A low-cost smartphone controlled sensor based on image analysis for estimating whole-plant tissue nitrogen (N) content in floriculture crops

2020 ◽  
Vol 169 ◽  
pp. 105173 ◽  
Author(s):  
Ranjeeta Adhikari ◽  
Cheng Li ◽  
Kirby Kalbaugh ◽  
Krishna Nemali
2021 ◽  
Author(s):  
Samantha Richardson ◽  
Samira Al Hinai ◽  
Jesse Gitaka ◽  
Will Mayes ◽  
Mark Lorch ◽  
...  

<p>Routine monitoring of available soil nutrients is required to better manage agricultural land<sup>1</sup>, especially in many lower and middle income countries (LMICs). Analysis often still relies on laboratory-based equipment, meaning regular monitoring is challenging.<sup>2</sup> The limited number of in situ sensors that exist are expensive or have complex workflows, thus are not suitable in LMICs, where the need is greatest.<sup>3</sup> We aim to develop a simple-to-use, low-cost analysis system that enable farmers to directly monitor available nutrients and pH on-site, thus making informed decisions about when and where to apply fertilisers.</p><p>We combine nutrient extraction via a cafetiere-based filtration system with nutrient readout on a paper microfluidic analysis device (PAD) employing colour producing reactions that can be captured via a smartphone camera through an app. Image analysis of colour intensity permits quantitation of analytes. We initially focus on key nutrients (phosphate, nitrate) and pH analysis.</p><p>For extraction of phosphate, we mixed soil and water in the cafetiere and quantified the extracted phosphate via phosphomolybdenum blue chemistry. For example, for 5 g of soil, a water volume of about 160 mL led to optimum extraction. Active mixing, by pushing coffee filter plunger up and down, aided extraction. A mixing period of 3 min yielded maximum extraction; this time period was deemed suitable for an on-site workflow.</p><p>Following nutrient extraction, a simple-to-use readout system is required. For this, we developed colourimetric paper-based microfluidic devices; these are simply dipped into the decanted soil supernatant from the cafetiere and wick fluids based on capillary forces. Chemical reagents are pre-stored in reaction zones, created by patterning cellulose with wax barriers. Our devices contain multiple paper layers with different reagents; these are folded, laminated and holes cut for sample entry. Following the required incubation time, the developed colour is captured using a smartphone. This constitutes a portable detector, already available to envisaged end users, even in LMICs. We have previously developed an on-paper reaction for monitoring phosphates in fresh water in the mg L<sup>-1</sup> working range, with readout after an incubation period of 3 min. This method was adapted here to enable storage at ambient temperatures up to 1 week by incorporating additional acidic reagents. Further pad devices were developed in our group for colour-based readout of nitrate, involving a two-step reaction chemistry. Within a relatively short incubation period (≤8 min) a pink coloured was formed following reduction of nitrate to nitrite with zinc and subsequent reaction to form an azo-dye. This system achieved detection in the low mg L<sup>-1</sup> range. Moreover, a pad to monitor pH was developed, employing chlorophenol red indicator, with linear response achieved over the relevant pH 5-7 range.  </p><p>Our analysis workflow combines a simple-to-use cafetiere-based extraction method with paper microfluidic colour readout and smart-phone detector. This has the potential to enable farmers to monitor nutrients in soils on-site. Future work will aim at integrating multiple analytes into a single analysis card and to automate image analysis.</p><p>[1] <em>Europ. J. Agronomy</em>, 55, 42–52, <strong>2014.</strong></p><p>[2] <em>Nutr. Cycling Agroecosyst.,</em> 109, 77-102, <strong>2017.</strong></p><p>[3] Sens Actuators B, 30, 126855, <strong>2019.</strong></p>


2011 ◽  
Vol 94 (6) ◽  
pp. 1896-1905 ◽  
Author(s):  
James D Crutchfield ◽  
John H Grove

Abstract A reusable catalytic reductor consisting of 96 copperized-cadmium pins attached to a microplate lid was developed to simultaneously reduce nitrate (NO3–) to nitrite (NO2–) in all wells of a standard microplate. The resulting NO2– is analyzed colorimetrically by the Griess reaction using a microplate reader. Nitrate data from groundwater samples analyzed using the new device correlated well with data obtained by ion chromatography (r2 = 0.9959). Soil and plant tissue samples previously analyzed for NO3– in an interlaboratory validation study sponsored by the Soil Science Society of America were also analyzed using the new technique. For the soil sample set, the data are shown to correlate well with the other methods used (r2 = 0.9976). Plant data correlated less well, especially for samples containing low concentrations of NO3–. Reasons for these discrepancies are discussed, and new techniques to increase the accuracy of the analysis are explored. In addition, a method is presented for analyzing NO3– in physiological fluids (blood serum and urine) after matrix modification with Somogyi's reagent. A protocol for statistical validation of data when analyzing samples with complex matrixes is also established. The simplicity, adaptability, and low cost of the device indicate its potential for widespread application.


