Color Sensor Research Articles

Automated Conveyor System of Sorting and Grading for Red Chili Pepper (Capsicum annum L.) using Image Processing and Artificial Neural Network

This research aims to design an automatic sorting and grading tool driven by color sensor processed through image processing and artificial neural networks (ANN). The research stage consists of data collection in a Mini Studio, image processing using ImageJ, and image classification with ANN. The automatic sorting process begins with items entering the belt, where they are processed in four phases: (1) separating good and rejects chili, (2) separating red from green chili, (3) distinguishing large and small red peppers, and (4) separating large and small green peppers. Automatic sorting and grading were based on image data processed using ANN. The best activation function was tansig-logsig-purelin with MAPE 1.220, RMSE 0.010, and R² = 1 during training. During testing, the MAPE 0.158, RMSE 1.790, and R² = 0.963. The criteria produced grade 1 (red, 10-15 cm), grade 2 (green, 10-15 cm), grade 3 (red, 5-9.99 cm), and reject grade. The quality of large red chilies is used as a reference for market pricing: grade 1 (IDR 60,000/kg), grade 2 (IDR 40,000/kg), and grade 3 (IDR 25.000 – 35,000). Assessing quality based on color with an automatic conveyor can reduce sorting and grading time by 70% compared to conventional methods. Keywords: ANN, Color, Grading, Image Processing, Sorting.

Learned Multi-aperture Color-coded Optics for Snapshot Hyperspectral Imaging

Learned optics, which incorporate lightweight diffractive optics, coded-aperture modulation, and specialized image-processing neural networks, have recently garnered attention in the field of snapshot hyperspectral imaging (HSI). While conventional methods typically rely on a single lens element paired with an off-the-shelf color sensor, these setups, despite their widespread availability, present inherent limitations. First, the Bayer sensor's spectral response curves are not optimized for HSI applications, limiting spectral fidelity of the reconstruction. Second, single lens designs rely on a single diffractive optical element (DOE) to simultaneously encode spectral information and maintain spatial resolution across all wavelengths, which constrains spectral encoding capabilities. This work investigates a multi-channel lens array combined with aperture-wise color filters, all co-optimized alongside an image reconstruction network. This configuration enables independent spatial encoding and spectral response for each channel, improving optical encoding across both spatial and spectral dimensions. Specifically, we validate that the method achieves over a 5dB improvement in PSNR for spectral reconstruction compared to existing single-diffractive lens and coded-aperture techniques. Experimental validation further confirmed that the method is capable of recovering up to 31 spectral bands within the 429--700 nm range in diverse indoor and outdoor environments.

A Tomato Sorting Automation Prototype Based on Color

Abstract—The process of sorting tomatoes can be done using visual methods by paying attention to color. The purpose of this research is to improve the process of sorting tomatoes based on color in distinguishing ripe tomatoes and immature tomatoes. Streamline the time of sorting tomato fruit in order to avoid losses due to spoilage. This research method is with a sample of tomato fruit taken RGB value through TCS 3200 color sensor according to the level of maturity. After the RGB value is obtained, it will be processed into the Arduino Uno to obtain maturity information through the rules that have been made and sorted using a servo motor. The results of this study indicate that a good condition for detecting tomato fruit is with a closer distance to the fruit with a dark background. This is because there is no excess light reflection so that the TCS sensor can take RGB values well and reduce the occurrence of misreading of ripeness information in the sorting process. Keywords— Tomato, Sensor TCS 3200, Arduino uno, Motor Servo.

Chromogenic Chemosensor for Simultaneous Detection of PO4 3- and CO3 2- Anions in Organo-Aqueous Solutions: Application in Arduino Based Electronic Color Sensor Device and Logic Gate.

Three new chromogenic receptors have been synthesized with the primary objective of facilitating the selective recognition of PO4 3-and CO3 2- ions in an organo-aqueous medium. R1 and R2 exhibit an extraordinary detection limit aligning with both EPA and WHO guidelines. R1 shows LOD of 0.135 ppm for PO4 3- and 0.175 ppm for CO3 2-, while R2 sets forth a LOD of 0.427 ppm for PO4 3- and 0.729 ppm for CO3 2-. The binding mechanism involves intramolecular charge transfer (ICT) band are substantiated by comprehensive studies that include UV-Vis titration, 1H-NMR titration, DFT studies and electrochemical studies. Chemosensors were employed in the formulation of logic gate, the fabrication of a paper strip test kit and its application in RGB color sensor device.

