A 64 × 128 3D-Stacked SPAD Image Sensor for Low-Light Imaging.

Low-light imaging capabilities are in urgent demand in many fields, such as security surveillance, night-time autonomous driving, wilderness rescue, and environmental monitoring. The excellent performance of SPAD devices gives them significant potential for applications in low-light imaging. This article presents a 64 (rows) × 128 (columns) SPAD image sensor designed for low-light imaging. The chip utilizes a three-dimensional stacking architecture and microlens technology, combined with compact gated pixel circuits designed with thick-gate MOS transistors, which further enhance the SPAD's photosensitivity. The configurable digital control circuit allows for the adjustment of exposure time, enabling the sensor to adapt to different lighting conditions. The chip exhibits very low dark noise levels, with an average DCR of 41.5 cps at 2.4 V excess bias voltage. Additionally, it employs a denoising algorithm specifically developed for the SPAD image sensor, achieving two-dimensional grayscale imaging under 6 × 10-4 lux illumination conditions, demonstrating excellent low-light imaging capabilities. The chip designed in this paper fully leverages the performance advantages of SPAD image sensors and holds promise for applications in various fields requiring low-light imaging capabilities.

Underwater Single-Photon 3D Reconstruction Algorithm Based on K-Nearest Neighbor.

The high sensitivity and picosecond time resolution of single-photon avalanche diodes (SPADs) can improve the operational range and imaging accuracy of underwater detection systems. When an underwater SPAD imaging system is used to detect targets, backward-scattering caused by particles in water often results in the poor quality of the reconstructed underwater image. Although methods such as simple pixel accumulation have been proven to be effective for time-photon histogram reconstruction, they perform unsatisfactorily in a highly scattering environment. Therefore, new reconstruction methods are necessary for underwater SPAD detection to obtain high-resolution images. In this paper, we propose an algorithm that reconstructs high-resolution depth profiles of underwater targets from a time-photon histogram by employing the K-nearest neighbor (KNN) to classify multiple targets and the background. The results contribute to the performance of pixel accumulation and depth estimation algorithms such as pixel cross-correlation and ManiPoP. We use public experimental data sets and underwater simulation data to verify the effectiveness of the proposed algorithm. The results of our algorithm show that the root mean square errors (RMSEs) of land targets and simulated underwater targets are reduced by 57.12% and 23.45%, respectively, achieving high-resolution single-photon depth profile reconstruction.

Prediction of wheat SPAD using integrated multispectral and support vector machines.

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69-0.79, RMSE was 2.30-12.94, and RE was 0.10%-1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value.

Fluorescence Multi-Detection Device Using a Lensless Matrix Addressable microLED Array.

A Point-of-Care system for molecular diagnosis (PoC-MD) is described, combining GaN and CMOS chips. The device is a micro-system for fluorescence measurements, capable of analyzing both intensity and lifetime. It consists of a hybrid micro-structure based on a 32 × 32 matrix addressable GaN microLED array, with square LEDs of 50 µm edge length and 100 µm pitch, with an underneath wire bonded custom chip integrating their drivers and placed face-to-face to an array of 16 × 16 single-photon avalanche diodes (SPADs) CMOS. This approach replaces instrumentation based on lasers, bulky optical components, and discrete electronics with a full hybrid micro-system, enabling measurements on 32 × 32 spots. The reported system is suitable for long lifetime (>10 ns) fluorophores with a limit of detection ~1/4 µM. Proof-of-concept measurements of streptavidin conjugate Qdot™ 605 and Amino PEG Qdot™ 705 are demonstrated, along with the device ability to detect both fluorophores in the same measurement.

Examining Chlorophyll Extraction Methods in Sesame Genotypes: Uncovering Leaf Coloration Effects and Anatomy Variations.

