Non-invasive determination of plant biomass with microwave resonators

Climate and soil factors co-derive the functional traits variations in naturalized downy thorn apple (Datura innoxia Mill.) along the altitudinal gradient in the semi-arid environment

Plant functional traits are consistently linked with certain ecological factors (i.e., abiotic and biotic), determining which components of a plant species pool are assembled into local communities. In this sense, non-native naturalized plants show more plasticity of morphological traits by adopting new habitat (an ecological niche) of the invaded habitats. This study focuses on the biomass allocation pattern and consistent traits-environment linkages of a naturalized Datura innoxia plant population along the elevation gradient in NW, Pakistan. We sampled 120 plots of the downy thorn apple distributed in 12 vegetation stands with 18 morphological and functional biomass traits during the flowering season and were analyzed along the three elevation zones having altitude ranges from 634.85 m to 1405.3 m from sear level designated as Group I to III identified by Ward's agglomerative clustering strategy (WACS). Our results show that many morphological traits and biomass allocation in different parts varied significantly (p < 0.05) in the pair-wise comparisons along the elevation. Likewise, all plant traits decreased from lower (drought stress) to high elevation zones (moist zones), suggesting progressive adaptation of Datura innoxia with the natural vegetation in NW Pakistan. Similarly, the soil variable also corresponds with the trait's variation e.g., significant variations (P < 0.05) of soil organic matter, organic carbon, Nitrogen and Phosphorus was recorded. The trait-environment linkages were exposed by redundancy analysis (RDA) that was co-drive by topographic (elevation, r = -0.4897), edaphic (sand, r = -0.4565 and silt, r = 0.5855) and climatic factors. Nevertheless, the influences of climatic factors were stronger than soil variables that were strongly linked with elevation gradient. The study concludes that D. innoxia has adopted the prevailing environmental and climatic conditions, and further investigation is required to evaluate the effects of these factors on their phytochemical and medicinal value.

Coherent terahertz laser feedback interferometry for hydration sensing in leaves

The response of terahertz to the presence of water content makes it an ideal analytical tool for hydration monitoring in agricultural applications. This study reports on the feasibility of terahertz sensing for monitoring the hydration level of freshly harvested leaves of Celtis sinensis by employing a imaging platform based on quantum cascade lasers and laser feedback interferometry. The imaging platform produces wide angle high resolution terahertz amplitude and phase images of the leaves at high frame rates allowing monitoring of dynamic water transport and other changes across the whole leaf. The complementary information in the resulting images was fed to a machine learning model aiming to predict relative water content from a single frame. The model was used to predict the change in hydration level over time. Results of the study suggest that the technique could have substantial potential in agricultural applications.

Leaf Count Aided Novel Framework for Rice (Oryza sativa L.) Genotypes Discrimination in Phenomics: Leveraging Computer Vision and Deep Learning Applications

Drought is a detrimental factor to gaining higher yields in rice (Oryza sativa L.), especially amid the rising occurrence of drought across the globe. To combat this situation, it is essential to develop novel drought-resilient varieties. Therefore, screening of drought-adaptive genotypes is required with high precision and high throughput. In contemporary emerging science, high throughput plant phenotyping (HTPP) is a crucial technology that attempts to break the bottleneck of traditional phenotyping. In traditional phenotyping, screening significant genotypes is a tedious task and prone to human error while measuring various plant traits. In contrast, owing to the potential advantage of HTPP over traditional phenotyping, image-based traits, also known as i-traits, were used in our study to discriminate 110 genotypes grown for genome-wide association study experiments under controlled (well-watered), and drought-stress (limited water) conditions, under a phenomics experiment in a controlled environment with RGB images. Our proposed framework non-destructively estimated drought-adaptive plant traits from the images, such as the number of leaves, convex hull, plant-aspect ratio (plant spread), and similarly associated geometrical and morphological traits for analyzing and discriminating genotypes. The results showed that a single trait, the number of leaves, can also be used for discriminating genotypes. This critical drought-adaptive trait was associated with plant size, architecture, and biomass. In this work, the number of leaves and other characteristics were estimated non-destructively from top view images of the rice plant for each genotype. The estimation of the number of leaves for each rice plant was conducted with the deep learning model, YOLO (You Only Look Once). The leaves were counted by detecting corresponding visible leaf tips in the rice plant. The detection accuracy was 86-92% for dense to moderate spread large plants, and 98% for sparse spread small plants. With this framework, the susceptible genotypes (MTU1010, PUSA-1121 and similar genotypes) and drought-resistant genotypes (Heera, Anjali, Dular and similar genotypes) were grouped in the core set with a respective group of drought-susceptible and drought-tolerant genotypes based on the number of leaves, and the leaves' emergence during the peak drought-stress period. Moreover, it was found that the number of leaves was significantly associated with other pertinent morphological, physiological and geometrical traits. Other geometrical traits were measured from the RGB images with the help of computer vision.

