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In sugar beet, maize and soybean, weeds are usually controlled by herbicides uniformly applied across the whole field. Due to restrictions in herbicide use and negative side effects, mechanical weeding plays a major role in integrated weed management (IWM). In 2015 and 2016, eight field experiments were conducted to test the efficacy of an OEM Claas 3-D stereo camera® in combination with an Einböck Row-Guard® hoe for controlling weeds. Ducks-foot blades in the inter-row were combined with four different mechanical intra-row weeding elements in sugar beet, maize and soybean and a band sprayer in sugar beet. Average weed densities in the untreated control plots were from 12 to 153 plants m?2 with Chenopodium album, Polygonum convolvulus, Thlapsi arvense being the most abundant weed species. Camera steered hoeing resulted in 78% weed control efficacy compared to 65% using machine hoeing with manual guidance. Mechanical intra-row elements controlled up to 79% of the weeds in the crop rows. Those elements did not cause significant crop damage except for the treatment with a rotary harrow in maize in 2016. Weed control efficacy was highest in the herbicide treatments with almost 100% followed by herbicide band-applications combined with inter-row hoeing. Mechanical weed control treatments increased white sugar yield by 39%, maize biomass yield by 43% and soybean grain yield by 58% compared to the untreated control in both years. However, yield increase was again higher with chemical weed control. In conclusion, camera guided weed hoeing has improved efficacy and selectivity of mechanical weed control in sugar beet, maize and soybean.  相似文献   

3.
In this paper, a new method to fuse low resolution multispectral and high resolution RGB images is introduced, in order to detect Gramineae weed in rice fields with plants at 50 days after emergence (DAE).The images are taken from a fixed-wing unmanned aerial vehicle (UAV) at 60 and 70 m altitude. The proposed method combines the texture information given by a high resolution red–green–blue (RGB) image and the reflectance information given by a low resolution multispectral (MS) image, to obtain a fused RGB-MS image with better weed discrimination features. After analyzing the normalized difference vegetation index (NDVI) and normalized green red difference index (NGRDI) for weed detection, it was found that NGRDI presents better features. The fusion method consists of decomposing the RGB image using the intensity, hue and saturation (IHS) transformation, then, a second order Haar wavelet transformation is applied to the intensity layer (I) and the NGRDI image. From this transformation, the low–low (LL) coefficients of the NGRDI image are replaced by the LL coefficients of the I layer. Finally, the fused image is obtained by transforming the new wavelet coefficients to RGB space. To test the method, a one hectare experimental plot with rice plants at 50 DAE with Gramineae weeds was selected. Additionally, to compare the performance of the method, two indices were used, specifically, the M/MGT index which is the percentage of detected weed area, and the MP index which indicates the precision of weed detection. These indices were evaluated in four validation zones using three Neural Networks (NN) detection systems based on three types of images; namely, RGB, RGB + NGRDI, and fused RGB-NGRDI. The best weed detection performance was obtained by the NN with the fused image, with M/MGT index between 80 and 108% and MP between 70 and 85%.  相似文献   

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Protein content, which represents rice taste quality, must be estimated in order to create a harvesting plan as well as next year’s basal dressing fertilizer application plan. Ground-based hyperspectral imaging with high resolution (1 × 1 mm per pixel) was used for estimating the protein content of brown rice before harvest. This paper compares the estimation accuracy of rice protein content estimation models generated from the mean reflectances of five regions of interest (ROIs): the overall target area, dark area (less illuminated parts of the rice plants), canopy area (leaves, yellow leaves, and ears), leaf area, and ear and yellow leaf area. The size of the target sampling area was 0.85 × 0.85 m. An R + G + B histogram and a GNDVI–NDVI image were used to separate the target area into the individual ROIs. The values of the coefficient of determination R 2 and the root mean square error of prediction (RMSE) were similar for each model: R 2 ranged from 0.83 to 0.86 and RMSE ranged from 0.27 to 0.30% for all models except for the dark area model, where R 2 = 0.76 and RMSE = 0.35%. There were no significant differences in the magnitude of the estimation error among all models. This result indicates that it is not necessary to obtain an image with a ground resolution that is greater than 0.85 × 0.85 m per pixel to estimate rice protein content before harvest. This result should provide useful information when deciding the altitude of platforms for imaging rice fields.  相似文献   