1994 ◽  
Vol 37 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Parthasarathi Bhattacharya ◽  
Satyahari Dey ◽  
Bimal Chandra Bhattacharyya

Author(s):  
Michael G. Mauk

Image capturing, processing, and analysis have numerous uses in solar cell research, device and process development and characterization, process control, and quality assurance and inspection. Solar cell image processing is expanding due to the increasing performance (resolution, sensitivity, spectral range) and low-cost of commercial CCD and infrared cameras. Methods and applications are discussed, with primary focus on monocrystalline and polycrystalline silicon solar cells using visible and infrared (thermography) wavelengths. The most prominent applications relate to mapping of minority carrier lifetime, shunts, and defects in solar cell wafers, in various stages of the manufacturing process. Other applications include measurements of surface texture and reflectivity, surface cleanliness, integrity of metallization lines, uniformity of coatings, and crystallographic texture and grain size. Image processing offers the capability to assess large-areas (> 100 cm2) with a non-contact, fast (~ 1 second), and modest cost. The challenge is to quantify and interpret the image data in order to better inform device design, process engineering, and quality control. Many promising solar cell technologies fail in the transition from laboratory to factory due to issues related to scale-up in area and manufacturing throughput. Image analysis provides an effective method to assess areal uniformity, device-to-device reproducibility, and defect densities. More integration of image analysis from research devices to field testing of modules will continue as the photovoltaics industry matures.


Agronomy ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 309 ◽  
Author(s):  
Isabelle Quilleré ◽  
Céline Dargel-Graffin ◽  
Peter J. Lea ◽  
Bertrand Hirel

The impact of nitrogen (N)-limiting conditions after silking on kernel yield (KY)-related traits and whole plant N management was investigated using fifteen maize lines representative of plant genetic diversity in Europe and America. A large level of genetic variability of these traits was observed in the different lines when post-silking fertilization of N was strongly reduced. Under such N-fertilization conditions, four different groups of lines were identified on the basis of KY and kernel N content. Although the pattern of N management, including N uptake and N use was variable in the four groups of lines, a number of them were able to maintain both a high yield and a high kernel N content by increasing shoot N remobilization. No obvious relationship between the genetic background of the lines and their mode of N management was found. When N was limiting after silking, N remobilization appeared to be a good predictive marker for identifying maize lines that were able to maintain a high yield and a high kernel N content irrespective of their female flowering date. The use of N remobilization as a trait to select maize genotypes adapted to low N input is discussed.


Author(s):  
Scott K. McGhee ◽  
A. M. Birk

This study assessed a low-cost, uncooled ferroelectric detector infrared camera for effusion cooling research. Advances in uncooled IR technology have led to applications previously limited to research-grade cameras. The imager operated in the 7–14μm waveband and sampled up to 30 frames per second. Thermal images were made of a matte-black flat plate, downstream of two cylindrical jets with injection angles of α = 30° and 90°, and L/D = 6. Thermocouple calibration was specific to each image. Statistical analysis and image analysis yielded detailed temperature maps with uncertainty as small as 0.9°C, a spatial resolution of 0.4mm, and a sensitivity of 0.1 °C. The system compared favorably with established infrared systems. Advantages include minimal instrumentation, on-line results, and a high degree of accuracy and resolution, at significantly reduced cost.


Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 808 ◽  
Author(s):  
Jean-Luc Baray ◽  
Asmaou Bah ◽  
Philippe Cacault ◽  
Karine Sellegri ◽  
Jean-Marc Pichon ◽  
...  

We present a simple algorithm that calculates the cloud occurrence frequency at an altitude site using automatic camera image analysis. This algorithm was applied at the puy de Dôme station (PUY, 1465 m. a.s.l., France) over 2013–2018. Cloud detection thresholds were determined by direct comparison with simultaneous in situ cloud probe measurements (particulate volume monitor (PVM) Gerber). The cloud occurrence frequency has a seasonal cycle, with higher values in winter (60%) compared to summer (24%). A cloud diurnal cycle is observed only in summer. Comparisons with the larger scale products from satellites and global model reanalysis are also presented. The NASA cloud-aerosol transport system (CATS) cloud fraction shows the same seasonal and diurnal variations and is, on average, 11% higher. Monthly variations of the ECMWF ERA-5 fraction of cloud cover are also highly correlated with the camera cloud occurrence frequency, but the values are 19% lower and up to 40% for some winter months. The METEOSAT-SEVIRI cloud occurrence frequency also follows the same seasonal cycle but with a much smaller decrease in summer. The all-sky imager cloud fraction (CF) presents larger variability than the camera cloud occurrence but also follows similar seasonal variations (67% in winter and 44% in summer). This automatic low-cost detection of cloud occurrence is of interest in characterizing altitude observation sites, especially those that are not yet equipped with microphysical instruments and can be deployed to other high-altitude sites equipped with cameras.


1999 ◽  
Author(s):  
Ignacio Blanquer ◽  
Vincente Hernandez ◽  
Javier Ramirez ◽  
Antonio M. Vidal ◽  
Mariano L. Alcaniz-Raya ◽  
...  

Sensors ◽  
2017 ◽  
Vol 17 (6) ◽  
pp. 1248 ◽  
Author(s):  
Fabrício Venâncio ◽  
Francisca Rosário ◽  
João Cajaiba

Sign in / Sign up

Export Citation Format

Share Document