Making Sense of Light: The Use of Optical Spectroscopy Techniques in Plant Sciences and Agriculture

Design and development of a miniature mid-infrared linear variable filter based spectrometer for environmental sensing

Miniaturized, energy-efficient and application-specific spectral sensing systems promise to be a highly sought-after technology in the coming years, with potential applications in areas such as: distributed sensor systems, IoT devices, mobile autonomous platforms, and many others. We present in this work the design, construction and measurement results of a compact, mid-infrared spectrometer working in the 3 - 4 µm spectral region, attractive for applications requiring the identification of polymer materials. The spectrometer is based on linear-variable filters (LVF) combined with an uncooled HgCdTe linear-detector array (LDA). The design and architecture of the device is described and discussed in the context of miniaturization challenges and constraints. Measured spectra of thin polyimide and polystyrene foils are presented to prove the applicability of the developed device to polymer materials detection and identification.

Field phenotyping for African crops: overview and perspectives

Improvements in crop productivity are required to meet the dietary demands of the rapidly-increasing African population. The development of key staple crop cultivars that are high-yielding and resilient to biotic and abiotic stresses is essential. To contribute to this objective, high-throughput plant phenotyping approaches are important enablers for the African plant science community to measure complex quantitative phenotypes and to establish the genetic basis of agriculturally relevant traits. These advances will facilitate the screening of germplasm for optimum performance and adaptation to low-input agriculture and resource-constrained environments. Increasing the capacity to investigate plant function and structure through non-invasive technologies is an effective strategy to aid plant breeding and additionally may contribute to precision agriculture. However, despite the significant global advances in basic knowledge and sensor technology for plant phenotyping, Africa still lags behind in the development and implementation of these systems due to several practical, financial, geographical and political barriers. Currently, field phenotyping is mostly carried out by manual methods that are prone to error, costly, labor-intensive and may come with adverse economic implications. Therefore, improvements in advanced field phenotyping capabilities and appropriate implementation are key factors for success in modern breeding and agricultural monitoring. In this review, we provide an overview of the current state of field phenotyping and the challenges limiting its implementation in some African countries. We suggest that the lack of appropriate field phenotyping infrastructures is impeding the development of improved crop cultivars and will have a detrimental impact on the agricultural sector and on food security. We highlight the prospects for integrating emerging and advanced low-cost phenotyping technologies into breeding protocols and characterizing crop responses to environmental challenges in field experimentation. Finally, we explore strategies for overcoming the barriers and maximizing the full potential of emerging field phenotyping technologies in African agriculture. This review paper will open new windows and provide new perspectives for breeders and the entire plant science community in Africa.

In-Loco Optical Spectroscopy through a Multiple Digital Lock-In on a Linear Charge-Coupled Device (CCD) Array

Accurate and reliable measurements of optical properties are crucial for a wide range of industrial and commercial applications. However, external illumination fluctuations can often make these measurements challenging to obtain. This work proposes a new technique based on digital lock-in processing that enables the use of CCD spectrometers in optical spectroscopy applications, even in uncontrolled lighting conditions. This approach leverages digital lock-in processing, performed on each pixel of the spectrometer's CCD simultaneously, to mitigate the impact of external optical interferences. The effectiveness of this method is demonstrated by testing and recovering the spectrum of a yellow LED subjected to other light sources in outdoor conditions, corresponding to a Signal-to-Noise Ratio of -70.45 dB. Additionally, it was possible to demonstrate the method's applicability for the spectroscopic analysis of gold nanoparticles in outdoor conditions. These results suggest that the proposed technique can be helpful for a wide range of optical measurement techniques, even in challenging lighting conditions.

