Calibration of a capacitance probe for measurement and mapping of dry matter yield in Mediterranean pastures

The main objective of this study was to calibrate a commercial capacitance probe for measuring pasture dry matter yields under Mediterranean conditions. The standard method of assessing pasture biomass is based on cutting all the forage within a specified area and requires great effort and expense to collect enough samples to accurately represent a pasture. The field tests were carried out in 2007, 2008 and 2009 on different dates (phenological stages), and on five dairy farms, representing typical pastures in the region (grasses; legumes; and bio-diverse flora, mixture of grasses, legumes and others species). The linear regression techniques used in 2007 to relate the weight of the herbage (direct measurements) to the meter reading of capacitance (indirect measurements) led to high regression coefficients in grasses (R² = 0.90; P < 0.01) and heterogeneous botanical composition (R² = 0.87; P < 0.001) and moderate regression coefficient in legumes species (R² = 0.48; P < 0.05). The validation of the calibration equations in 2008 and 2009 in two sites showed RSME values of 130 kg ha⁻¹ in heterogeneous botanical composition and 456 kg ha⁻¹ in legumes. The results indicated that the capacitance probe together with a GPS receiver might support site-specific management of pastures which would be useful in large areas.     

Widescale testing of the Crop-meter for site-specific farming

A sensor for measuring crop biomass density has been designed and developed to meet the demands for practical use in site-specific farming. The mechanical sensor named ‘Crop-meter’ is based on the pendulum principle. The suitability and measuring stability of the Crop-meter has been confirmed under field conditions in different regions of Germany. Significant correlations were obtained between Crop-meter signals and soil electrical conductivity (R ²=0.16−0.66) and grain yield (R ²=0.42−0.57). To test the suitability of the Crop-meter for site-specific management, it was used to control variable application rates for nitrogen fertiliser, growth regulators and fungicides in real time. A small increase in yield (3.1%) as well as reduced application rates for agrochemicals (14.6% nitrogen fertilisers; 23.1% fungicides and growth regulators) were proved in large-scale trials.     

Design of a hyperspectral nitrogen sensing system for orange leaves

The orange (Citrus sinensis) is one of the most important agricultural crops in Florida. Heavy reliance on agricultural chemicals and low fertilizer use efficiencies in citrus production have raised environmental and economic concerns. In this study, a nitrogen sensor was developed to predict nitrogen concentrations in orange leaves. Four design criteria were chosen to maximize the sensing efficiency and reliability. They were: (1) coverage of the spectral N sensing range, (2) no moving parts, (3) single leaf detection, and (4) diffuse reflectance measurement. Based on chlorophyll and protein spectral absorption bands, the sensor's wavelength ranges were chosen to be 620–950 nm and 1400–2500 nm. A reflectance housing was designed to block environmental noise and to ensure single leaf measurement. A halogen light source, two detector arrays, two linear variable filters, and data acquisition cards with 16-bit analog-to-digital converters were used to collect data. The designed N sensor had a spectral resolution less than 30 nm. Test results showed that the nitrogen sensor had good linearity (r > 0.99) and stability. With averaged signal-to-noise ratio (SNR) of 299, the system was able to predict N content with a root mean square difference (RMSD) of l.69 g kg⁻¹ for the validation data set. Using the N sensor, unknown leaf samples could be classified into low, medium and high N levels with 70% accuracy.     

Investigation and analysis of an ultrasonic sensor for specific yield assessment and greenhouse features identification

The spectrum of an ultrasonic return echo from plants has been shown to contain useful information. The research reported in this paper focused on developing an ultrasonic sensing system and analyzing the ultrasonic classification features that would ultimately be used as the basis for a yield estimation robotic system. An algorithm was also developed for prediction of fruit mass per plant based on the ultrasonic echo return from a plant. The ultrasonic sensor system was tested in lab and pepper greenhouse environments and on single pepper plants, single leaves and fruit. The results showed the potential of ultrasonic sensors for such a robot in classifying plants and greenhouse infrastructures such as walls. It showed the robot’s ability to detect hidden plant rows and fruits as well as making an estimation of the fruit mass in single plants. A multi-linear regression model developed for estimating the energy level was found to be highly significant with R ² of 0.64 and 0.84 for 28–32 and 20–28 kHz ranges respectively. This estimated model was used to derive a prediction method for fruit mass per plant that yielded an R² of 0.34.     