This study focuses on optimizing chlorophyll extraction techniques, in which leaf discs are cut from places on the leaf blade to enhance chlorophyll concentration in sesame (Sesamum indicum L.) leaves. Thirty sesame genotypes, categorized into light green (LG), middle green (MG), and deep green (DG) pigment groups based on leaf coloration, were selected from a larger pool of field-grown accessions. The investigation involved determining optimal Soil Plant Analysis Development (SPAD) value index measurements, quantifying pigment concentrations, exploring extraction solvents, and selecting suitable leaf disk positions. Significant variations in chlorophyll content were observed across genotypes, greenness categories, and leaf disk positions. The categorization of genotypes into DG, MG, and LG groups revealed a correlation between leaf appearance and chlorophyll content. The study highlighted a consistent relationship between carotenoids and chlorophyll, indicating their role in adaptation to warm environments. An examination of leaf disk positions revealed a significant chlorophyll gradient along the leaf blade, emphasizing the need for standardized protocols. Chlorophyll extraction experiments identified DMSO and 96% ethanol, particularly in those incubated for 10 min at 85 °C, as effective choices. This recommendation considers factors like cost-effectiveness, time efficiency, safety, and environmental regulations, ensuring consistent and simplified extraction processes. For higher chlorophyll extraction, focusing on leaf tips and the 75% localization along the sesame leaf blade is suggested, as this consistently yields increased chlorophyll content. Furthermore, our examination revealed significant anatomical variations in the internal structure of the mesophyll tissue leaves between deep green and light green sesame plants, primarily linked to chloroplast density and pigment-producing structures. Our findings, therefore, provide insightful knowledge of chlorophyll gradients and encourage the use of standardized protocols that enable researchers to refine their experimental designs for precise and comparable chlorophyll measurements. The recommended solvent choices ensure reliable outcomes in plant physiology, ecology, and environmental studies.

A Simulation Method for Underwater SPAD Depth Imaging Datasets.

In recent years, underwater imaging and vision technologies have received widespread attention, and the removal of the backward-scattering interference caused by impurities in the water has become a long-term research focus for scholars. With the advent of new single-photon imaging devices, single-photon avalanche diode (SPAD) devices, with high sensitivity and a high depth resolution, have become cutting-edge research tools in the field of underwater imaging. However, the high production costs and small array areas of SPAD devices make it very difficult to conduct underwater SPAD imaging experiments. To address this issue, we propose a fast and effective underwater SPAD data simulation method and develop a denoising network for the removal of backward-scattering interference in underwater SPAD images based on deep learning and simulated data. The experimental results show that the distribution difference between the simulated and real underwater SPAD data is very small. Moreover, the algorithm based on deep learning and simulated data for the removal of backward-scattering interference in underwater SPAD images demonstrates effectiveness in terms of both metrics and human observation. The model yields improvements in metrics such as the PSNR, SSIM, and entropy of 5.59 dB, 9.03%, and 0.84, respectively, demonstrating its superior performance.

Yield and Fruit Characteristics of Tomato Crops Grown with Mineral Macronutrients: Impact of Organo-Mineral Fertilizers through Foliar or Soil Applications.

The utilization of plant biostimulants has gained importance as a strategy by which to improve plant productivity and soil health. Two independent trials were conducted across two seasons (2021 and 2023) to evaluate the effects of foliar or soil applications of various commercial organo-mineral fertilizers (Futuroot®, Radicon® Amifort®) with biostimulant action that is exerted on yield and fruit characteristics of processing tomato crops (cv Taylor F1) that have been exposed to mineral macronutrients. These treatments were administered three times during the season: at the transplanting, pre-flowering and berry development stages. In the first trial, conducted in two fields characterized respectively by low and high fertility, foliar applications of Radicon®, which is based on humic acid and amino acids, increased the leaf greenness index SPAD compared with the control. Furthermore, the leaf green colour intensity (SPAD index), measured during the reproductive phases of the tomato exhibited a positive correlation (R2 = 0.726) with the marketable yield obtained. This increase in marketable yield was significant in the biostimulant treatment compared with the control in both soils, especially in the soil characterized by lower fertility (16.1%), when compared with the more fertile soil (6.8%). In the second trial, conducted in the low-fertility field mentioned above, soil applications of all biostimulants (Futuroot®, Radicon® and the combinations [Radicon® + Amifort-Plus®]) significantly increased the marketable yield by 27.8%, 13.5% and 27.7%, respectively, compared with the control. The most significant beneficial effects of both Futuroot® and [Radicon® + Amifort®] could be attributed to the combination of humic acids and auxins, cytokinins or microelements (Zn, Mn, MgO) present in the formulation of these products. Furthermore, the increase in marketable yield obtained when Radicon® was applied to leaves was higher (16.1%) than that observed with soil application (13.5%). In both trials, no relevant effects of biostimulant products were observed on most of the physicochemical characteristics of tomato fruits. In conclusion, the biostimulants based on humic acid and amino acids combined with chemical fertilizers tested in the present study and applied by fertigation were more effective in improving tomato yield, and therefore they can be recommended for efficient agricultural production.

