components. After building disks centred in centroids resulted from both FNCC and CHT, the detection results were merged based on the size and Euclidian distance of the intersection areas of the disks from these two methods. Finally, the number of fruit was determined after false positive removal using texture features. For a validation dataset of 59 images, 84.4 % of the fruits were successfully detected, which indicated the potential of the proposed method toward the development of an early yield mapping system. 相似文献
10.
采棉机产量监测系统采集数据的误差分析 总被引：1，自引：0，他引：1
为了获取农田作物产量信息，建立产量分布图，在消化、吸收美国AgLeader公司棉花产量监测系统PF3000的基础上，进行了棉花测产收获试验。在收获过程中，对流量传感器、速度传感器等进行了标定，并对产量数据进行了处理。试验结果表明，现场标定可有效提高测产系统流量传感器和速度传感器的测量精度，但田问环境比较复杂，产量数据采集过程中仍会引入一些误差，需对产量数据进行误差处理。误差处理后得到的棉花产量分布图聚类性增强，较为符合实际情况。 相似文献
11.
联合收割机实时测产系统的抗振动干扰设计 总被引：3，自引：0，他引：3
收割机上的振动严重影响了测产的精度,研究联合收割机车身振动信号特征及其对测产传感器的影响,找出一套新的减振方法.分析了车上振动信号的特征,在此基础上,从谷物称重方式、传感器安装、电子硬件电路、经典算法滤波等方面进行了抗振动干扰的设计.经试验验证系统硬件可靠,软件算法滤波合理,动态测量误差可达到±5%以内,基本上满足了联... 相似文献
12.
小麦生长模型对拔节期和孕穗期低温胁迫响应能力的比较 总被引：1，自引：0，他引：1
【目的】作物生长模型是预测和评估气候变化对作物生产力影响的重要量化工具,明确典型作物生长模型对小麦拔节期和孕穗期低温胁迫响应能力的不足,可以为进一步改进低温胁迫对小麦生产力影响的模拟算法提供指导。【方法】本研究将来自4套国际知名小麦生长模型（美国密歇根州立大学的CERES-Wheat、美国华盛顿州立大学的CropSyst、荷兰瓦赫宁根大学的WOFOST和法国国家农业科学研究院的STICS模型）的典型低温胁迫效应算法,与本课题组研发的小麦生长模拟模型WheatGrow相耦合,利用2012—2013年南京和2013—2015如皋不同品种（扬麦16和徐麦30）、不同温度水平（最低至-6℃）和持续时间（2、4、6 d）的人工气候室低温盆栽试验资料,检验和评价了原WheatGrow模型和耦合后低温胁迫效应算法的WheatGrow模型在拔节期和孕穗期低温胁迫下对小麦叶面积指数动态、茎生物量、地上部总生物量、籽粒产量等指标的预测能力。【结果】拔节—孕穗期低温胁迫明显降低了小麦叶面积指数、地上部生物量积累和籽粒产量,且随低温水平的降低和持续时间的增加降低幅度呈明显升高趋势。比较不同处理时期和品种发现,小麦生长发育及产量对孕穗期低温处理较拔节期低温处理更加敏感,扬麦16较徐麦30对低温胁迫更为敏感。耦合了4种低温胁迫效应算法的WheatGrow模型在模拟叶面积指数动态上较原WheatGrow模型有所改善,但模拟误差仍然较大,其中对孕穗期低温处理的模拟误差大于拔节期处理。4种低温胁迫算法均低估了低温胁迫对茎生物量以及成熟期地上部生物量积累的不利影响。综合比较4种低温胁迫算法的预测能力可以看出,对于叶面积指数和地上部生物量的动态模拟,CropSyst模型中的低温胁迫效应算法表现最好;对于茎生物量的动态模拟,WOFOST模型中的低温胁迫效应算法表现最好,特别是孕穗期低温处理;对于籽粒产量的模拟,STICS模型中的低温胁迫效应算法表现最好,其次是CropSyst模型。【结论】耦合低温胁迫效应算法后的WheatGrow模型,在模拟叶面积指数、茎生物量、地上部生物量和籽粒产量上均好于原WheatGrow模型,且在弱低温条件下的模拟效果好于强低温条件,但是4套算法由于没有考虑低温胁迫对茎秆的直接伤害、低温胁迫对干物质分配的影响以及低温胁迫后的恢复和补偿效应,因此在模拟茎生物量积累,以及模拟不同低温持续时间下的地上部生物量积累存在明显不足。此外,4套低温效应算法引入参数较多,为模型的参数化带来一定的困难,有待今后进一步改进和完善。研究结果对改进小麦生长模型对低温胁迫响应,降低气候变化背景下作物生产力的预测预警的不确定性具有重要意义。 相似文献
13.