Performance of an Ultrasonic Tree Volume Measurement System in Commercial Citrus Groves

Florida growers have planted citrus groves at varying spacings to improve resource efficiency and to optimize fruit production for maximum economic return. Four commercial groves with different row spacings and tree ages were scanned with a Durand-Wayland ultrasonic system to measure and map tree volumes and to examine the effect of row spacings and tree ages on ultrasonic measurements. The ultrasonically measured volumes (UVs) were compared with manually measured tree volumes (MVs) of 30 trees in each grove to examine the performance of the ultrasonic system. The ultrasonic system measured tree volumes reliably in different groves with an average prediction accuracy (APA) >90%, and correlation with manual measurement of R²=0.95–0.99. Standard error of prediction and root mean square errors were relatively higher in widely spaced old groves than closely spaced young groves. The ultrasonically sensed tree volume map showed substantial variation in canopy volumes (0–240 m³ tree⁻¹) within the grove. Therefore, the use of ultrasonic systems is a better option to quantify and map each tree volume rapidly (real-time) for planning site-specific management practices accurately in commercial groves and for estimating fruit yield.     

滴灌施用噻虫胺防治柑橘木虱研究

【目的】明确滴灌施药防治柑橘木虱Diaphorina citri Kuwayama的可行性,为田间控制柑橘黄龙病传播提供新的手段。【方法】通过室内模拟滴灌施用噻虫胺,测定了噻虫胺在土壤中的分布以及柑橘叶片中含量,研究了滴灌施药对柑橘木虱防治效果。通过田间试验,检测分析了柑橘叶片中噻虫胺含量。【结果】在室内条件下,一次滴灌施药对柑橘木虱的防治效果可长达4个月;噻虫胺在土壤中以滴头为起始点在土壤中呈半圆形迁移分布,当柑橘叶片中噻虫胺质量分数大于0.64 mg·kg–1时,对柑橘木虱的防治效果均高于80%。田间试验表明,在药后7～63 d柑橘上部叶片中噻虫胺的质量分数大于0.64 mg·kg–1。【结论】滴灌施用噻虫胺能有效防治柑橘木虱,是田间控制柑橘黄龙病传播的有效手段。     

小型植保无人机喷雾参数对橘树冠层雾滴沉积分布的影响

【目的】探索小型植保无人机对果树喷施作业的雾滴沉积分布效果及应用前景,研究小型植保无人机喷雾参数对橘树冠层雾滴沉积分布的影响。【方法】采用三因素(飞行高度、飞行速度、喷施流量)的正交试验,应用小型六旋翼植保无人机进行喷雾试验。【结果】根据雾滴沉积密度和雾滴沉积均匀性结果,较佳的作业参数是喷头流量1.0 L·min~(-1)、作业高度2.5 m、作业速度4 m·s~(-1),影响雾滴沉积密度的主次顺序依次为作业速度、作业高度、喷头流量;根据雾滴沉积穿透性结果,作业高度均为2.0 m的试验号2(作业速度4 m·s~(-1),喷头流量0.6 L·min~(-1))和试验号8(作业速度1 m·s~(-1),喷头流量1.0 L·min~(-1))中雾滴沉积穿透性分别为22.21%和22.41%,其雾滴覆盖密度大且穿透性较好;影响雾滴沉积穿透性的因素主次顺序为作业高度、作业速度、喷头流量。【结论】针对植保无人机旋翼风场的影响和橘树独特的树形结构,对植保无人机的作业参数进行了优选,以保证航空喷施作业雾滴在橘树冠层的有效沉积分布。本试验研究可为小型无人机对果树的合理喷施、提高喷施效率提供参考和指导。     

