scholarly journals A Computer-Vision-Based Approach for Nitrogen Content Estimation in Plant Leaves

Agriculture ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 766
Author(s):  
Tazeem Haider ◽  
Muhammad Shahid Farid ◽  
Rashid Mahmood ◽  
Areeba Ilyas ◽  
Muhammad Hassan Khan ◽  
...  
Keyword(s):  
Computer Vision ◽  
Visual Inspection ◽  
Spinacia Oleracea ◽  
Nitrogen Deficiency ◽  
Laboratory Analysis ◽  
Growth And Yield ◽  
Plant Leaves ◽  
Color Similarity ◽  
Highly Correlated ◽  
Different Color

Nitrogen is an essential nutrient element required for optimum crop growth and yield. If a specific amount of nitrogen is not applied to crops, their yield is affected. Estimation of nitrogen level in crops is momentous to decide the nitrogen fertilization in crops. The amount of nitrogen in crops is measured through different techniques, including visual inspection of leaf color and texture and by laboratory analysis of plant leaves. Laboratory analysis-based techniques are more accurate than visual inspection, but they are costly, time-consuming, and require skilled laboratorian and precise equipment. Therefore, computer-based systems are required to estimate the amount of nitrogen in field crops. In this paper, a computer vision-based solution is introduced to solve this problem as well as to help farmers by providing an easier, cheaper, and faster approach for measuring nitrogen deficiency in crops. The system takes an image of the crop leaf as input and estimates the amount of nitrogen in it. The image is captured by placing the leaf on a specially designed slate that contains the reference green and yellow colors for that crop. The proposed algorithm automatically extracts the leaf from the image and computes its color similarity with the reference colors. In particular, we define a green color value (GCV) index from this analysis, which serves as a nitrogen indicator. We also present an evaluation of different color distance models to find a model able to accurately capture the color differences. The performance of the proposed system is evaluated on a Spinacia oleracea dataset. The results of the proposed system and laboratory analysis are highly correlated, which shows the effectiveness of the proposed system.

scholarly journals Utilizing UAV and 3D Computer Vision for Visual Inspection of a Large Gravity Dam

2018 ◽  
Vol 4 ◽  
Author(s):  
Ali Khaloo ◽  
David Lattanzi ◽  
Adam Jachimowicz ◽  
Charles Devaney
Keyword(s):  
Computer Vision ◽  
Visual Inspection ◽  
Gravity Dam ◽  
3D Computer Vision

A Comparison of Orthogonal Transforms in Engineering Computer Vision

1990 ◽  
Vol 204 (5) ◽  
pp. 321-327 ◽  
Author(s):  
G A H Al-Kindi ◽  
R M Baul ◽  
K F Gill
Keyword(s):  
Computer Vision ◽  
Machine Vision ◽  
Visual Inspection ◽  
Computational Time ◽  
Transform Coefficients ◽  
Orthogonal Transforms ◽  
The Impact

A comparison of a number of commonly used orthogonal transforms, when applied to the recognition and visual inspection of engineering components, has been made. The impact on the performance and computational time for the machine vision process due to varying numbers of transform coefficients is assessed.

Palmer Amaranth (Amaranthus palmeri) Interference in Soybeans (Glycine max)

Weed Science ◽  
1994 ◽  
Vol 42 (4) ◽  
pp. 523-527 ◽  
Author(s):  
Tracy E. Klingaman ◽  
Lawrence R. Oliver
Keyword(s):  
Glycine Max ◽  
Field Study ◽  
Palmer Amaranth ◽  
Growth And Yield ◽  
Yield Reduction ◽  
Amaranthus Palmeri ◽  
Soybean Yield ◽  
Soybean Canopy ◽  
Highly Correlated

A 2-yr field study was conducted at Fayetteville, AR, to determine the effect of Palmer amaranth interference on soybean growth and yield. Palmer amaranth density had little effect on soybean height, but soybean canopy width ranged from 77 cm in the weed-free check to 35 cm in plots with 10 plants m–1of row 12 wk after emergence. Soybean yield reduction was highly correlated to Palmer amaranth biomass at 8 wk after emergence and maturity, soybean biomass at 8 wk after emergence, and Palmer amaranth density. Soybean yield reduction was 17, 27, 32, 48, 64, and 68%, respectively, for Palmer amaranth densities of 033, 0.66, 1, 2, 333, and 10 plants m–1of row. Soybean yield reduction and Palmer amaranth biomass were linear to approximately 2 Palmer amaranth m–1of row, suggesting intraspecific interference between adjacent Palmer amaranth is initiated at Palmer amaranth densities between 2 and 3.33 plants m–1of row.

scholarly journals Special Features on Intelligent Imaging and Analysis

2019 ◽  
Vol 9 (22) ◽  
pp. 4804 ◽  
Author(s):  
Dosik Hwang ◽  
DaeEun Kim
Keyword(s):  
Computer Vision ◽  
Medical Imaging ◽  
Biomedical Applications ◽  
Visual Inspection ◽  
Research Fields ◽  
Robot Systems

Intelligent imaging and analysis have been studied in various research fields, including medical imaging, biomedical applications, computer vision, visual inspection and robot systems [...]