Ultra-Wideband Microwave Imaging System for Root Phenotyping

The roots are a vital organ for plant growth and health. The opaque surrounding environment of the roots and the complicated growth process means that in situ and non-destructive root phenotyping face great challenges, which thus spur great research interests. The existing methods for root phenotyping are either unable to provide high-precision and high accuracy in situ detection, or they change the surrounding root environment and are destructive to root growth and health. Thus,we propose and develop an ultra-wideband microwave scanning method that uses time reversal to achieve in situ root phenotyping nondestructively. To verify the method’s feasibility, we studied an electromagnetic numerical model that simulates the transmission signal of two ultra-wideband microwave antennas. The simulated signal of roots with different shapes shows the proposed system’s capability to measure the root size in the soil. Experimental validations were conducted considering three sets of measurements with different sizes, numbers and locations, and the experimental results indicate that the developed imaging system was able to differentiate root sizes and numbers with high contrast. The reconstruction from both simulations and experimental measurements provided accurate size estimation of the carrots in the soil, which indicates the system’s potential for root imaging.

Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions

Controlled plant growth facilities provide the possibility to alter climate conditions affecting plant growth, such as humidity, temperature, and light, allowing a better understanding of plant responses to abiotic and biotic stresses. A bottleneck, however, is measuring various aspects of plant growth regularly and non-destructively. Although several high-throughput phenotyping facilities have been built worldwide, further development is required for smaller custom-made affordable systems for specific needs. Hence, the main objective of this study was to develop an affordable, standalone and automated phenotyping system called "Phenocave" for controlled growth facilities. The system can be equipped with consumer-grade digital cameras and multispectral cameras for imaging from the top view. The cameras are mounted on a gantry with two linear actuators enabling XY motion, thereby enabling imaging of the entire area of Phenocave. A blueprint for constructing such a system is presented and is evaluated with two case studies using wheat and sugar beet as model plants. The wheat plants were treated with different irrigation regimes or high nitrogen application at different developmental stages affecting their biomass accumulation and growth rate. A significant correlation was observed between conventional measurements and digital biomass at different time points. Post-harvest analysis of grain protein content and composition corresponded well with those of previous studies. The results from the sugar beet study revealed that seed treatment(s) before germination influences germination rates. Phenocave enables automated phenotyping of plants under controlled conditions, and the protocols and results from this study will allow others to build similar systems with dimensions suitable for their custom needs.

Biomass estimation of cultivated red algae Pyropia using unmanned aerial platform based multispectral imaging

BACKGROUND

Pyropia is an economically advantageous genus of red macroalgae, which has been cultivated in the coastal areas of East Asia for over 300 years. Realizing estimation of macroalgae biomass in a high-throughput way would great benefit their cultivation management and research on breeding and phenomics. However, the conventional method is labour-intensive, time-consuming, manually destructive, and prone to human error. Nowadays, high-throughput phenotyping using unmanned aerial vehicle (UAV)-based spectral imaging is widely used for terrestrial crops, grassland, and forest, but no such application in marine aquaculture has been reported.

