Crop Monitoring for Nitrogen Nutrition Level by Digital Camera

2018 ◽  
pp. 595-603 ◽  
Author(s):  
Igor Korobiichuk ◽  
Vitaliy Lysenko ◽  
Oleksiy Opryshko ◽  
Dmiyriy Komarchyk ◽  
Natalya Pasichnyk ◽  
...  
Keyword(s):  
Nitrogen Nutrition ◽  
Digital Camera ◽  
Crop Monitoring

scholarly journals Rice crop monitoring using multirotor UAV and RGB digital camera at early stage of growth

2018 ◽  
Vol 169 ◽  
pp. 012095 ◽  
Author(s):  
C Y N Norasma ◽  
M Y Abu Sari ◽  
M A Fadzilah ◽  
M R Ismail ◽  
M H Omar ◽  
...  
Keyword(s):  
Early Stage ◽  
Digital Camera ◽  
Rice Crop ◽  
Crop Monitoring

Using simple RGB Camera to estimate Nitrogen Uptake, Nitrogen Nutrition Index (NNI) and critical Nitrogen: Spring wheat case study.

2020 ◽  
Author(s):  
Jiftah Ben-Asher
Keyword(s):  
Spring Wheat ◽  
Dry Matter ◽  
Nitrogen Nutrition ◽  
N Uptake ◽  
Maximum Yield ◽  
Digital Camera ◽  
Growth Period ◽  
Growth Cycle ◽  
Nitrogen Nutrition Index ◽  
Grain Unit

<p>The first Nc dilution curve was based on dry matter (DM) power function. This model is limited to  point of singularity near zero. Another disadvantage was that it required meaasurements of DM which is time and labor consuming. Alternatively we proposed a logistic model that starts at zero and on the abscissa assumed a linear relationship between days after emergence (DAE) and DM throughout the relevant stages of wheat growth cycle.  </p><p>The Objectives of this study were to: 1) To demonstrate the feasibility of digital camera to replace laboratory tests. 2) To Determine critical N (Nc) and Nitrogen nutrition Index(NNI) of spring wheat and 3) Use N% and dry matter yield in order to calculate N uptake by wheat. This last is expected to be a tool to calculate the required amount of nitrogen to obtain maximum yield.</p><p>Wheat experiments were conducted in greenhouse lysimeters. Varied rates of N fertilizer (equivalent to 0–180 kg ha<sup>-1</sup>) and several  cultivars varying from shortest to longest ripening growth period. Nc reduced gradually from about 6% to 2%  ( =60-20 gr/Kg) when DM increased with DAE  from 0 to 14,000 kg/ha during 80 growing days.  NNI was stable and clearly distinct between   maximal index (1.0  and minimal index (0.2) when (DAE) was about 60;   Photographs succeeded to replicate laboratory measurements and obtained a linear regression curve with a unity  slop and r<sup>2</sup>=0.93. Nitrogen.  use efficiency (NUE) ranged from 50 to 65 kg  DM/unit N and from 30 to 50 Kg grain /unit N .</p>

scholarly journals COMPARING COMMERCIAL OPTICAL SENSORS FOR CROP MONITORING TASKS IN PRECISION VITICULTURE

2009 ◽  
Vol 40 (1) ◽  
pp. 11 ◽  
Author(s):  
Fabrizio Mazzetto ◽  
Aldo Calcante ◽  
Aira Mena
Keyword(s):  
Remote Sensing ◽  
Optical Sensors ◽  
Precision Agriculture ◽  
Digital Camera ◽  
Test Results ◽  
Crop Monitoring ◽  
Pv Systems ◽  
Cultural Conditions ◽  
Precision Viticulture ◽  
Increasing Demand

The emergence of precision agriculture technologies and an increasing demand for higher quality grape products has led to a growing interest in Precision Viticulture. Actually, cultural monitoring is the most important application in PV systems: it requires specific technologies able to investigate the cultural conditions. To this aim, typically remote sensing surveys are adopted. These, anyhow, involve technical, economical and organisational barriers hampering a wide diffusion of their application. In order to overcome these problems, it would be necessary to substitute and/or integrate remote sensing information with alternative ground sensing technologies, to be employed directly inside the vineyard. This paper considers a commercial optical sensor, the GreenSeeker, useful in ground sensing surveys, and it compares its performances in monitoring vine with results obtained by a multispectral digital camera used as a tester. The experimentation was carried out in a greenhouse, on an artificial row including 15 grapevines (Cabernet Sauvignon variety). In front of the row, it was fixed a metallic rail gauge in order to permit a longitudinal movement of the Greenseeker sensor. Each plant was investigated at three different heights with a 5 s data time acquisition. Simultaneously, photos of the same grapevine were took by a multispectral digital camera, in order to obtain NDVI values through image analysis. The multispectral digital camera, normally used for remote sensing survey in agriculture, was considered as a test. Results demonstrate a strength correlation (R2 = 0.97) between the NDVI values measured through the two methods. This shows the same behaviour of the two tools, according to crop vigour and stress conditions induced into the plants. Consequently the GreenSeeker can be considered as a suitable solution for cultural monitoring in viticulture.