PSXIII-16 Comparison of models for prediction of pig body weight using features from an autonomous 3D computer vision system

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 475-476
Author(s):  
Arthur Francisco Araujo Fernandes ◽  
João R R Dorea ◽  
Robert Fitzgerald ◽  
William O Herring
Keyword(s):  
Computer Vision ◽  
Body Weight ◽  
Vision System ◽  
The Body ◽  
Body Volume ◽  
Depth Images ◽  
3D Computer Vision ◽  
Relevant Variables ◽  
Highly Correlated ◽  
Fully Connected

Abstract Computer vision systems (CVS) have many applications in livestock, for example, they allow measuring traits of interest without the need for directly handling the animals, avoiding unnecessary animal stress. The objective in the current study was to devise an automated CVS for extraction of variables as body measurements and shape descriptors in pigs using depth images. These features were then tested as potential predictors of live body weight (BW) using a 5-fold cross validation (CV) with different modeling approaches: traditional multiple linear regression (LR), partial least squares (PLS), elastic networks (EL), and artificial neural networks (ANN). The devised CVS could analyze and extract features from a video fed at a rate of 12 frames per second. This resulted in a dataset with more than 32 thousand frames from 655 pigs. However, only the 580 pigs with more than 5 frames recorded were used for the development of the predictive models. From the body measures extracted from the images, body volume, area and length presented the highest correlations with BW, while widths and heights were highly correlated with each other (Figure 1). The results of the CV of the models developed for predictions of BW using a selected set of the more significant variables presented mean absolute errors (MAE) of 3.92, 3.78, 3.72, and 2.57 for PLS, LR, EN, and ANN respectively (Table 1). In conclusion, the CVS developed can automatically extract relevant variables from 3D images and a fully connected ANN with 6 hidden layers presented the overall best predictive results for BW.

Enhanced Growth and Yield of Rice (Oryza sativa L.) and Soil Enrichment is Mediated by Enhanced Availability of N and P in Soil and Plant Leaves on Application of Organic Matrix Entrapped Urea and DAP

2015 ◽  
Vol 1 (01) ◽  
pp. 57-68
Author(s):  
Rana Pratap Singh ◽  
Vishalakcchi Ashok ◽  
Sanjeev Kumar
Keyword(s):  
Oryza Sativa ◽  
Field Experiments ◽  
Oryza Sativa L ◽  
Organic Matrix ◽  
Growth And Yield ◽  
Cow Dung ◽  
Plant Leaves ◽  
Chemical Fertilizers ◽  
Field Station ◽  
Neem Leaves

Field experiments were conducted during the Kharif season of the cropping years 2011 and 2012 at the Experimental Field Station of Department of Environmental Science, Babasaheb Bhimrao Ambedkar University, Lucknow to compare the efficacy of organic matrix entrapped chemical fertilizers i.e. Urea and DAP (OMECF) with the conventional chemical fertilizers (CCF) and no fertilizer (NF) for the cultivation of rice (Oryza sativa). The OMECF prepared in granular form contained cow dung, powder of neem leaves (Azadirachta indica), and clay soil (diameter of particles less than 0.02 mm) in 1:1:1 ratios and 15% saresh (plant gum of Acacia sp.) as binder a long with half and one fourth of the recommended dose of commercially available urea and DAP. Single basal application of OMECF showed an increase in plant growth in terms of fresh and dry weights, root length, shoot length, root and leaves numbers and levels of NO3-, NO2-, NH4 + and PO4 -in the rhizosphere and their accumulation in plant leaves.

Effect of Wastewater Irrigation on Heavy Metal Accumulation, Growth and Yield of Vegetables

2017 ◽  
Vol 3 (01) ◽  
pp. 65-76
Author(s):  
Saima Kausar ◽  
Shahla Faizan ◽  
Irfana Haneef
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Accumulation ◽  
Spinacia Oleracea ◽  
High Mobility ◽  
Dry Weight ◽  
Heavy Metal Accumulation ◽  
Growth And Yield ◽  
Spinacia Oleracea L ◽  
Trigonella Foenum Graecum L