利用VirtuoZo软件围绕正射影像的制作展开研究,改变了传统的依靠地面控制点的方法,直接利用外方位元素进行模型的定向,并在此基础上完成了东北林业大学校园正射影像图的制作.该方法的应用节省了大量的外业控制点测量,其成图精度经验证可以达到常规测图规范的要求. 相似文献
14.
DEM提取坡度·坡向算法的对比研究 总被引：4，自引：1，他引：3
以1∶1万地形图数字化所生成的DEM为研究对象,采用6种算法分别提取坡度、坡向。通过比较不同算法所提取坡度的平均值、最大值、标准差、中误差以及坡向的标准差、变异系数、坡向余弦中误差及标准差、不同坡向面积数据,定量地分析中误差与地形变化的关系,找到研究区较合理的坡度、坡向的提取算法,进一步分析不同水平分辨率DEM所提取的坡度、坡向的面积误差变化规律。运用面积百分比加权总体误差和面积百分比平均总体误差的指标,获取2项指标与水平分辨率的线性函数关系,为实际工作选取适宜的水平分辨率提供依据。 相似文献
15.
Precision treatment of both crops and weeds requires the accurate identification of both types of plant. However both identification and treatment methods are subject to error and it is important to understand how misclassification errors affect crop yield. This paper describes the use of a conductance growth model to quantify the effect of misclassification errors caused by an image analysis system.Colour, morphology and knowledge about planting patterns have been combined, in an image analysis algorithm, to distinguish crop plants from weeds. As the crop growth stage advances, the algorithm is forced to trade improved crop recognition for reduced weed classification. Depending on the chosen method of weed removal, misclassification may result in inadvertent damage to the crop or even complete removal of crop plants and subsequent loss of yield. However incomplete removal of weeds might result in competition and subsequent yield reduction. The plant competition model allows prediction of final crop yield after weed or crop removal. The competition model also allows the investigation of the impact on yield of misclassification in the presence of both aggressive and benign weed types. The competition model and the image analysis algorithm have been linked successfully to investigate a range of misclassification scenarios in scenes containing cabbage plants. 相似文献
16.
S. de Bruin G.B.M. Heuvelink J.D. Brown 《Computers and Electronics in Agriculture》2008,63(2):245-256
It has been argued that the upcoming targeted approach to managing field operations, or precision farming, requires that field boundaries are measured with cm level accuracy, thus avoiding losses such as wasted inputs, unharvested crops and inefficient use of the land. This paper demonstrates a method for verification of such claims, based on a statistical model that accounts for temporal correlation in positional measurement errors. Our implementation employs the Data Uncertainty Engine (DUE), which is free software that aids the user in defining probability distributions for uncertain spatial objects, and draws random samples from these distributions. A case study concerning the financial consequences of uncertain geometry for a farmer who uses a digital map to optimise field operations for 15 ha of a potato crop is presented. The error model was parameterised on measurement scenarios representing (1) the Dutch registry of agricultural fields; (2) differential GPS-based field checks for verification of area declarations; and (3) special purpose Real Time Kinematic (RTK)-GPS surveys. We found that a farmer who has a manually digitised map of the study area would benefit from a RTK-GPS survey in a single crop year if the survey would cost less than € 442. An independent test case showed that the results of the error model were consistent with field data. 相似文献
17.