RANCANG BANGUN PENDETEKSI DEHIDRASI MANUSIA BERDASARKAN WARNA URINE BERBASIS INTERNET OF THINGS (IOT)

In the current technological era, the Internet of Things (IoT) provides creative fixes for numerous health problems. The purpose of this research is to design and construct a urine color analysis system that uses the Internet of Things to identify human dehydration. Urine color is precisely measured and analyzed by the system using color and pH sensors. Data is then sent over an internet connection to a cloud-based platform.The urine color analysis results will be compared to accepted medical standards as part of the processing of the gathered data to ascertain the user's bodily hydration level. This system has a Blynk app-based user interface that offers proper hydration recommendations and real-time information about the user's level of hydration. It is anticipated that by putting this system in place, users will be able to efficiently check their level of hydration and take precautions to avoid being dehydrated. This research offers a more approachable and cost-effective method of managing one's own health in addition to aiding in the development of Internet of Things-based health technology.

Development of an ESP32 Microcontroller-based Colorimeter with an Android App for the Verification of Roasting Degree of Coffee Beans

A lo w-cost and portable colorimeter was developed using an ESP32 microcontroller and a TCS34725 color sensor to monitor the degree of coffee roast, crucial for maintaining flavor consistency and controlling product quality across different batches. The colorimeter detected color recognition resulting in RGB color intensity values, which could be displayed on the device’s TFT LCD touchscreen. Additionally, colorimetric data was transmitted in real-time via WiFi and stored in a MySQL database using an Android app created with the MIT App Inventor platform. The colorimeter was powered by a rechargeable lithium phosphate battery. The consistency of coffee roasting was ensured by self-identifying the standard RGB values of the roasted coffee beans at five degrees (light, light-medium, medium, medium-dark, and dark) with the app. The darker the color of the roasted coffee, the lower the RGB values were gained. The color detection was highly precise, with a relative standard deviation of less than 5%.

Real time monitoring of heavy metal adulteration in biodiesel using Arduino UNO platform@A promising multi-purpose stimuli-responsive azomethine based chemoreceptor for hierarchical tri-ionic sensing

The presence of metallic adulteration even in very trace level may lead to deleterious impact on the biodiesel quality and ultimately may be responsible for the dropping down of system efficiency, which necessitates the trace level recognition of heavy metal adulteration from biodiesel. In this context, herein using an azomethine functionalized chromogenic chemoreceptor, 1-((E)-(4-hydroxyphenylimino) methyl) napthalen-2-ol (HMN) has been reported for the selective chemodosimetric recognition of Cu2+ with a lower detection threshold of 7.8 ppb via distinct chromogenic variation of HMN. In addition to this, it has also exhibited selective and reversible naked eye chromogenic sensing behaviour towards F− (LOD=160 ppb) and Al3+ (LOD=48 ppb) at very trace level, which is quite lower than the WHO permissible limit. Distinct chromogenic recognition of F− by HMN proceeds via strong intermolecular hydrogen bonding mediated improved intramolecular charge transfer. The spectroscopic response of HMN in alternate presence and absence of the targeted analytes made it suitable to formulate AND-NOT-XNOR-NAND-OR gate based ‘Castle-like’ complicated logic circuitry. In-vitro cell imaging study using A549, human lung carcinoma cell line attests intracellular recognition capability of HMN, demonstrating its effectual bio-medicinal applications. Interestingly, inspired by the capability of HMN towards recognition of copper from biodiesel specimen, an RGB-assisted device comprised of TCS color sensor and an Arduino UNO 8-bit microcontroller has been developed for real-time quantitative analysis of the biodiesel adulteration. Going one step further, utilization of lab-on-a-box based prototype to monitor the concentration-dependent chromogenic fluctuation via RGB analysis is undoubtedly beneficial for the determination of copper adulteration in biodiesel sample. The presently developed chemoreceptor can thus be regarded as a valuable addition in the field of supramolecular chemistry as well as a significant initiative towards regular monitoring of the biodiesel quality control parameters as a part of sustainable environment.