RESULTS

In this study, multispectral images of cultivated Pyropia yezoensis were taken using a UAV system in the north of Haizhou Bay in the midwestern coast of Yellow Sea. The exposure period of P. yezoensis was utilized to prevent the significant shielding effect of seawater on the reflectance spectrum. The vegetation indices of normalized difference vegetation index (NDVI), ratio vegetation index (RVI), difference vegetation index (DVI) and normalized difference of red edge (NDRE) were derived and indicated no significant difference between the time that P. yezoensis was completely exposed to the air and 1 h later. The regression models of the vegetation indices and P. yezoensis biomass per unit area were established and validated. The quadratic model of DVI (Biomass = - 5.550DVI² + 105.410DVI + 7.530) showed more accuracy than the other index or indices combination, with the highest coefficient of determination (R²), root mean square error (RMSE), and relative estimated accuracy (Ac) values of 0.925, 8.06, and 74.93%, respectively. The regression model was further validated by consistently predicting the biomass with a high R² value of 0.918, RMSE of 8.80, and Ac of 82.25%.

CONCLUSIONS

This study suggests that the biomass of Pyropia can be effectively estimated using UAV-based spectral imaging with high accuracy and consistency. It also implied that multispectral aerial imaging is potential to assist digital management and phenomics research on cultivated macroalgae in a high-throughput way.

Surface Density of the Spongy and Palisade Parenchyma Layers of Leaves Extracted From Wideband Ultrasonic Resonance Spectra

The wide band and air-coupled ultrasonic resonant spectroscopy together with a modified Simulated Annealing metaheuristic algorithm and a 1D layered acoustic-model are used to resolve the structure of plant leaves. In particular, this paper focuses on the extraction of the surface density of the different layers of tissue in leaves having a relatively simple structure. There are three main reasons to select the surface density as the focus of this study: (i) it is a parameter directly extracted by the proposed technique and it requires no further processing, (ii) it is relevant in order to study the dynamic of the water within the different tissues of the leaves and also to study the differential development of the different tissues, and (iii) unlike other parameters provided by this technique (like resonant frequency, impedance, ultrasonic elastic modulus, or ultrasonic damping), this parameter can be easier to understand as it is a direct measure of mass per unit surface. The selection of leaves with a simple structure is justified by the convenience of avoiding an unnecessary complication of the data extraction step. In this work, the technique was applied to determine the surface density of the palisade and spongy parenchyma layers of tissue of Ligustrum lucidum, Vitis vinifera, and Viburnum tinus leaves. The first species was used to study the variation of the surface density at full turgor with the thickness of the leaf, while the two other species were used to study the variation of the surface densities with the variation in the leaf relative water content. Consistency of the results with other conventional measurements (like overall surface density, and cross-section optical and cryo-SEM images) is discussed. The results obtained reveal the potential of this technique; moreover, the technique presents the additional advantage that can be applied in-vivo as it is completely non-invasive, non-destructive, fast, and equipment required is portable.