Within-field nitrogen response in corn related to aerial photograph color

Precise management of nitrogen (N) using canopy color in aerial imagery of corn (Zea mays L.) has been proposed as a strategy on which to base the rate of N fertilizer. The objective of this study was to evaluate the relationship between canopy color and yield response to N at the field scale. Six N response trials were conducted in 2000 and 2001 in fields with alluvial, claypan and deep loess soil types. Aerial images were taken with a 35-mm slide film from ≥1100 m at the mid- and late-vegetative corn growth stages and processed to extract green and red digital values. Color values of the control N (0 kg N ha⁻¹) and sufficient N (280 kg N ha⁻¹ applied at planting) treatments were used to calculate the relative ratio of unfertilized to fertilized and relative difference color values. Other N fertilizer treatments included side-dressed applications in increments of 56 kg N ha⁻¹. The economic optimal N rate was weakly related (R ² ≤ 0.34) or not related to the color indices at both growth stages. For many sites, delta yield (the increase in yield between control N and sufficient N treatments) was related to the color indices (R ² ≤ 0.67) at the late vegetative growth stage; the best relationship was with green relative difference. The results indicate the potential for color indices from aerial photographs to be used for predicting delta yield from which a site-specific N rate could be determined.     

Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages

Many hyperspectral vegetation indices (VIs) have been developed to estimate crop nitrogen (N) status at leaf and canopy levels. However, most of these indices have not been evaluated for estimating plant N concentration (PNC) of winter wheat (Triticum aestivum L.) at different growth stages using a common on-farm dataset. The objective of this study was to evaluate published VIs for estimating PNC of winter wheat in the North China Plain for different growth stages and years using data from both N experiments and farmers’ fields, and to identify alternative promising hyperspectral VIs through a thorough evaluation of all possible two band combinations in the range of 350–1075 nm. Three field experiments involving different winter wheat cultivars and 4–6 N rates were conducted with cooperative farmers from 2005 to 2007 in Shandong Province, China. Data from 69 farmers’ fields were also collected to evaluate further the published and newly identified hyperspectral VIs. The results indicated that best performing published and newly identified VIs could explain 51% (R₇₀₀/R₆₇₀) and 57% (R₄₁₈/R₄₀₅), respectively, of the variation in PNC at later growth stages (Feekes 8–10), but only 22% (modified chlorophyll absorption ratio index, MCARI) and 43% (R₇₆₃/R₇₆₁), respectively, at the early stages (Feekes 4–7). Red edge and near infrared (NIR) bands were more effective for PNC estimation at Feekes 4–7, but visible bands, especially ultraviolet, violet and blue bands, were more sensitive at Feekes 8–10. Across site-years, cultivars and growth stages, the combination of R₃₇₀ and R₄₀₀ as either simple ratio or a normalized difference index performed most consistently in both experimental (R ² = 0.58) and farmers’ fields (R ² = 0.51). We conclude that growth stage has a significant influence on the performance of different vegetation indices and the selection of sensitive wavelengths for PNC estimation, and new approaches need to be developed for monitoring N status at early growth stages.     

Laser rangefinder-based measuring of crop biomass under field conditions

Knowledge of site-specific crop parameters such as plant height, coverage and biomass density is important for optimising crop management and harvesting processes. Sensors for measuring crop parameters are essential pre-requisites to gather this information. In recent years, laser rangefinder sensors have been adopted in many industrial applications. In agricultural engineering, the potential of laser rangefinders for measuring crop parameters has been little exploited. This paper reports the design and the performance of a measuring system based on a triangulation and a time-of-flight laser rangefinder for estimating crop biomass density in representative crops under field conditions. It was shown that the mean height of reflection point is a suitable parameter for non-contact indirect measurement of crop biomass by laser rangefinder sensors. The main parameters for potential assessment were the coefficient of determination (R ² ) and the standard error (RMSE) for the relation between crop biomass density and the mean height of the reflection point in crop stands from oilseed rape, winter rye, winter wheat and grassland during the vegetation period in 2006. For the triangulation sensor, R ² was in the range from 0.87 to 0.98 and for the time-of-flight sensor in the range from 0.75 to 0.99 for both fresh matter and dry matter density. The triangulation sensor had a reduced suitability caused by masking effects of the reflected beam and because of limited measuring range. Based on the results of experiments and technical data, it was concluded that the time-of-flight principle has good potential for site-specific crop management.     