Pressure Visualization and Quantification Photonic Skin Based on Flexible Optical Fiber Combiner

AbstractThe integration of pressure quantification and visualization enhances pressure perception, accuracy, and efficiency. Current solutions require improvements in quantization accuracy, structural simplicity, and integration. We proposed a novel photonic skin comprising a 3 × 1 flexible optical fiber combiner, integrating red, green, and blue light emitting diode (LED) chips through three flexible optical fibers. Under pressure, changes in the optical fibers' transmission loss alter the output light intensity ratio, thus inducing a color shift at the combiner's output. This visible change can be precisely quantified using a color sensor chip. Performance metrics include sensing range up to 33N, sensitivity between 0.04 and 0.24 dB N−1, detection limit below 0.08 N, response time of 500 ms, recovery time of 400 ms, and durability exceeding 2000 cycles. A compact flexible circuit board manages light source driving, data acquisition, and wireless communication, forming a wearable photonic skin system. This system enables visual recognition and quantitative measurement of pressure across diverse scenarios, including different tactile modes, multi‐position pressure, finger bending, and neck movement. For oral occlusion force detection, the spatial separation of the sensing and visualization areas enables the system to simultaneously provide accurate measurements and intuitive visual assessment.

Intelligent Radiometric Calibration System for Ocean Color Satellite Sensors

Abstract To achieve the integration of multiple ocean color (OC) sensors’ radiometric calibration tasks into a single system, we have developed an intelligent on-orbit radiometric calibration system called the Generalized Radiometric Calibration Entity for Ocean Color (Grace-OC). The system features real-time data downloading capabilities and integrates three calibration methods: onboard calibration, system vicarious calibration and cross calibration, enabling intelligent selection of on-orbit radiometric calibration methods tailored to the calibration sensors. Compared to other calibration systems, we have improved the universality and efficiency of the system by establishing high-spectral aerosols and Rayleigh lookup tables (LUTs) which are verified consistency through a comparative analysis with operational LUTs releasing by National Aeronautics and Space Administration (NASA) in this paper. Building upon this foundation, we have integrated a comprehensive analysis function for calibration coefficients to automatically construct degradation models of the radiometric measurement performance, and to achieve mutual verification between different calibration methods. We applied Grace-OC to HY1C/D and verified the feasibility of the intelligent selection calibration methods and the stability of the calibration system, achieving a calibration accuracy of up to 0.5%. Simultaneously, the precision of degradation models of the radiometric measurement performance is confirmed through Grace-OC, and the on-orbit radiometric calibration task was ultimately completed within 6 minutes for each per scene. Based on the above applications, Grace-OC has demonstrated its universality for various OC sensors, as well as the stability of on-orbit radiometric calibration tasks and the efficiency of operational speed.

Design of a Smart Donation Box Based on IoT

This research, entitled "IoT-based Intelligent Charity Box Design", aims to develop a charity box system that utilizes the Internet of Things (Iot) technology to enhance public participation in charity. In this context, the charity box not only serves as a container for storing donations, but is also equipped with features that can automatically monitor and calculate the amount of money inserted. The system uses the Wemos D1 Mini as a microcontroller connected to the Internet, allowing users to access data in real time through a website. In addition, this smart charity box is equipped with a PIR sensor that detects motion and triggers sound on the DFPlayer, as well as a TCS3200 color sensor that counts the paper money entered. Thus, the research not only offers technological solutions, but also seeks to remind the public of the importance of charity in a more interactive and efficient way. The results of this research are expected to benefit the management of charity funds and raise social awareness in the community.

Phytoplankton bloom detection and trends in satellite inherent optical properties over the last two decades in a heterogeneous Patagonian coastal system