Combining features selection strategy and features fusion strategy for SPAD estimation of winter wheat based on UAV multispectral imagery.

The Soil Plant Analysis Development (SPAD) is a vital index for evaluating crop nutritional status and serves as an essential parameter characterizing the reproductive growth status of winter wheat. Non-destructive and accurate monitorin3g of winter wheat SPAD plays a crucial role in guiding precise management of crop nutrition. In recent years, the spectral saturation problem occurring in the later stage of crop growth has become a major factor restricting the accuracy of SPAD estimation. Therefore, the purpose of this study is to use features selection strategy to optimize sensitive remote sensing information, combined with features fusion strategy to integrate multiple characteristic features, in order to improve the accuracy of estimating wheat SPAD. This study conducted field experiments of winter wheat with different varieties and nitrogen treatments, utilized UAV multispectral sensors to obtain canopy images of winter wheat during the heading, flowering, and late filling stages, extracted spectral features and texture features from multispectral images, and employed features selection strategy (Boruta and Recursive Feature Elimination) to prioritize sensitive remote sensing features. The features fusion strategy and the Support Vector Machine Regression algorithm are applied to construct the SPAD estimation model for winter wheat. The results showed that the spectral features of NIR band combined with other bands can fully capture the spectral differences of winter wheat SPAD during the reproductive growth stage, and texture features of the red and NIR band are more sensitive to SPAD. During the heading, flowering, and late filling stages, the stability and estimation accuracy of the SPAD model constructed using both features selection strategy and features fusion strategy are superior to models using only a single feature strategy or no strategy. The enhancement of model accuracy by this method becomes more significant, with the greatest improvement observed during the late filling stage, with R2 increasing by 0.092-0.202, root mean squared error (RMSE) decreasing by 0.076-4.916, and ratio of performance to deviation (RPD) increasing by 0.237-0.960. In conclusion, this method has excellent application potential in estimating SPAD during the later stages of crop growth, providing theoretical basis and technical support for precision nutrient management of field crops.

Corrigendum: Sensor-based precision nutrient and irrigation management enhances the physiological performance, water productivity, and yield of soybean under system of crop intensification.

[This corrects the article DOI: 10.3389/fpls.2023.1282217.].

A Method to Correct the Temporal Drift of Single-Photon Detectors Based on Asynchronous Quantum Ghost Imaging.

Single-photon detection and timing has attracted increasing interest in recent years due to their necessity in the field of quantum sensing and the advantages of single-quanta detection in the field of low-level light imaging. While simple bucket detectors are mature enough for commercial applications, more complex imaging detectors are still a field of research comprising mostly prototype-level detectors. A major problem in these detectors is the implementation of in-pixel timing circuitry, especially for two-dimensional imagers. One of the most promising approaches is the use of voltage-controlled ring resonators in every pixel. Each of these runs independently based on a voltage supplied by a global reference. However, this yields the problem that the supply voltage can change across the chip which, in turn, changes the period of the ring resonator. Due to additional parasitic effects, this problem can worsen with increasing measurement time, leading to drift in the timing information. We present here a method to identify and correct such temporal drifts in single-photon detectors based on asynchronous quantum ghost imaging. We also show the effect of this correction on recent quantum ghost imaging (QGI) measurement from our group.

A time-correlated single photon counting SPAD array camera with a bespoke data-processing algorithm for lightsheet fluorescence lifetime imaging (FLIM) and FLIM videos.