利用F2及其衍生群体定位陆地棉产量和纤维品质性状QTLs 总被引：3，自引：0，他引：3
以陆地棉(Gossypiumhirsutum L.)丰产品种中棉所35和优质品种渝棉1号杂交产生的F2群体为材料,利用SSR标记构建了包含46个连锁群和303个位点的连锁图谱.该图覆盖2 543.6 c M,约占四倍体棉花基因组的57.2%,标记间平均距离为8.4 c M.应用MQM作图法分析F2及其衍生群体家系的产量和纤维品质性状,共得到25个产量和23个纤维品质性状QTLs,其中1个QTL(qFS07-1)在3个环境下检测到,2个QTLs(qFS20-1和qFS21-1)在2个环境下检测到.在检测到的QTLs中,22个分布在A亚组,26个分布在D亚组. 相似文献
18.
国产X—3视差测图仪已被广泛用于土地利用现状图的测制中。然而,高原山区具有高差大,航片航向重迭度高和像片基线长度≤45mm的特点,采用常规方法测图,必须隔片建立立体模型,并且精度差,工效低,适用范围受限。改进方法是右盘像片沿X轴向左平移b′毫米,变一张像片二次高程定向为一次定向,并完成跟踪转绘,从而使测图精度和可测高差范围提高一倍,测图工时减少40％,也扩大了适用范围。 相似文献
19.
The ability to map profit across a cotton field would enable producers to determine where money is being made or lost on their farms and to implement precise field management practices to facilitate the highest return possible on each portion of a field. Mapping profit requires knowledge of site-specific costs and revenues, including yield and price. Price varies site-specifically because fiber quality varies, so mapping fiber quality is an important component of profit mapping. To map fiber quality, the harvest location of individual cotton bales must be known, and thus a system to track the harvest location of cotton modules must be available. To this end, a wireless module-tracking system was recently developed, but automation of the system is required before it will find practical use on the farm. In Part 1 of this report, research to develop automatic triggering of wireless messages is described. In Part 2, research to enable the system to function with multiple harvesting machines of the same type in the same field - a common situation in commercial cotton farming - is described along with testing of the entire automated wireless module-tracking system. To automate wireless-message triggering, a sensing and control system was added to a harvester to indicate when the machine is dumping a basket load of cotton so that wireless messages can be automatically sent from the harvester to subsequent field machines. This automated system was incorporated into the existing wireless module-tracking system, field tested, and it ultimately operated as designed, without human intervention. Linking data collected with this system together with cotton classing data enabled the creation of fiber-quality maps. 相似文献
20.
Spectral unmixing techniques can be used to quantify crop canopy cover within each pixel of an image and have the potential
for mapping the variation in crop yield. This study applied linear spectral unmixing to airborne hyperspectral imagery to
estimate the variation in grain sorghum yield. Airborne hyperspectral imagery and yield monitor data recorded from two sorghum
fields were used for this study. Both unconstrained and constrained linear spectral unmixing models were applied to the hyperspectral
imagery with sorghum plants and bare soil as two endmembers. A pair of plant and soil spectra derived from each image and
another pair of ground-measured plant and soil spectra were used as endmember spectra to generate unconstrained and constrained
soil and plant cover fractions. Yield was positively related to the plant fraction and negatively related to the soil fraction.
The effects of variation in endmember spectra on estimates of cover fractions and their correlations with yield were also
examined. The unconstrained plant fraction had essentially the same correlations (r) with yield among all pairs of endmember spectra examined, whereas the unconstrained soil fraction and constrained plant
and soil fractions had r-values that were sensitive to the spectra used. For comparison, all 5151 possible narrow-band normalized difference vegetation
indices (NDVIs) were calculated from the 102-band images and related to yield. Results showed that the best plant and soil
fractions provided better correlations than 96.3 and 99.9% of all the NDVIs for fields 1 and 2, respectively. Since the unconstrained
plant fraction could represent yield variation better than most narrow-band NDVIs, it can be used as a relative yield map
especially when yield data are not available. These results indicate that spectral unmixing applied to hyperspectral imagery
can be a useful tool for mapping the variation in crop yield. 相似文献