Use of wastewater for irrigation is on the rise in India and other developing countries. Wastewater contains plant nutrients that favour crop growth but leave a burden of heavy metals which can enter the food chain and is a cause of great concern. This study was conducted to explore the possibility of using wastewater to grow four vegetables fenugreek (Trigonella foenum-graecum L.), spinach (Spinacia oleracea L.), radish (Raphanus sativus L.) and carrot (Daucus carotaL.). Two aspects namely (1) effect on plant growth and yield (2) accumulation of cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in leaves and roots of the plant have been presented in this paper. The physico-chemical analysis of the wastewater showed that it was rich in total suspended and dissolved solids with large amount of BOD and COD. The higher amount of Cl-, Ca++, Mg++ and K+ were also present in the effluent. The heavy metal (Cd, Cr, Cu, Ni, Pb and Zn) content in wastewater is comparatively more than groundwater (GW). The values of these heavy metals were slightly higher in the soil irrigated with wastewater. The effluent severely affects crop plants and soil properties when used for irrigation. The growth characteristics (plant length, plant fresh and dry weight, leaf number and leaf area) as well as yield characteristics (seed number, 1000 seed weight and seed yield) of all the plants, irrigated with 100% wastewater, were more than that with groundwater. The pattern of increase for the plants was fenugreek greater than radish greater than spinach greater than carrot. Though the wastewater contains low levels of the heavy metals, the soil and plant samples show higher values due to accumulation, but their level was under permissible limits in plants. The trend of metal accumulation in wastewater-irrigated soil is in the order: Pb greater than Ni greater than Zn greater than Cu greater than Cr greater than Cd. Of the four plants that are grown, the order of total heavy metal accumulation in roots is Carrot greater than Radish, while in leaves the order is Spinach greater than Fenugreek. The enrichment factor (EF) of the heavy metals in contaminated soil is in the sequence of Ni (3.1) greater than Pb (2.6) greater than Cd (2.35) greater than Zn (2.18) greater than Cu (1.66) greater than Cr (1.05), while in plants EF varies depending upon the species and plant part. Radish and carrot show a high transfer factor (TF greater than 1) for Cd signifying a high mobility of Cd from soil to plant whereas the TF values for Pb are very low as it is not bioavailable. Thus, it may be concluded that wastewater may be used profitably for the cultivation of these vegetables and could effectively supplement not only the nutrient requirement of the crop but may also act as the source of water..

Growth and yield of clonal guavas in south-eastern Queensland

1986 ◽  
Vol 26 (5) ◽  
pp. 619
Author(s):  
KR Chapman ◽  
B Paxton ◽  
DH Maggs
Keyword(s):  
Fruit Size ◽  
Tree Height ◽  
Tree Canopy ◽  
Tree Size ◽  
Growth And Yield ◽  
Marketable Yield ◽  
Cross Sectional ◽  
South Eastern ◽  
Canopy Volume ◽  
Highly Correlated

Five processing guava clones (GA6- 1, GA7- 12, GA8-30, GA9-35, GA11-56) were tested over 3 cropping years at Nambour, in coastal south-eastern Queensland. Mean marketable yield for the first crop at 2 years of age was 45 kg/tree or 36.23 t/ha at a density of 805 trees/ha. GA11-56, the most acceptable clone for processing, also gave the highest marketable yields of 627, 71.65 and 72.53 t/ha for the first 3 crops. Yield per unit cross sectional area of trunk was a more simple and useful index of yield efficiency than more complex parameters including a fruitfulness index and multiple regressions with yield of north-south canopy spread, number of primary branches and combinations of these and trunk girth. Similarly, trunk - - girth provided at least as good an estimate of tree size as the vigour index. Tree dimension measurements which included east-west canopy spread, north-south canopy spread, tree height, stem height, number of primary branches, crown height, crown radius, tree canopy volume, canopy surface area and an index of crown weight provided no consistent indication of tree size. They were not highly correlated with either accumulated or final yield of the guava. The GA11-56 clone because of its yield, fruit size and other desirable processing characteristics was the only clone that could be recommended for commercial plantings.

scholarly journals Plant leaf alanine: 2-oxoglutarate aminotransferase. Peroxisomal localization and identity with glutamate:glyoxylate aminotransferase

1981 ◽  
Vol 195 (1) ◽  
pp. 235-239 ◽  
Author(s):  
T Noguchi ◽  
S Hayashi
Keyword(s):  
Spinacia Oleracea ◽  
Soluble Fraction ◽  
Sucrose Density Gradient ◽  
Soluble Enzyme ◽  
Plant Leaves ◽  
Peroxisomal Enzyme ◽  
Enzyme Preparations ◽  
Predominant Form ◽  
Single Form ◽  
Alanine Aminotransferase Activity

The distribution of alanine:2-oxoglutarate aminotransferase (EC 2.6.1.2) in spinach (Spinacia oleracea) leaf homogenates was examined by centrifugation in a sucrose density gradient. About 55% of the total homogenate activity was localized in the peroxisomes and the remainder in the soluble fraction. The peroxisomes contained a single form of alanine:2-oxoglutarate aminotransferase, and the soluble fraction contained two forms of the enzyme. Both the peroxisomal enzyme and the soluble predominant form (about 90% of the total soluble activity) were co-purified with glutamate:glyoxylate aminotransferase to homogeneity; it had been reported to be present exclusively in the peroxisomes of plant leaves and to participate in the glycollate pathway in leaf photorespiration [Tolbert (1971) Annu. Rev. Plant Physiol. 22, 45-74]. The evidence indicates that alanine:2-oxoglutarate aminotransferase and glutamate:glyoxylate aminotransferase activities are associated with the same protein. The peroxisomal and soluble enzyme preparations had nearly identical properties, suggesting that the soluble predominant alanine aminotransferase activity is from broken peroxisomes and about 96% of the total homogenate activity is located in peroxisomes.

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