A wide-field microscope with epi-fluorescence and selective plane illumination was combined with a single-photon avalanche diode (SPAD) array camera to enable live-cell fluorescence lifetime imaging (FLIM) using time-correlated single-photon counting (TCSPC). The camera sensor comprised of 192 × 128 pixels, each integrating a single SPAD and a time-to-digital converter. Jointly, they produced a stream of single-photon images of photon arrival times with ≈ 38 ps accuracy. The photon arrival times were subject to systematic delays and nonlinearities, which were corrected by a Monte-Carlo algorithm. The SPAD camera was then applied to FLIM where histogramming the resulting photon arrival times in each pixel resulted in decays compatible with common data processing pipelines for fluorescence lifetime analysis. The capabilities of the TCSPC camera-based FLIM microscope were demonstrated by imaging living unicellular photosynthetic algae and artificial lipid vesicles. Epi-fluorescence illumination enabled rapid fluorescence lifetime imaging of living cells and selective-plane illumination enabled 3-dimensional FLIM of stationary samples.

Research on SPAD Estimation Model for Spring Wheat Booting Stage Based on Hyperspectral Analysis.

With the rapid progression of agricultural informatization technology, the methodologies of crop monitoring based on spectral technology are constantly upgraded. In order to carry out the efficient, precise and nondestructive detection of relative chlorophyll (SPAD) during the booting stage, we acquired hyperspectral reflectance data about spring wheat vertical distribution and adopted the fractional-order differential to transform the raw spectral data. After that, based on correlation analysis, fractional differential spectra and fractional differential spectral indices with strong correlation with SPAD were screened and fused. Then, the least-squares support vector machine (LSSSVM) and the least-squares support vector machine (SMA-LSSSVM) optimized on the slime mold algorithm were applied to construct the estimation models of SPAD, and the model accuracy was assessed to screen the optimal estimation models. The results showed that the 0.4 order fractional-order differential spectra had the highest correlation with SPAD, which was 9.3% higher than the maximum correlation coefficient of the original spectra; the constructed two-band differential spectral indices were more sensitive to SPAD than the single differential spectra, in which the correlation reached the highest level of 0.724. The SMA-LSSSVM model constructed based on the two-band fractional-order differential spectral indices was better than the single differential spectra and the integration of both, which realized the assessment of wheat SPAD.

Better estimation of evapotranspiration and transpiration using an improved modified Priestly-Taylor model based on a new parameter of leaf senescence in a rice field.

Evapotranspiration (ET) is at the heart of the global water, energy, and carbon cycles. As ET is difficult and expensive to measure, it is crucial to develop estimation models that can be widely applied. Currently, an improved Priestley-Taylor (PT) model considers soil moisture stress, temperature constraints, and leaf senescence; however, its parameter (fs) for simulating crop senescence is based on empirical values, making it difficult to apply to different varieties and complex external conditions and thus challenging to generalize. We improved the parameters fs in the original model based on the chlorophyll decomposition that accompanies crop senescence through easily observable SPAD values (Soil-Plant Analysis Development readings) in the field. We validated the improved model by obtaining ET of different rice varieties in 2022 and 2023 using the energy balance residual method at the Free Air Concentration Enrichment Experimental (FACE) Facility located in Yangzhou City, China. The results showed that the simulation of leaf senescence using SPAD values was feasible and could be extended to different varieties. The new model using improved leaf senescence parameter for estimating ET and transpiration (T) in three plots (2022 and 2023) exhibited slightly enhanced accuracy, particularly at the later stages of crop growth. Moreover, the higher the T/ET ratio of the cropland, the more significant the improvement. This new development enhances the ability of PT models to estimate ET and T using readily available field observations and provides some suggestions for wider application in the field for other crop species.

Hot-Carrier Damage in N-Channel EDMOS Used in Single Photon Avalanche Diode Cell through Quasi-Static Modeling.

A single photon avalanche diode (SPAD) cell using N-channel extended-drain metal oxide semiconductor (N-EDMOS) is tested for its hot-carrier damage (HCD) resistance. The stressing gate-voltage (VGS) dependence is compared to hot-hole (HH) injection, positive bias temperature (PBT) instability and off-mode (VGS = 0). The goal was to check an accurate device lifetime extraction using accelerated DC to AC stressing by applying the quasi-static (QS) lifetime technique. N-EDMOS device is devoted to 3D bonding with CMOS imagers obtained by an optimized process with an effective gate-length Leff = 0.25 µm and a SiO2 gate-oxide thickness Tox = 5 nm. The operating frequency is 10 MHz at maximum supply voltage VDDmax = 5.5 V. TCAD simulations are used to determine the real voltage and timing configurations for the device in a mixed structure of the SPAD cell. AC device lifetime is obtained using worst-case DC accelerating degradation, which is transferred by QS technique to the AC waveforms applied to N-EDMOS device. This allows us to accurately obtain the AC device lifetime as a function of the delay and load for a fixed pulse shape. It shows the predominance of the high energy hot-carriers involved in the first substrate current peak during transients.

