Timely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras very pertinent this work because they can obtain remote-sensing images with higher temporal, spatial, ground resolution than satellites. In study, we evaluated (i) the performance using a near-surface spectroscopy (350~2500 nm, 3 nm at 700 8.5 1400 6.5 2100 nm), UAV-mounted snapshot hyperspectral sensor (450~950 8 532 nm) high-definition...

The number of wheat ears in the field is very important data for predicting crop growth and estimating yield as such receiving ever-increasing research attention. To obtain data, we propose a novel algorithm that uses computer vision to accurately recognize digital image. First, red-green-blue images acquired by manned ground vehicle are selected based on light intensity ensure this method robust with respect intensity. Next, cut target can be identified remaining parts. simple linear...

The number of panicles per unit area is a common indicator rice yield and great significance to estimation, breeding, phenotype analysis. Traditional counting methods have various drawbacks, such as long delay times high subjectivity, they are easily perturbed by noise. To improve the accuracy detection in field, we developed implemented panicle system that based on improved region-based fully convolutional networks, use automate rice-phenotype measurements. field experiments were conducted...

The accurate estimation of the number strawberries in a greenhouse can be used to determine yield and adaptability different varieties controlled environment. detection results play an important role evaluation maturity fruits for purpose quantitative classification. existing manual examination method is error-prone time-consuming, which makes mechanized harvesting difficult. In this work, we propose robust architecture, named "improved Faster-RCNN", detect ground-level RGB images captured...

Abstract Background Fractional vegetation cover (FVC) is an important parameter for evaluating crop-growth status. Optical remote-sensing techniques combined with the pixel dichotomy model (PDM) are widely used to estimate cropland FVC medium high spatial resolution on ground. However, PDM-based estimation limited by effects stemming from variation of crop canopy chlorophyll content (CCC). To overcome this difficulty, we propose herein a “fan-shaped method” (FSM) that uses CCC spectral index...

To obtain an accurate count of wheat spikes, which is crucial for estimating yield, this paper proposes a new algorithm that uses computer vision to achieve goal from image. First, home-built semi-autonomous multi-sensor field-based phenotype platform (FPP) used orthographic images plots at the filling stage. The data acquisition system FPP provides high-definition RGB and multispectral corresponding quadrats. Then, panchromatic are obtained by fusion three channels RGB. Gram–Schmidt then...

Timely and accurately estimates of crop biomass grain yield estimation are crucial for agricultural management. Optical remote sensing techniques can provide parameters (e.g., biomass, fractional vegetation cover (FVC)) at regional larger scales. However, such saturate high canopy cannot detect stored in reproductive organs. The AquaCrop model be used to estimate FVC, output based on growth environmental temperature, rainfall, irrigation). In this work, we developed a method estimating...

Accurate canopy mapping and head-volume estimation of large areas broccoli is an important prerequisite for precision farming since it provides phenotypic traits associated with field management, environmental control, yield prediction. Currently, the detection characterization mostly rely on ground surveys human interpretation, which often time- labor-intensive. Recent developments based unmanned aerial vehicle (UAV) remote sensing offer low cost, timely, flexible data acquisition, thereby...

Maize (zee mays L.) is one of the most important grain crops in China. Lodging a natural disaster that can cause significant yield losses and threaten food security. identification analysis contributes to evaluate cultivates lodging-resistant maize varieties. In this study, we collected visible multispectral images with an unmanned aerial vehicle (UAV), introduce comprehensive methodology workflow extract lodging features from UAV imagery. We use statistical methods screen several potential...

Methods to obtain accurate phenotypic data of the seedling stage maize are receiving ever-increasing research attention because such very important for crop growth and estimating yield. To data, we propose herein an algorithm that uses computer vision accurately recognize seedlings from a digital image. First, red-green-blue (RGB) images acquired by manned ground vehicle (MGV) unmanned aerial (UAV) transformed into grayscale image clarify details images, Otsu threshold-segmentation method,...

Accurate counting of wheat ears in field conditions is vital to predict yield and for crop breeding. To quickly accurately obtain the number a field, we propose herein method count based on fully convolutional network (FCN) Harris corner detection. The technical procedure consists essentially 1) constructing dataset wheat-ear images from acquired red-green-blue (RGB) images; 2) training FCN as segmentation model by using constructed image dataset; 3) preparing testing inputting them into get...

Abstract Background Timely and accurate estimates of canopy chlorophyll (Chl) a b content are crucial for crop growth monitoring agricultural management. Crop reflectance depends on many factors, which can be divided into the following categories: (i) leaf effects (e.g., pigments), (ii) Leaf Area Index [LAI]), (iii) soil background reflectance). The estimation variables, such as Chl contents, from at scale is usually less than that scale. In this study, we propose Visible Near-infrared (NIR)...

Achieving the non-contact and non-destructive observation of broccoli head is key step to realize acquisition high-throughput phenotyping information broccoli. However, rapid segmentation grading remains difficult in many parts world due low equipment development level. In this paper, we combined an advanced computer vision technique with a deep learning architecture allow real-time accurate about head. By constructing private image dataset 100s broccoli-head images (acquired using...

The crop above-ground biomass (AGB) is critically important for monitoring growth, and its accurate estimation can be used by agricultural managers to improve farmland management predict grain yield. Many studies have shown that models the of AGB multiple growth stages based on optical remote sensing spectral indices (SIs) often underestimate in later due saturation problems. purpose this study was estimate winter-wheat using (i) high-frequency information obtained from image wavelet...

Soybean breeders must develop early-maturing, standard, and late-maturing varieties for planting at different latitudes to ensure that soybean plants fully utilize solar radiation. Therefore, timely monitoring of breeding line maturity is crucial harvesting management yield measurement. Currently, the widely used deep learning models focus more on extracting image features, whereas shallow feature information ignored. In this study, we designed a new convolutional neural network (CNN)...

Crop residue left in the field after harvest helps to protect against water and wind erosion, increase soil organic matter, improve quality, so a proper estimate of quantity crop is crucial optimize tillage for research into environmental effects. Although remote-sensing-based techniques cover (CRC) have proven be good tools determining CRC, their application limited by variations moisture soil. In this study, we propose angle index (CRAI) CRC four distinct soils with varying (SM) content...

The accurate large-scale measurement of peach crowns is vital in horticultural science and the optimization orchard management. Nowadays, numerous crown parameters (e.g., area, height, volume) can be obtained via analysis point clouds or photographs. Current laser-based sensors provide required reliable information; however, they are costly time-consuming. Therefore, a simpler approach for required. For this purpose, study presents pipeline monitoring clustering 259 tree based on unmanned...