Single superphosphate fertilizer distribution among seeder-fertilizer rows

The objective was to verify the uniformity of single superphosphate distribution among seeder-fertilizer rows and its consequences on crops. The experiment was installed in the municipality of Tibagi—PR, involving the following crop rotation in the same area: black oat (Avena strigosa) in 2012, corn (Zea mays) in the 2012–13 season, wheat (Triticum aestivum) in 2013, soybeans (Glycine max) in the 2013–14 season, black oat in 2014 and corn closing the cycle in the 2014–15 season. The experimental design was used in randomized blocks, considering the number of rows of the seeder-fertilizer (ranging from 11 for corn to 27 for wheat) as treatments; with three replicates. During the experimental period, 250 kg ha^?1 of single superphosphate were distributed per crop at sowing, with a mean deviation of up to 14% and variation in the fertilizer mass among the seeder-fertilizer rows in up to 52%. The variables evaluated were initial population and income components. It was concluded that it is not possible to correlate the variation of fertilizer distribution among rows of the seeder-fertilizer with the variables that presented significant differences in the crops through three agricultural seasons. This fact may be related to the alternation of the highest and lowest doses of simple superphosphate. Due to the succession of seeder-fertilizers used over the years to crops seeding, there was a compensation for the random variation of fertilizer among rows and crop spacings along the crop seasons.

     

Prediction of yield and the contribution of legumes in legume-grass mixtures using field spectrometry

Productivity and botanical composition of legume-grass swards in rotation systems are important factors for successful arable farming in both organic and conventional farming systems. As these attributes vary considerably within a field, a non-destructive method of detection while doing other tasks would facilitate more targeted management of crops and nutrients in the soil–plant–animal system. Two pot experiments were conducted to examine the potential of field spectroscopy to assess total biomass and the proportions of legume, using binary mixtures and pure swards of grass and legumes. The spectral reflectance of swards was measured under artificial light conditions at a sward age ranging from 21 to 70 days. Total biomass was determined by modified partial least squares (MPLS) regression, stepwise multiple linear regression (SMLR) and the vegetation indices (VIs) simple ratio (SR), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and red edge position (REP). Modified partial least squares and SMLR gave the largest R ² values ranging from 0.85 to 0.99. Total biomass prediction by VIs resulted in R ² values of 0.87–0.90 for swards with large leaf to stem ratios; the greatest accuracy was for EVI. For more mature and open swards VI-based detection of biomass was not possible. The contribution of legumes to the sward could be determined at a constant biomass level by the VIs, but this was not possible when the level of biomass varied.     

Comparison of passive and active canopy sensors for the estimation of vine biomass production

Recent advances in optical designs and electronic circuits have allowed the transition from passive to active proximal sensors. Instead of relying on the reflectance of natural sunlight, the active sensors measure the reflectance of modulated light from the crop and so they can operate under all lighting conditions. This study compared the potential of active and passive canopy sensors for predicting biomass production in 25–32 randomly selected positions of a Merlot vineyard. Both sensors provided estimates of the normalized difference vegetation index (NDVI) from a nadir view of the canopy at veraison that were good predictors of pruning weight. Although the red NDVI of the passive sensors explained more of the variation in biomass (R ² = 0.82), its relationship to pruning weight was nonlinear and was best described by a quadratic regression (NDVI = 0.55 + 0.50 wt−0.21 wt²). The theoretically greater linearity of the amber NDVI-biomass relationship could not be verified under conditions of high biomass. The linear correlation to stable isotope content in leaves (¹³C and ¹⁵N) provided evidence that canopy reflectance detected plant stresses as a result of water shortage and limited fertilizer N uptake. Thus, the canopy reflectance data provided by these mobile sensors can be used to improve site-specific management practices of vineyards.     

Assessment of forage mass from grassland swards by height measurement using an ultrasonic sensor