7.
The present studies have shown Laurus nobilis L. to be a drought tolerant species. When the plant was first subjected to dehydration, the rate of net photosynthesis decreased from Pn = (8–10) to –1 μmol/(m2 s) and to –3 μmol/(m2 s) during the second dehydration before it was subsequently irrigated. The rewatering on August 5 and August 8 promoted a sharp burst of this parameter, but the Pn value was restored to its original level only after August 8. Soil drought caused a drop in a rate of transpiration from 65–70 to 10 mg/(m2 s). Watering soil up to a 15% moisture level brought an increase in E = 25 mg/(m2 s), but only the second watering managed to fully restore it to the initial value. Apical growth of the plants was closely correlated with soil moisture. As the soil moisture was reduced to W = 15–5%, the terminal growth reached a saturation point and started to plateau. Watering the soil up to W = 15% promoted apical growth by 4 mm. Reducing soil moisture to W = 3–4% caused a complete cessation of the growth. Subsequent watering to W = 27–28% led to a gradual and complete recovery of turgor and an increase in the growth rate up to 6–8 mm per day. The surface response functions Pn = f(I, W) and E = f(I, W) allowed us to determine conditions and levels of potential maximums and boundaries of the areas of optimum photosynthesis and transpiration: optimum Pn = 8–9 μmol/(m2 s) with I = 900–1400 μmol/(m2 s) and W = 17–24% and the optimum E = 25–35 mg/(m2 s) with I = 1000–1400 μmol/(m2 s) and W = 16–24%.  相似文献   

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The objective of this study was to compare performance of partial least square regression (PLSR) and best narrowband normalize nitrogen vegetation index (NNVI) linear regression models for predicting N concentration and best narrowband normalize different vegetation index (NDVI) for end of season biomass yield in bioenergy crop production systems. Canopy hyperspectral data was collected using an ASD FieldSpec FR spectroradiometer (350–2500 nm) at monthly intervals in 2012 and 2013. The cropping systems evaluated in the study were perennial grass {mixed grass [50 % switchgrass (Panicum virgatum L.), 25 % Indian grass “Cheyenne” (Sorghastrum nutans (L.) Nash) and 25 % big bluestem “Kaw” (Andropogon gerardii Vitman)] and switchgrass “Alamo”} and high biomass sorghum “Blade 5200” (Sorghum bicolor (L.) Moench) grown under variable N applications rates to estimate biomass yield and quality. The NNVI was computed with the wavebands pair of 400 and 510 nm for the high biomass sorghum and 1500 and 2260 nm for the perennial grass that were strongly correlated to N concentration for both years. Wavebands used in computing best narrowband NDVI were highly variable, but the wavebands from the red edge region (710–740 nm) provided the best correlation. Narrowband NDVI was weakly correlated with final biomass yield of perennial grass (r2 = 0.30 and RMSE = 1.6 Mg ha?1 in 2012 and r2 = 0.37 and RMSE = 4.0 Mg ha?1, but was strongly correlated for the high biomass sorghum in 2013 (r2 = 0.72 and RMSE = 4.6 Mg ha?1). Compared to the best narrowband VI, the RMSE of the PLSR model was 19–41 % lower for estimating N concentration and 4.2–100 % lower for final biomass. These results indicates that PLSR might be best for predicting the final biomass yield using spectral sample obtained in June to July, but narrowband NNVI was more robust and useful in predicting N concentration.  相似文献   

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The persistence, and international expansion, of food banks as a non-governmental response to households experiencing food insecurity has been decried as an indicator of unacceptable levels of poverty in the countries in which they operate. In 1998, Poppendieck published a book, Sweet charity: emergency food and the end of entitlement, which has endured as an influential critique of food banks. Sweet charity‘s food bank critique is succinctly synthesized as encompassing seven deadly “ins” (1) inaccessibility, (2) inadequacy, (3) inappropriateness, (4) indignity, (5) inefficiency, (6) insufficiency, and (7) instability. The purpose of this paper is to examine if and how the contemporary food bank critique differs from Sweet charity’s “ins” as a strategy for the formulation of synthesizing arguments for policy advocacy. We used critical interpretive synthesis methodology to identify relationships within and/or between existing critiques in the peer-reviewed literature as a means to create “‘synthetic constructs’ (new constructs generated through synthesis)” of circulating critiques. We analyzed 33 articles on food banks published since Sweet charity, with the “ins” as a starting point for coding. We found that the list of original “ins” related primarily to food bank operations has been consolidated over time. We found additional “ins” that extend the food bank critique beyond operations (ineffectiveness, inequality, institutionalization, invalidation of entitlements, invisibility). No synthetic construct emerged linking the critique of operational challenges facing food banks with one that suggests that food banks may be perpetuating inequity, posing a challenge for mutually supportive policy advocacy.  相似文献   