Organic fertilizer type and dose affect growth, morphological and physiological parameters, and mineral nutrition of watermelon seedlings.

Background: Organic agriculture has grown rapidly in recent years due to its environmental friendliness, sustainability, and improved farm profitability. Transplants are commonly used for fruits and vegetables to achieve consistent quality, uniformity, and easy field spacing control. The efficacy and optimal amounts of fertilizers for organic transplant production need to be investigated. Methods: The effects of three organic fertilizers (Sustane 4-6-4, Nature Safe 7-7-7, and Dramatic 2-4-1) and one conventional fertilizer Peters Professional 20-20-20 (Conventional) with four doses (nitrogen (N) content was matched among fertilizers in each level, as 0.14 g/L, 0.28 g/L, 0.56 g/L, and 0.84 g/L N, respectively) on watermelon seedlings were compared in this study. Results: The results showed that all organic fertilizer treatments were not significantly different from the Conventional group in terms of watermelon germination. The only exception was the highest dose of Sustane 4-6-4 (0.84 g/L N) which decreased the germination rate and relative emergence index. Generally, growth index, shoot fresh and dry weights, true leaf number, and stem diameter increased as the amount of N increased within each fertilizer type. The best shoot growth was observed in the highest doses of Conventional and Dramatic 2-4-1 treatments (0.84 g/L N). However, Dramatic 2-4-1 treatments resulted in the lowest root growth when compared to other fertilizers at the same N dose. The second highest fertilization dose (0.56 g/L N) of Sustane 4-6-4 had the best root growth according to root fresh weight, root volume, root area, total root length, as well as the numbers of root tip and crossing when compared to other treatments. For seedlings, a well-developed root system can ensure a good seedling establishment and high survival rate under stressful field conditions after transplanting. Thus, Sustane 4-6-4 at 14 g/L (0.56 g/L N) is recommended to produce high-quality organic watermelon seedlings among the treatments applied in this study.

Effects of biochar treatments on the elemental composition of tobacco (Nicotiana tabacum L.) leaves based on the priming period.

This study determined the effects of different doses of biochars (B) on Virginia tobacco (Nicotiana tabacum L.) cultivar, on first and second harvest dependent change in plant nutrients (N, P, K, Ca, Mg, Cl, Zn, Fe, Mn, Cu, and B), leaf color parameters (L*, a*, and b*), chlorophyll value (SPAD), electrolyte leakage (EL), crude ash, number of leaves, and plant height. Pot experiments were conducted with biochar treatments of 10 tons ha-1 (B1), 20 tons ha-1 (B2), 40 tons ha-1 (B3), and 80 tons ha-1 (B4). Tobacco leaf macroelement (N, P, K, Ca, and Mg) levels increased with increasing biochar doses. The highest values were obtained for B4 treatments (80 tons ha-1) and the lowest for control (B0) treatments. Microelements (Fe, Zn, Mn, and B) exhibited a non linear change, while Cl and Cu exhibited a linear change. Color parameters (L*, a*, and b*) for the first and second priming showed the highest L* and b* values for B2 and B3 treatments, respectively, and the highest a* values for the B2 treatment. Leaf SPAD values increased with increasing biochar doses; further, the obtained SPAD values were ordered as B4 > B3 > B2 > B1 > B0. Leaf electrolyte leakage values were 25.90 %-37.25 % in the first priming and 26.90 %-40.59 % in the second priming. For both the primings, the highest crude ash values (21.94 % and 19.05 %) were observed for the B4 treatments, whereas the lowest values (17.89 % and 17.01 %) were observed for the B0 treatments. the tallest plant height (121.9 cm) and the highest number of leaves (45.3) were determined in B4 applications. Overall, considering the nutrition and quality of tobacco, B2 application is recommended.

The implementation of the SPAD-502 Chlorophyll meter for the quantification of nitrogen content in Arabica coffee leaves.