Using a Digital Camera for Documentation

2002 ◽  
Vol 12 (4) ◽  
pp. 145-146
Author(s):  
Steven C. Chang
Keyword(s):  
Digital Camera

A testing paradigm for quantifying ICC profilers

2019 ◽  
Vol 2019 (1) ◽  
pp. 80-85
Author(s):  
Pooshpanjan Roy Biswas ◽  
Alessandro Beltrami ◽  
Joan Saez Gomez
Keyword(s):  
Digital Camera ◽  
Visual Assessment ◽  
Just Noticeable Difference ◽  
Color Management ◽  
Color Gamut ◽  
Gamut Mapping ◽  
Digital File ◽  
Mapping Process ◽  
Testing Paradigm

To reproduce colors in one system which differs from another system in terms of the color gamut, it is necessary to use a color gamut mapping process. This color gamut mapping is a method to translate a specific color from a medium (screen, digital camera, scanner, digital file, etc) into another system having a difference in gamut volume. There are different rendering intent options defined by the International Color Consortium [5] to use the different reproduction goals of the user [19]. Any rendering intent used to reproduce colors, includes profile engine decisions to do it, i.e. looking for color accuracy, vivid colors or pleasing reproduction of images. Using the same decisions on different profile engines, the final visual output can look different (more than one Just Noticeable Difference[16]) depending on the profile engine used and the color algorithms that they implement. Profile performance substantially depends on the profiler engine used to create them. Different profilers provide the user with varying levels of liberty to design a profile for their color management needs and preference. The motivation of this study is to rank the performance of various market leading profiler engines on the basis of different metrics designed specifically to report the performance of particular aspects of these profiles. The study helped us take valuable decisions regarding profile performance without any visual assessment to decide on the best profiler engine.

INFLUENCE OF CULTIVATION DEGREE OF SOD-PODZOLIC SOIL ON RESPONSIVENESS OF SOWING PEAS TO NITROGEN NUTRITION LEVEL

2020 ◽  
Keyword(s):  
Podzolic Soil ◽  
Nitrogen Nutrition ◽  
Maximum Yield ◽  
Mineral Nitrogen ◽  
Degree Of Saturation ◽  
Cultivated Soil ◽  
Combined Use ◽  
Dry Soil ◽  
Microbial Preparation ◽  
Harvest Maturity

The article presents the results of a vegetation experiment on studying an effect of increasing doses of nitrogen (factor С - N0; No.o5; No.io; N015; No.2o; N0,25 g/kg of absolutely dry soil) and pre-sowing inoculation of seeds with biological preparation "Risotorphine" (factor В - no inoculation; by inoculation) on the formation of vegetative mass and grain yield ofpeas at cultivating in the conditions of a poorly cultivated (factor A0) and of a medium cultivated (factor A f sod-podzolic soil. Cultivation degree of soil was expressed by such criteria as power of an arable horizon, value of metabolic acidity and content of mobile phosphorus, a degree of saturation of soil with bases. For experience tab there were used Mitscher-lich cups with a capacity of 5 kg of absolutely dry soil (a.d.s.), in 16 repetitions of options. The experiments were conducted in the conditions of vegetation site on the territory of University Scientific Centre "Lipogorie" of FSBEI Perm GATA, guided by a science-based methodology. When harvesting peas for a green mass more intensive development and productivity of plants (23.3 and 58.9, 40.0, 78.8 g/cup, respectively) in the phase of stem branching and budding a beginning offlowering that is recorded for its use on the background of inoculation, usage of mineral nitrogen in a dose of 0.10 g/kg on a poorly cultivated soil and 0.15 g/kg a.d.s. on a medium cultivated soil. Applying of higher doses of nitrogen has a depressing effect on development of assimilating surface of pea plants on a poorly and a medium cultivated soil. When raising pea plants before harvest maturity of grain: in the conditions of a poorly cultivated soil for yield at the level of 7.92 g/cup, the process of carrying on only an inoculation of seed with microbial preparation "Rizotorfin" can be considered; in the medium cultivated soil varieties, plant peas impose higher requirements for the level of mineral nutrition the maximum yield in the experiment (which 9.22 g/cup), noted at a combined use of inoculation and mineral nitrogen in a dose of 0.20 g/kg a.d.s.

PENGARUH COUNTRY OF ORIGIN, WORD OF MOUTH, KUALITAS YANG DIPERSEPSIKAN TERHADAP NIAT BELI: STUDY PADA KAMERA DIGITAL MEREK JEPANG

2019 ◽  
Vol 4 (3) ◽  
pp. 365-374
Author(s):  
Edy Purwanto ◽  
Aryo Wibisono
Keyword(s):  
Purchase Intention ◽  
Structural Equation ◽  
Sampling Method ◽  
Word Of Mouth ◽  
Country Of Origin ◽  
Digital Camera ◽  
Perceived Quality ◽  
Equation Modeling ◽  
Country Of Origin Image ◽  
Method Analysis

This study aims to test the influence of country of origin image and word of mouth on perceived quality. Then, the country of origin image and word of mouth and perceived quality on purchase intention of digital camera from Japan. The number of samples in this research are 230 respondents taken by purposive sampling method. Analysis of Structural Equation Modeling (SEM) is used to test the hypothesis. The results of this study showed that country of origin image and word of mouth have a positive and significant effect on perceived quality. Then, Word of mouth and perceived quality have a positive and significant effect on purchase intention but a country of origin image has no significant effect on purchase intention. 

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