10.
Easy-to-capture and robust plant status indicators are important factors when implementing precision agriculture techniques on fields. In this study, aerial red, green and blue color space (RGB) photography and near-infrared (NIR) photography was performed on an experimental field site with nine different cover crops. A lightweight unmanned aerial system (UAS) served as platform, consumer cameras as sensors. Photos were photogrammetrically processed to orthophotos and digital surface models (DSMs). In a first validation step, the spatial precision of RGB orthophotos (x and y, ± 0.1 m) and DSMs (z, ± 0.1 m) was determined. Then, canopy cover (CC), plant height (PH), normalized differenced vegetation index (NDVI), red edge inflection point (REIP), and green red vegetation index (GRVI) were extracted. In a second validation step, the PHs derived from the DSMs were compared with ground truth ruler measurements. A strong linear relationship was observed (R 2 = 0.80?0.84). Finally, destructive biomass samples were taken and compared with the remotely-sensed characteristics. Biomass correlated best with plant height (PH), and good approximations with linear regressions were found (R 2 = 0.74 for four selected species, R 2 = 0.58 for all nine species). CC and the vegetation indices (VIs) showed less significant and less strong overall correlations, but performed well for certain species. It is therefore evident that the use of DSM-based PHs provides a feasible approach to a species-independent non-destructive biomass determination, where the performance of VIs is more species-dependent.  相似文献   

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An essential part of the wild blueberry cropping system is the proper management of agrochemical inputs including herbicides, fungicides and insecticides. A machine vision system was developed and mounted on the rear sprayer boom 0.18 m in front of the sprayer nozzles capable of targeting the agrochemical application on an as-needed basis. The three-point hitch mounted sprayer featured 27 nozzles over a 13.7 m boom width and a storage tank capacity of 1135 l. Nine digital color cameras continually take images in real-time while computer software processes the images in 0.15 s to determine the target locations where the nozzles open and spray at speeds up to 1.77 m s?1. Two wild blueberry fields in central Nova Scotia were selected for smart sprayer performance testing with spot-application (SA) of agrochemical as compared to control and uniform application techniques. Chateau® herbicide was applied in a field with an infestation of hair cap moss. Spray droplet comparison showed moss patches were properly targeted using the smart sprayer. SA provided the same coverage performance as compared to uniform on the moss targets with herbicide application savings of 78.5% using the smart sprayer. Harvestable yield results were similar for all application tracks. TruPhos Magnesium and ZincMax foliar fertilizers were tank mixed with Bravo® and Proline® fungicides and applied to compare the difference of SA, control and uniform application. Results showed SA of foliar fertilizer and fungicide led to less premature leaf drop and increased the blueberry stem height, number of branches, stem diameter and fruit buds. SA of foliar fertilizer and fungicide also increased the percent of healthy wild blueberry plants by 57.8% and the harvestable yield by 137.8%. Fungicide application savings using the smart sprayer for SA were 11.6%.  相似文献   