The non-destructive assessment of forage mass in legume-grass mixtures as a tool for yield mapping in precision farming applications has been investigated in two field experiments. An ultrasonic sensor was used to determine sward heights. Forage mass-height relationships were evaluated by carrying out static measurements on binary legume-grass mixtures of white clover (Trifolium repens L.), red clover (Trifolium pratense L.), and lucerne (Medicago sativa L.) with perennial rye grass (Lolium perenne L.) across a wide range of sward heights (5.0-104.2 cm) and forage mass (0.15-11.25 t ha⁻¹). Mobile measurements, hereafter referred to as “on-the-go” were conducted by mounting the ultrasonic sensor in combination with a high-precision Differential Global Positioning System (DGPS) on a vehicle. Data were recorded along experimental plots consisting of perennial rye grass and grass-clover mixtures similar to the mixtures that were used for the static experiment. The static experiment revealed a relationship between ultrasonic sward height and forage mass explaining 74.8% of the variance with a standard error (SE) of 1.05 t ha⁻¹ in a common dataset. The type of legume species, weed proportion, and growth period had a significant impact on the above mentioned relationship. Legume-specific regression functions had higher R²-values of up to 0.855 (white clover mixture). Datasets including legume-specific mixtures and pure swards of both components reached comparable R² values between 0.799 and 0.818 but exhibited higher SE values. The abundance of weeds resulted in increased ultrasonic sward heights for the same levels of forage mass. On-the-go measurements across experimental field plots yielded a sward height range of 1.4-70.4 cm. Abrupt forage mass changes at the transition from treatment plots to cut interspaces resulted in a significant deviation from stubble height within a distance of 50 cm to plot borders. When legume-specific equations derived from static measurements were applied to sward heights, forage mass was overestimated by 21.4% on average. Mean residuals from predicted forage mass ranged between 0.893 (pure grass) and 1.672 (red clover mixture) and increased significantly if the point sampling distance along the track was increased to more than 0.82 m on average across all plots. The prediction accuracy of forage mass from ultrasonic height measurements is promising; however, further modifications to the technique are necessary. One such improvement can be the use of spectral reflectance signatures in combination with the ultrasonic sensor.     

侧向风对航空植保无人机平面扇形喷头雾滴飘移的影响

目的 侧向风是影响植保无人机航空喷施雾滴飘移和作业效果的主要因素。探究航空植保喷施过程中侧向风对雾滴沉积和飘移的影响,为植保无人机航空喷施作业参数的选择和作业关键部件的改进提供数据支持和理论指导。方法 以常用平面扇形喷头Lechler系列的LU 120-015和LU 120-03标准压力喷头为研究对象,基于计算流体力学离散相模型的粒子跟踪技术,在适宜的边界条件下对喷施作业过程中风洞内雾滴流场和农药喷洒离散相进行模拟试验;通过仿真模拟对平面扇形喷头喷施的雾滴沉积和飘移分布情况进行可视化分析,探究雾滴粒子在不同侧风风速条件下的飘移特性;在农业航空专用风洞中,采用近似条件对雾滴的沉积飘移特性进行试验验证和分析。结果 仿真模拟结果表明,随着侧向风速的增加,离散相雾滴粒子飘移程度越严重,雾滴水平飘移越明显。随着侧向风速的增加,模拟离散相雾滴粒子的准确沉积率(R_a)呈指数下降,由14.11%下降到0.66%;水平飘移率(R_h)呈线性增加,由14.25%增加到60.58%。风洞试验结果表明,在侧风风速分别为1、3和6 m/s的条件下,雾滴的R_h分别为0.4%、48.1%和75.1%,且雾滴在风洞内部会随着侧风风速的增加发生一定程度的卷扬现象。仿真模拟与风洞测试试验的R_h具有显著相关性(R²=0.963,P<0.05)。结论 仿真模拟对航空喷施条件下的雾滴飘移具有较好的预测效果;采用仿真模拟辅助风洞试验测试的方法,可以比较准确地得出航空植保无人机作业中常用平面扇形喷头的雾滴沉积与飘移情况。     

基于物联网和LSTM的柑橘园土壤含水量和电导率预测模型

目的 构建柑橘果园环境信息物联网实时采集系统,建立基于物联网和长短期记忆(LSTM)的柑橘园土壤含量和电导率预测模型,为果园灌溉施肥管理、效果预测评估提供参考依据。方法 利用土壤温度、含水量、电导率三合一传感器,在柑橘果园中设置5个节点和1个气象站,通过ZigBee短距离无线通信和GPRS远距离无线传输,将果园气象数据和土壤墒情数据传输至远程服务器。利用LSTM模型建立气象数据与土壤含水量和电导率的预测模型,计算均方根误差(RMSE)和决定系数(R²)以进行性能评估。结果 物联网系统能够实现远程传输柑橘果园环境数据,建立了基于LSTM和广义回归神经网络(GRNN)的土壤含水量和电导率预测模型,模型在5个节点的数据集的训练结果分别为：LSTM模型训练的土壤含水量和电导率的RMSE范围分别为6.74~8.65和6.68~8.50,GRNN模型训练的土壤含水量和电导率的RMSE范围分别为7.01~14.70和7.60~13.70。利用生成的LSTM模型和气象数据进行拟合,将土壤含水量和电导率的预测值与实测值进行回归分析,LSTM模型拟合的土壤含水量和电导率的R²范围分别为0.760~0.906和0.648~0.850,GRNN模型拟合的土壤含水量和电导率的R²范围分别为0.126~0.369和0.132~0.268,说明LSTM模型的性能表现较好。结论 建立了柑橘果园环境的物联网信息传输系统,构建的基于LSTM的果园土壤含水量和电导率预测模型具有较高的精度,可用于指导柑橘果园的灌溉施肥管理。     