ABSTRACT To effectively address ecosystem health risks, it is crucial to use detection methods that efficiently cover vast areas with good spatial resolution. These methods should enhance understanding of how phytoplankton blooms might evolve due to climate change. Satellite Ocean Color sensors are advantageous for detecting and monitoring phytoplankton blooms over time. This study uses the Inherent Optical Properties (IOP) index, which considers light absorption by phytoplankton (Ab_phy) and by detritus plus colored dissolved organic matter (Ab_adg), to detect phytoplankton blooms in six subareas within the San Matías Gulf (SMG; Patagonia, Argentina). The findings reveal a significant increase in bloom alerts over the last 20 years in the northwestern and southwestern subareas. Temporal changes in chlorophyll a (Chla) and sea surface temperature (SST) were observed, both showing an increase over the studied period. Environmental features like the diffusive attenuation coefficient (Kd_490) and Ab_phy also showed positive trends in four of the six subareas. The positive trends in SST and Kd_490 suggest a potential reduction in the euphotic zone depth. Additionally, the presence of phytoplankton biomass, indicated by Chla and Ab_phy, is linked to reduced light penetration in the water column due to absorption by the cells and self-shading. A decrease in Ab_adg was observed, while photosynthetically active radiation (PAR) showed no significant trend over the last two decades. These patterns could significantly impact the frequency and timing of phytoplankton blooms, altering their community composition and phenology. Such changes have profound implications for the entire marine food web and the ecosystem services within the SMG. The results underscore the importance of incorporating optical data for monitoring phytoplankton blooms across multiple areas.

Self-Powered FTO/CdSe/Bi2Se3 Photodetector with Bipolar Photoresponse Characteristics.

Self-powered photodetectors with bipolar photoresponse characteristics are expected to play a critical role in the field of secure optical communication, artificial neuromorphic systems, and intelligent color sensors. In this work, asymmetric heterojunction devices exhibiting wavelength-dependent bipolar photoresponse with a structure of Glass/FTO/CdSe/Bi2Se3/Au were fabricated. Under a short wavelength light irradiation, the top CdSe absorber generates a high carrier concentration; the excited carriers are quickly separated by the built-in electric field induced by the FTO/CdSe diode, resulting in a negative photocurrent. For light with wavelengths beyond the CdSe absorption edge, it is absorbed by the bottom Bi2Se3 absorber, and a positive photocurrent can be observed. Therefore, based on the bandgap difference between the top CdSe absorber and the bottom Bi2Se3 absorber, combined with the photogenerated carriers separated by asymmetric back-to-back diode, a wavelength-dependent bipolar response is realized. In this work, by employing this structure, the responsivities of -33.3 and 0.3 mA/W were achieved under the illumination of 405 and 830 nm, respectively. This work provides important indications in the preparation and performance optimization for wavelength-dependent bipolar photodetectors.

Fraud-proof methylcellulose-based fish freshness indicator: Reversibility in halochromic sensing of basic volatiles is tailored by ionic strength

Food from animal sources (e.g., fish) represents the food group most likely to disseminate diseases to humans. To prevent food contamination and foodborne illnesses, intelligent packaging has been developed to monitor fish freshness by real-time tracking their physicochemical attributes and informing consumers about their conservation state. In this context, we investigated the influence of ionic strength (IS) provided by CaCl2 on the chromatic response of anthocyanin açai extracts incorporated into methylcellulose (MC) within hydrocolloid-based colorimetric sensors for monitoring the freshness of Lambari fish. The color sensitivity of the sensors was modulated by IS in the presence of NH3 volatile and/or TVB-N. Increasing IS led to a plasticizing effect in the MC matrix, which influenced the chromatic properties of anthocyanin in the presence of NH3 and/or TVB-N. The perception of distinct colors by untrained eyes improved from 10 min with the control sensor to 2.5 min for sensors with IS >50 mM. Adjusting the IS to 500 mM with LiCl, CaCl2, or MgCl2 resulted in gray-green, blue, or moss-green colors, respectively, diverging from the control sensor's color (pink and gray) after 10 min of ammonia exposure, confirming salt-induced copigmentation. Color irreversibility in the sensors was achieved when the IS exceeded 250 mM. Through principal component analysis, we statistically validate the efficacy of the sensor in assessing the freshness of Lambari fish. The sensor maintained its color-change capability even after 60 d of storage and was able to classify Lambari fish freshness according to Brazilian and European standards. This study elucidates the interrelation between the structures and properties of natural compounds such as MC, anthocyanin, and CaCl2, providing a method to control the chromatic properties of sensors intended to monitor food quality, safety, and shelf-life.