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Wild blueberry (Vaccinium angustifolium Ait.) fields in the north east Canada are naturally grown in a course textured thin layer of soil and below this layer is a soilless layer of gravel. The root zone depth of this crop varies from 10 to 15 cm. Investigating the depth to the gravel layer below the course textured soil is advantageous, as it affects the water holding capacity of the root zone. Water and nutrient management are the two primary determinants of crop yield and the amount of leaching. The objective of this study was to estimate the depth to the gravel layer using DualEM-2 instrument. A C++ program written in Visual Studio 2010 was used to develop mathematical models for estimating the depth to the gravel layer from the outputs of DualEM-2 sensor. Two wild blueberry fields were selected in central Nova Scotia, Canada to evaluate the performance of DualEM-2 instrument in estimating the rootzone depth above the gravel layer. The mid points of squares created by grid lines were used as the sampling points at each experimental site. The actual depth to the interface was measured manually at selected grid points (n = 50). The apparent ground conductivity (ECa) values of DualEM-2 were recorded and the depth to the interface was estimated for the same sampling points within the selected fields. The fruit yield samples were also collected from the same grid points to identify the impact of the depth to the gravel layer on crop yield. After calibrations, comprehensive surveys were conducted and the actual and estimated depths to the interface were established. The interpolated maps of fruit yield, and the actual (zin) and estimated (\( {\text{z}}_{\text{in}}^{*} \)) depths to the interface were created in ArcGIS 10 software. Results indicated that the zin was significantly correlated with \( {\text{z}}_{\text{in}}^{*} \) for the North River (R 2 = 0.73; RMSE = 0.27 m) and the Carmel (R 2 = 0.45; RMSE = 0.20 m) sites. Results revealed that the areas with shallow depth to the gravel layer were low yielding, indicating that the variation in the depth to the gravel layer can have an impact on crop productivity. Non-destructive estimations of the depth to the gravel layer can be used to develop erosion control strategies, which will result in an increased crop production.  相似文献   

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Till date, the remote sensing research on crop nutrient monitoring has focused mainly on biomass and nitrogen (N) estimation and only a few attempts had been made to characterize and monitor macronutrients other than N. Field experiments were undertaken to study the remote detection of macronutrient status of rice using hyperspectral remote sensing. The variability in soil available N, phosphorus (P) and sulphur (S) and their content in plants were created using artificial fertility gradient design. The leaf and canopy hyperspectral reflectance was captured from variable macronutrient status vegetation. Linear correlation analysis between the spectral reflectance and plant nutrient status revealed significantly (p < 0.05) higher correlation coefficient at 670, 700, 730, 1090, 1260, 1460 nm for the nutrient under study. Published and proposed vegetation indices (VIs) were tested for canopy N, P and S prediction. The results of the investigation revealed that, published VIs (NDVI hyper and NDVI broadbands) could retrieve canopy N with higher accuracy, but not P and S. The predictability of the visible and short wave infrared based VI NRI1510 ((R1510 ? R660)/(R1510 + R660)) was the highest (r = 0.81, p < 0.01) for predicting N. Based on the outcomes of linear correlation analysis new VIs were proposed for remote detection of P and S. Proposed VI P_670_1260 ((R1260 ? R670)/(R1260 + R670)) retrieved canopy P status with higher prediction accuracy (r = 0.67, p < 0.01), whereas significantly higher canopy S prediction (r = 0.58, p < 0.01) was obtained using VI S_670_1090 ((R1090 ? R670)/(R1090 + R670)). The proposed spectral algorithms could be used for real time and site-specific N, P and S management in rice. Nutrient specific wavelengths, identified in the present investigation, could be used for developing relatively low-cost sensors of hand-held instruments to monitor N, P and S status of rice plant.  相似文献   

15.
This study assessed the capability of several xanthophyll, chlorophyll and structure-sensitive spectral indices to detect water stress in a commercial farm consisting of five fruit tree crop species with contrasting phenology and canopy architecture. Plots irrigated and non-irrigated for eight days of each species were used to promote a range of plant water status. Multi-spectral and thermal images were acquired from an unmanned aerial system while concomitant measurements of stomatal conductance (gs), stem water potential (Ψs) and photosynthesis were taken. The Normalized Difference Vegetation Index (NDVI), red-edge ratio (R700/R670), Transformed Chlorophyll Absorption in Reflectance Index normalized by the Optimized Soil Adjusted Vegetation Index (TCARI/OSAVI), the Photochemical Reflectance Index using reflectance at 530 (PRI) and 515 nm [PRI(570–515)] and the normalized PRI (PRInorm) were obtained from the narrow-band multi-spectral images and the relationship with the in-field measurements explored. Results showed that within the Prunus species, Ψs yielded the best correlations with PRI and PRI(570–515) (r2 = 0.53) in almond trees, with TCARI/OSAVI (r2 = 0.88) in apricot trees and with PRInorm, R700/R670 and NDVI (r2 from 0.72 to 0.88) in peach trees. Weak or no correlations were found for the Citrus species due to the low level of water stress reached by the trees. Results from the sensitivity analysis pointed out the canopy temperature (Tc) and PRI(570–515) as the first and second most sensitive indicators to the imposed water conditions in all the crops with the exception of apricot trees, in which Ψs was the most sensitive indicator at midday. PRInorm was the least sensitive index among all the water stress indicators studied. When all the crops were analyzed together, PRI(570–515) and NDVI were the indices that better correlations yielded with Crop Water Stress Index, gs and, particularly, Ψs (r2 = 0.61 and 0.65, respectively). This work demonstrated the feasibility of using narrow-band multispectral-derived indices to retrieve water status for a variety of crop species with contrasting phenology and canopy architecture.  相似文献   