The utilization of a non-destructive SPAD-502 chlorophyll meter, which enables the measurement of nitrogen status in plant leaves, has gained popularity in agronomic crops. Its application to horticultural crops like coffee remains relatively uncommon. The device provides quick and real-time measurements, helping to provide on-time nitrogen fertilizer to coffee plants before deficiency signs occur. Coffee leaves are characterized by thick and waxy leaves, together with many layers of tree crown. Therefore, the objective of this study was to develop a method for measuring nitrogen levels in coffee plants using the SPAD-502 Chlorophyll meter for an appropriate nitrogen fertilizer application rate in Arabica coffee plants. •Coffee trees were separated into upper, middle and lower levels. Data on SPAD values and total nitrogen were analyzed.•Pearson Correlation Coefficient (R), Coefficient of Determination (R2) and linear regression were calculated for different three levels of both SPAD-502 and total nitrogen values.•The results revealed a strong correlation (R2 = 0.63) between the SPAD readings of coffee leaves obtained from the upper canopy and their nitrogen content. These findings can provide a good concept of which coffee crown level will be a better part for measuring N content using a SPAD-502 Chlorophyll meter.

First-Arrival Differential Counting for SPAD Array Design.

We present a novel architecture for the design of single-photon detecting arrays that captures relative intensity or timing information from a scene, rather than absolute. The proposed method for capturing relative information between pixels or groups of pixels requires very little circuitry, and thus allows for a significantly higher pixel packing factor than is possible with per-pixel TDC approaches. The inherently compressive nature of the differential measurements also reduces data throughput and lends itself to physical implementations of compressed sensing, such as Haar wavelets. We demonstrate this technique for HDR imaging and LiDAR, and describe possible future applications.

Analysis of Cadmium Contamination in Lettuce (Lactuca sativa L.) Using Visible-Near Infrared Reflectance Spectroscopy.

In order to rapidly and accurately monitor cadmium contamination in lettuce and understand the growth conditions of lettuce under cadmium pollution, lettuce is used as the test material. Under different concentrations of cadmium stress and at different growth stages, relative chlorophyll content of lettuce leaves, the cadmium content in the leaves, and the visible-near infrared reflectance spectra are detected and analyzed. An inversion model of the cadmium content and relative chlorophyll content in the lettuce leaves is established. The results indicate that cadmium concentrations of 1 mg/kg and 5 mg/kg promote relative chlorophyll content, while concentrations of 10 mg/kg and 20 mg/kg inhibit relative chlorophyll content. The cadmium content in the leaves increases with increasing cadmium concentrations. Cadmium stress caused a "blue shift" in the red edge position only during the mature period, while the red valley position underwent a "blue shift" during the seedling and growth periods and a "red shift" during the mature period. The green peak position exhibited a "blue shift". After model validation, it was found that the model constructed using the ratio of red edge area to yellow edge area and the normalized values of red edge area and yellow edge area effectively estimated the cadmium content in lettuce leaves. The model established using the normalized vegetation index of the red edge and the ratio of the peak green value to red shoulder amplitude can effectively estimate the relative chlorophyll content in lettuce leaves. This study demonstrates that the visible-near infrared spectroscopy technique holds great potential for monitoring cadmium contamination and estimating chlorophyll content in lettuce.

N-Channel MOSFET Reliability Issue Induced by Visible/Near-Infrared Photons in Image Sensors.

Image sensors such as single-photon avalanched diode (SPAD) arrays typically adopt in-pixel quenching and readout circuits, and the under-illumination first-stage readout circuits often employs high-threshold input/output (I/O) or thick-oxide metal-oxide-semiconductor field-effect transistors (MOSFETs). We have observed reliability issues with high-threshold n-channel MOSFETs when they are exposed to strong visible light. The specific stress conditions have been applied to observe the drain current (Id) variations as a function of gate voltage. The experimental results indicate that photo-induced hot electrons generate interface trap states, leading to Id degradation including increased off-state current (Ioff) and decreased on-state current (Ion). The increased Ioff further activates parasitic bipolar junction transistors (BJT). This reliability issue can be avoided by forming an inversion layer in the channel under appropriate bias conditions or by reducing the incident photon energy.