一种风压转换近地风速检测装备设计与试验

【目的】针对目前相关设备风场自干扰大的问题,为更好地获取无人机(Unmanned arial vehicle,UAV)近地风场参数信息,以风压信号为基础,采用皮托管风速传感器设计一种风压转换近地风速检测装备。【方法】利用轴流风机对叶轮风速传感器和皮托管风速传感器的感应位置进行风速干扰对比试验,利用热线式标准风速仪测定干扰前后的风速变化,利用轴流风机以相同的风速检测该装备所有传感器的测量风速并记录,得到该系统的一致性。将同一风速下标准热线式风速仪的测量风速和该系统的传感器测量风速进行对比,找出皮托管风速传感器准确度较低的风速段,利用Matlab软件对风压信号–风速值进行拟合。【结果】在10.00~15.00 m·s–1风速下皮托管风速传感器对直流风速的削弱不超过1%,而叶轮传感器达到20%以上。系统所采用的30个风压变送器在风速为15.00 m·s~~(–1)时的最大绝对差异为0.96 m·s–1,最大相对差异为6.40%,变异系数为1%。以三次公式进行拟合后,误差平方和(SSE)为0.099 6,拟合优度(R2)0.96。【结论】本系统能够有效检测无人机下旋翼风速数据,且比叶轮式风速传感器网络测量系统在减少干扰方面具有明显优势,可以为研究无人机田间作业提供有效帮助。     

柳橙皮基可降解膜的制备及其性能研究

为探索新型可降解膜材料的制备方法及其性能,以柳橙皮为成膜基材,海藻酸钠和羧甲基纤维素钠为增稠剂,甘油为增塑剂,采用流延法制备柳橙皮膜,并探究了柳橙皮浓度、增稠剂浓度、增塑剂浓度对膜力学性能和阻隔性能的影响。结果表明:柳橙皮浓度为1.5%,海藻酸钠浓度为0.1%,羧甲基纤维素钠浓度为0.2%,甘油浓度为0.2%,此时膜的综合性能最佳。其主要指标:抗拉强度为24.08 MPa,断裂伸长率为15.73%,水蒸气透过系数为1.686×10~(-12)g·cm·cm~(-2)·s~(-1)·Pa~(-1)。研究表明,柳橙皮成膜性较好,且具有良好的力学性能和阻隔性能,是一种具有开发潜力的新型包装材料。     

Laboratory Measurement of Mowing Machine Material Feed Rate

The main objective of this research was to evaluate two possibilities of material feed rate measurement of modern mowing machines equipped with conditioner. The machines are commonly used for harvest of grasses (Lolium multiflorum, Dactylus glomerata, Phleum pratense, etc.), clover (Trifolium pratense, etc.), alfalfa (Medicago sativa) etc.A mowing machine with finger conditioner was equipped with an electronic measuring unit for the purpose of our measurements. The mowing machine's conditioner shaft was supplied with strain gauges placed on a torque-meter and with a RPM optical sensor counter. Together with torque-meter the mowing machine was equipped with a curved impact plate mounted on the machine's material output.It was decided to arrange a laboratory measurement to obtain information about the dependence of conditioner power input and signals from the impact plate on material mass flow. A mixture of grass and alfalfa was used for our measurement.The measurements carried out proved that a very good linear relationship existed between the conditioner's power input, output frequency of the apparatus measuring impact force by means of the impact plate, and material feed rate through the mowing machine. The calculated coefficients of correlation were about 0.95. It is possible to differentiate a material feed rate difference of 0.5kgs^–1 using both methods. This accuracy should be sufficient for practical utilisation such as creating yield maps.