Harmful Algal Blooms on the Portuguese coast: Cross-checking events with remote sensing ocean colour data for coastal management

Phytoplankton plays a vital role in marine ecosystems, serving as a primary food source for a diverse array of organisms, including commercially important bivalves, crustaceans, and fish. However, in some situations, the proliferation of algae can cause serious economic losses for aquaculture, fishing, and tourism and have major environmental and human health impacts. Increases in the occurrence of toxic phytoplankton blooms in Iberian waters have been reported. Earth Observation (EO) can provide important information about the spatial and temporal distribution and the destination of blooms, with scales not available for conventional monitoring techniques. The present work aims to take advantage of public databases (Harmful Algae Event Database (HAEDAT)) to relate ocean colour data, also publicly available, (Copernicus Marine Environmental Monitoring Service (CMEMS)) with the detection of the occurrence of harmful algal blooms (HABs). From the analysis of the HAEDAT database, it was possible to observe that in Portugal, from 1987 to 2020, there were 669 HABs events, with Diarrhetic Intoxication by Shellfish (DSP) syndrome. The images were extracted from multiple ocean colour sensors (2017–2020) for periods coinciding with DSP HABs events in recent years to identify patterns in the development of HAB toxins and to assist in coastal management. Having in account the HAB events analysed (12), was observed a weak but significant correlation between the datasets when the comparison was between the biotoxin concentration and its 14th day precedent Chlorophyll a (Chl a) concentration (rSpearman=0.15). These results show how EO data relate to regular bivalve toxin monitoring programs on the Portuguese coast and are useful for future integration in modelling tools. Other than being useful for coastal water quality assessment and management, these results also reinforce the importance of maintaining existing monitoring programs on a regular basis, especially as some types of HABs may not be easily distinguishable by EO.

IoT-based Smart Piggy Bank Design Implementation Using RFID and Telegram Notification

Saving is one of the most important things in financial management. Saving is beneficial for the long term for life. In the conventional way, people can save in a closed container or generally use an object called a piggy bank. However, there are still many shortcomings of the current conventional piggy bank, such as having to be disassembled to take the money and it is difficult to monitor the amount of savings in it so that it can only be used once. With the help of technology, these conventional tools can be used better and more efficiently. This smart piggy bank can be integrated with the Telegram when money is inserted so that it becomes more monitored in saving. The money inserted is detected by infrared sensors and color sensors which are then accumulated and sent via Telegram. Previously, there has been similar research in using sensors to detect money and send notifications based on the Internet of Things. This research aims to develop the existing research by integrating some of its features. Testing was conducted using the Black Box method, focusing on the functionality of the device. As a result, the money inserted into the piggy bank can be accumulated properly and monitored via Telegram with a calculation according to the amount of money inserted and can be used by many people because it uses an RFID card that contains user data and savings so that it becomes more efficient and recorded.

Integrating colorimetry with surface sensitive transducers: Advancing molecular diagnostics in biofluids

Colorimetric sensors are preferred for visually detecting target analytes, but achieving ultra-low detection capabilities for food analysis, environmental samples, and molecular diagnostics is challenging. In this study, we interfaced a purpald-based formaldehyde color sensor (as a model probe reaction) with a surface plasmon gold microarray imaging chip. Such hyphenated surface-sensitive signal-amplifying techniques enabled ultra-low detection in biofluids with a linear range of 10−5 – 0.5 ppm compared to the spectrophotometric narrower linear range of 0.01–1 ppm. The detection limit of 86×10−6 ppm from the hyphenated sensing is 140-fold lower than the detection limit from the spectrophotometric method alone (12×10−3 ppm). The absorbance maximum of the purpald-formaldehyde adduct was 553 nm, with no notable tail overlap between the adduct absorbance band beyond 700 nm and the fixed angle source incident wavelength of 800 nm from the surface plasmon instrument. Hence, the possible adduct thiol-surface plasmon gold surface interaction, affinity, and the higher mass and refractive index changes of the adduct are likely causes of the observed signal amplification. We achieved a formaldehyde sample recovery of 92 % from a diluted serum (a minimally invasive assay method), which was comparable to the results in a buffer solution. Further, we extended to demonstrate in diluted urine sample matrices to be noninvasive bioanalysis and determined the interference from urea that could also form a purpald adduct like formaldehyde. In conclusion, coupling a surface-sensitive transducer with less sensitive colorimetric reactions is promising for molecular diagnostics in real samples and can be broadly extended to any other desired molecular targets and sample matrices.