Effects of Glyphosate-Based Herbicide on Primary Production and Physiological Fitness of the Macroalgae Ulva lactuca

The use of glyphosate-based herbicides (GBHs) worldwide has increased exponentially over the last two decades increasing the environmental risk to marine and coastal habitats. The present study investigated the effects of GBHs at environmentally relevant concentrations (0, 10, 50, 100, 250, and 500 μg·L⁻¹) on the physiology and biochemistry (photosynthesis, pigment, and lipid composition, antioxidative systems and energy balance) of Ulva lactuca, a cosmopolitan marine macroalgae species. Although GBHs cause deleterious effects such as the inhibition of photosynthetic activity, particularly at 250 μg·L⁻¹, due to the impairment of the electron transport in the chloroplasts, these changes are almost completely reverted at the highest concentration (500 μg·L⁻¹). This could be related to the induction of tolerance mechanisms at a certain threshold or tipping point. While no changes occurred in the energy balance, an increase in the pigment antheraxanthin is observed jointly with an increase in ascorbate peroxidase activity. These mechanisms might have contributed to protecting thylakoids against excess radiation and the increase in reactive oxygen species, associated with stress conditions, as no increase in lipid peroxidation products was observed. Furthermore, changes in the fatty acids profile, usually attributed to the induction of plant stress response mechanisms, demonstrated the high resilience of this macroalgae. Notably, the application of bio-optical tools in ecotoxicology, such as pulse amplitude modulated (PAM) fluorometry and laser-induced fluorescence (LIF), allowed separation of the control samples and those treated by GBHs in different concentrations with a high degree of accuracy, with PAM more accurate in identifying the different treatments.

Raman Method in Identification of Species and Varieties, Assessment of Plant Maturity and Crop Quality—A Review

The present review covers reports discussing potential applications of the specificity of Raman techniques in the advancement of digital farming, in line with an assumption of yield maximisation with minimum environmental impact of agriculture. Raman is an optical spectroscopy method which can be used to perform immediate, label-free detection and quantification of key compounds without destroying the sample. The authors particularly focused on the reports discussing the use of Raman spectroscopy in monitoring the physiological status of plants, assessing crop maturity and quality, plant pathology and ripening, and identifying plant species and their varieties. In recent years, research reports have presented evidence confirming the effectiveness of Raman spectroscopy in identifying biotic and abiotic stresses in plants as well as in phenotyping and digital selection of plants in farming. Raman techniques used in precision agriculture can significantly improve capacities for farming management, crop quality assessment, as well as biological and chemical contaminant detection, thereby contributing to food safety as well as the productivity and profitability of agriculture. This review aims to increase the awareness of the growing potential of Raman spectroscopy in agriculture among plant breeders, geneticists, farmers and engineers.

Non-Invasive Monitoring of the Thermal and Morphometric Characteristics of Lettuce Grown in an Aeroponic System through Multispectral Image System

Aeroponics is a soilless cultivation technology integrating plant nutrition, physiology, ecological environment, agricultural automation and horticulture. One of the soilless advantages is that a non-invasive observation of the root system growth development is possible. This paper presents a vegetative growth evaluation of lettuce plants in an aeroponic chamber, where root and leaf development parameters were measured in three lettuce crops through plant images captured in the visible (VIS), near infrared (NIR) and far infrared (IR) spectra. A total of ninety lettuce plants was transplanted for this research, thirty for each experimental crop. The three lettuce crops were grown for thirty days in an aeroponic growth plant chamber inside a greenhouse under favorable conditions. The morphometric and thermal parameters of the lettuce roots (perimeter, area, length and average temperature) and leaves (perimeter, area and average temperature) were evaluated for each crop along ten image-capturing sessions through an implemented multispectral vision system. The average values of the root and leaf morphometric parameters obtained with the implemented imaging system along the lettuce growing period were statistically analyzed with Tukey testing. The obtained analysis results show no significant difference for a value of p ≤ 0.05 in 86.67%. Hence, the morphometric parameters can be used to characterize the vegetative lettuce growth in aeroponic crops. On the other hand, a correlation analysis was conducted between the thermal parameters computed with the root and leaf thermal image processing and the measured ambient temperature. The results were: R = 0.945 for correlation between ambient and leaf temperature, R = 0.963 for correlation between ambient and root temperature and R = 0.977 for leaf and root temperature. According to these results, the plant temperature is highly correlated with the ambient temperature in an aeroponic crop. The obtained study results suggest that multispectral image processing is a useful non-invasive tool to estimate the vegetative root and leaf growth parameters of aeroponic lettuce plants in a greenhouse.