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Additions of large loads of phosphorus (P) enriched animal manure to soils and the persistence of their environmental impact have been associated with continued water quality impairment in regions of high density of confined animal feeding operations. Foliar P in corn (Zea mays L.) and changes in labile P in Aquic Hapludults were determined following P application of 0–560 kg P ha?1 as KH2PO4 and an application of Fe3+ (150 mg Fe3+ kg?1) in field mini-lysimeters to develop calibrations of soil and plant nutritional responses. X-ray fluorescence (XRF) scanning of uppermost leaves of plants at the V2, V5, and V8 stages showed that foliar P proportionally increased with addition rates. Exchangeable and enzyme-labile P forms were effective indicators of foliar XRFS-P for up to 30 days after emergence. Phosphorus calibration curves developed for flag leaves showed that spatial distribution of foliar P (3.6, 4.2, and 5.3 g kg?1) corresponded to field zones treated with 0, 15, and 30 kg P ha?1 as dairy manure P for the past 18 years. Up-to-date crop uptake and availability of P in these Hapludults were best described by a square root function of soil XRFS-P and total exchangeable inorganic P (r2 = 0.4; RMSE = 419 and 422 g ha?1, respectively). Therefore, a timely knowledge of canopy P status and its linkage to actual soil P status supports in situ element-specific sensing and precision nutrient management in order to manage the declining use-efficiency in crops and reduce potential loss to the environment.  相似文献   

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A mosaic disease caused by a virus with isometric particles with a diameter of 28–30 nm has been revealed on a wild vetch species Vicia unijuga in the Amur oblast. The thermal inactivation point (TIP) of the pathogen is 73°C, longevity in vitro (LIV) is up to 3 days, and dilution endpoint (DEP) is 10?5. Virions contain one capsid protein with molecular mass 19 kD. The antigenic relationship between the isolate and brome mosaic virus and earlier identified V. unijuga mosaic virus, a representative of the genus Bromovirus, is determined. The pathogen has been identified as a new strain of this bromovirus. The virus is easily transmitted to cultivated legumes, causing considerable damage.  相似文献   

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Wheat field seedling density has a significant impact on the yield and quality of grains. Accurate and timely estimates of wheat field seedling density can guide cultivation to ensure high yield. The objective of this study was to develop an image-processing based, automatic counting method for wheat field seedlings, to investigate the principle of automatic counting of wheat emergence in the field, and to validate the newly developed method in various conditions. Digital images of the wheat fields at seedling stages with five cultivars and five seedling densities were acquired directly from above the fields. The wheat seedlings information was extracted from the background using excessive green and Otsu’s method. By analyzing the characteristic parameters of the overlapping regions (Overlapping region is a number of overlapping wheat seedlings in the image) of the fields, a chain code-based skeleton optimization method and corresponding equation were established for automatic counting of wheat seedlings in the overlapping regions. The results showed that the newly developed method can effectively count the number of wheat seedlings, with an average accuracy rate of 89.94 % and a highest accuracy rate of 99.21 %. The results also indicated that the accuracy of counting was not affected by different cultivars. However, the seedling density had significant impact on the counting accuracy (P < 0.05). When the seedling density was between 120 × 104 and 240 × 104 ha?1, high counting accuracy (>92 %) could be obtained. The study demonstrated that the newly developed method is reliable for automatic wheat seedlings counting, and also provides a theoretical perspective for automatic seedling counting in the wheat field.  相似文献   

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