Building an Educational Automated Mechatronics-Based Sorting System

This paper discusses the development of an automated sorting machine designed as a comprehensive mechatronics educational project. The project integrates mechanical and electrical design, incorporating a robot arm, a microcontroller, sensors, and actuators. The sorting machine uses color identification to sort wooden blocks of three different colors. The blocks are stacked and dropped onto a conveyor belt by a hopper system that employs a solenoid actuator and a servo to release one block at a time at specific intervals. As the belt runs continuously, each block passes under a color sensor, which monitors the color and signals one of three servo-powered mechanical arms to guide the block into the appropriate chute. Each chute is equipped with a capacitive proximity sensor that sends a voltage signal to the robot controller, queuing commands for the robot to pick up the blocks from the bottom of each chute and return them to the hopper to form a continuously running sorting system. This paper details the design and integration of the system’s various elements and the development of the control software. The designed system can drop blocks every 8.05 s, sort each block within 5 s of being sensed, and return them to the sorting system every 12 s. It has a color-sensing accuracy of 97%, with a failure rate of around 7%. The system achieved quick and reliable sorting using various low-cost, accessible, and open-source parts. The project exemplifies a cost-effective solution suitable for mechatronics education, demonstrating the numerous challenges involved in developing automated sorting systems.

Colorimetric sensor nanoarchitectonics for trace Pb2+ ions detection by porous fungus-like CoS nanozyme

The heavy metal lead (Pb) holds significant importance in the manufacturing industry due to its extensive range of applications. However, its high toxicity poses a serious risk to both environment and human health. Consequently, on-site portable analysis methods have been developed to detect Pb2+, which is advantageous for obtaining timely information regarding environmental pollution. In this study, a fungal-like porous CoS (FP CoS) was discovered to selectively recognize, adsorb, and detect Pb2+. FP CoS exhibited rapid kinetics (reducing from 8.56 mg∙L–1 to 69 µg∙L–1 within 30 min) as well as exceptional adsorption capacity of 88.14 mg∙g−1 for Pb2+. Benefiting from the selective enrichment of Pb2+, the peroxidase-like activity of FP CoS nanoenzyme was further enhanced, enabling colorimetric detection of Pb2+ with a detection limit of 14 ng∙L–1, surpassing numerous reported materials. When applied to environmental samples spiked with 0–100 μg∙L–1 Pb2+, the combination of FP CoS nanosensor and a portable RGB color sensor yielded an impressive recovery percentage of 112 %. Based on these results, the FP CoS nanosensor not only provides a rapid and visually discernible colorimetric approach for trace and ultra-trace Pb2+ but also serves as a sensitive sensor for detecting Pb2+ in various scenarios.

Development of TCS3200 Color Sensor Based on Arduino Uno and Its Application in Determining Borax Levels in Food

Development of TCS3200 Color Sensor Based on Arduino Uno and Its Application in Determining Borax Levels in Food

Proximal sensor characterization of Haitian agricultural soils: A case study in the Central Plateau

Optimized agronomic production is vital to life and livelihood in Haiti. As such, rapid, low-cost soil characterization may inform specific decision making for improved crop production. Ahead of a larger soil characterization campaign (120,000 points) in Eastern Haiti, this study evaluated the use of two proximal sensors (portable X-ray fluorescence – pXRF; NixPro color sensor) at farms of Association Zanmi Agrikol (AZA) for soil characterization and evaluation of spatial variability of soil properties. Analysis of 166 surface soil samples (0–5 cm) collected in three different areas revealed that similar inter-elemental associations reported in other countries remain applicable in Haiti; weak, yet significant relationships between Al, K, and Fe contents and color parameters (L*, A*, B*) were observed. Considerable variability in soil morphology and chemical properties exist even across short distances, underscoring the need for high density sampling schemes. Soil pH (observed up to 8.4) likely imposes restrictions on the bioavailability of certain micronutrients; soil salinity was low (not agronomically limiting) across the study areas, and reflective of excessive drainage. Soil profile characterization identified one Eutrudept and one Quartzipsamment; both used for agronomic production. The proliferation of skeletal coarse fragments (e.g., cobbles, stones) and sandy matrix with depth emphasize the need for periodic supplemental irrigation and fertilization via either soil amendments (e.g., compost) or commercial fertilizers as water holding capacity and nutrient storage (e.g., clays, organic matter) are likely to be limited. Use of the NixPro color sensor showed differences in topsoil color likely reflective of differential soil organic carbon levels. The proximal sensors applied herein represent their first such use for agronomic management in Haiti and have shown considerable promise for additional study and application.