Plant Phenotyping Research Trends, a Science Mapping Approach

Modern plant phenotyping, often using non-invasive technologies and digital technologies, is an emerging science and provides essential information on how genetics, epigenetics, environmental pressures, and crop management (farming) can guide selection toward productive plants suitable for their environment. Thus, phenotyping is at the forefront of future plant breeding. Bibliometric science mapping is a quantitative method that analyzes scientific publications throughout the terms present in their title, abstract, and keywords. The aim of this mapping exercise is to observe trends and identify research opportunities. This allows us to analyze the evolution of phenotyping research and to predict emerging topics of this discipline. A total of 1,827 scientific publications fitted our search method over the last 20 years. During the period 1997-2006, the total number of publications was only around 6.1%. The number of publications increased more steeply after 2010, boosted by the overcoming of technological bias and by a set of key developments at hard and software level (image analysis and data storage management, automation and robotics). Cluster analysis evidenced three main groups linked to genetics, physiology, and imaging. Mainly the model plant "Arabidopsis thaliana" and the crops "rice" and "triticum" species were investigated in the literature. The last two species were studied when addressing "plant breeding," and "genomic selection." However, currently the trend goes toward a higher diversity of phenotyped crops and research in the field. The application of plant phenotyping in the field is still under rapid development and this application has strong linkages with precision agriculture. EU co-authors were involved in 41.8% of the analyzed papers, followed by USA (15.4%), Australia (6.0%), and India (5.6%). Within the EU, coauthors were mainly affiliated in Germany (35.8%), France (23.7%), and United Kingdom (18.4%). Time seems right for new opportunities to incentivize research on more crops, in real field conditions, and to spread knowledge toward more countries, including emerging economies. Science mapping offers the possibility to get insights into a wide amount of bibliographic information, making them more manageable, attractive, and easy to serve science policy makers, stakeholders, and research managers.

Changes in 15NO3 - Availability and Transpiration Rate Are Associated With a Rapid Diurnal Adjustment of Anion Contents as Well as 15N and Water Fluxes Between the Roots and Shoots

Background and Aims: Understanding interactions between water and nitrate fluxes in response to nitrate availability and transpiration rate is crucial to select more efficient plants for the use of water and nitrate. Methods: Some of these interactions were investigated in intact Brassica napus plants by combining a non-destructive gravimetric device with ¹⁵NO₃ ^- labeling. The set-up allowed high-resolution measurement of the effects of a cross-combination of two concentrations of KNO₃ or KCl (0.5 and 5 mM) with two different rates of transpiration controlled by the relative humidity during a day-night cycle. Key Results: Results show that (1) high external nitrate concentrations increased root water uptake significantly whatever the transpiration rate, (2) nitrate translocation depended both on the rate of nitrate uptake and loading into xylem (3) dilution-concentration effect of nitrate in the xylem was mainly modulated by both external nitrate availability and transpiration rate, (4) dynamic changes in ¹⁵N translocation in the xylem modified shoot growth and capacitance, and (5) variations in tissue concentrations of NO₃ ^- induced by the experimental conditions were balanced by changes in concentrations of chloride and sulfate ions. These effects were even more amplified under low transpiration condition and 0.5 mM external nitrate concentration. Conclusion: Taken together, these results highlight the fine and rapid adjustment of anion contents, nitrate and water flows to changes in transpiration rate and nitrate availability during a day-night cycle. The use of this non-invasive gravimetric device is therefore a powerful tool to assess candidates genes involved in nitrogen and water use efficiency.

Use of Natural Diversity and Biotechnology to Increase the Quality and Nutritional Content of Tomato and Grape

Improving fruit quality has become a major goal in plant breeding. Direct approaches to tackling fruit quality traits specifically linked to consumer preferences and environmental friendliness, such as improved flavor, nutraceutical compounds, and sustainability, have slowly been added to a breeder priority list that already includes traits like productivity, efficiency, and, especially, pest and disease control. Breeders already use molecular genetic tools to improve fruit quality although most advances have been made in producer and industrial quality standards. Furthermore, progress has largely been limited to simple agronomic traits easy-to-observe, whereas the vast majority of quality attributes, specifically those relating to flavor and nutrition, are complex and have mostly been neglected. Fortunately, wild germplasm, which is used for resistance against/tolerance of environmental stresses (including pathogens), is still available and harbors significant genetic variation for taste and health-promoting traits. Similarly, heirloom/traditional varieties could be used to identify which genes contribute to flavor and health quality and, at the same time, serve as a good source of the best alleles for organoleptic quality improvement. Grape (Vitis vinifera L.) and tomato (Solanum lycopersicum L.) produce fleshy, berry-type fruits, among the most consumed in the world. Both have undergone important domestication and selection processes, that have dramatically reduced their genetic variability, and strongly standardized fruit traits. Moreover, more and more consumers are asking for sustainable production, incompatible with the wide range of chemical inputs. In the present paper, we review the genetic resources available to tomato/grape breeders, and the recent technological progresses that facilitate the identification of genes/alleles of interest within the natural or generated variability gene pool. These technologies include omics, high-throughput phenotyping/phenomics, and biotech approaches. Our review also covers a range of technologies used to transfer to tomato and grape those alleles considered of interest for fruit quality. These include traditional breeding, TILLING (Targeting Induced Local Lesions in Genomes), genetic engineering, or NPBT (New Plant Breeding Technologies). Altogether, the combined exploitation of genetic variability and innovative biotechnological tools may facilitate breeders to improve fruit quality tacking more into account the consumer standards and the needs to move forward into more sustainable farming practices.

Non-invasive assessment of leaf water status using a dual-mode microwave resonator

The water status in plant leaves is a good indicator for the water status in the whole plant revealing stress if the water supply is reduced. The analysis of dynamic aspects of water availability in plant tissues provides useful information for the understanding of the mechanistic basis of drought stress tolerance, which may lead to improved plant breeding and management practices. The determination of the water content in plant tissues during plant development has been a challenge and is currently feasible based on destructive analysis only. We present here the application of a non-invasive quantitative method to determine the volumetric water content of leaves and the ionic conductivity of the leaf juice from non-invasive microwave measurements at two different frequencies by one sensor device. A semi-open microwave cavity loaded with a ceramic dielectric resonator and a metallic lumped-element capacitor- and inductor structure was employed for non-invasive microwave measurements at 150 MHz and 2.4 Gigahertz on potato, maize, canola and wheat leaves. Three leaves detached from each plant were chosen, representing three developmental stages being representative for tissue of various age. Clear correlations between the leaf- induced resonance frequency shifts and changes of the inverse resonator quality factor at 2.4 GHz to the gravimetrically determined drying status of the leaves were found. Moreover, the ionic conductivity of Maize leaves, as determined from the ratio of the inverse quality factor and frequency shift at 150 MHz by use of cavity perturbation theory, was found to be in good agreement with direct measurements on plant juice. In conjunction with a compact battery- powered circuit board- microwave electronic module and a user-friendly software interface, this method enables rapid in-vivo water amount assessment of plants by a handheld device for potential use in the field.

A review of imaging techniques for plant phenotyping

Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phenotyping platforms, a variety of imaging methodologies are being used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress (disease, insects, drought and salinity). These imaging techniques include visible imaging (machine vision), imaging spectroscopy (multispectral and hyperspectral remote sensing), thermal infrared imaging, fluorescence imaging, 3D imaging and tomographic imaging (MRT, PET and CT). This paper presents a brief review on these imaging techniques and their applications in plant phenotyping. The features used to apply these imaging techniques to plant phenotyping are described and discussed in this review.

The reflectivity in the S-band and the broadband ultrasonic spectroscopy as new tools for the study of water relations in Vitis vinifera L

The large water requirements of Vitis vinifera L. together with an increase in temperature and drought events imply the need for irrigation in the driest areas of its distribution range. Generous watering may reduce grape quality so irrigation should be precisely regulated through the development of new methods of accurate irrigation scheduling based on plant 'stress sensing'. Two new methods, the reflectivity in the S-band and the broadband ultrasonic spectroscopy, can be used as non-invasive and reproducible techniques for the study of plant water relations in V. vinifera. On one hand, the measurement of reflectance at frequencies around 2.4 GHz gives an excellent accuracy when the changes in the existing area (S) between two reflectance curves are correlated with the relative water content (RWC). On the other hand, an improvement of the broadband ultrasonic spectroscopy based on the enlargement of the analysis frequency window provides, apart from the determination of the turgor loss point (TLP), additional information about the leaves without additional computational cost or additional leaf information requirements. Before TLP, the frequency associated with the maximum transmittance (f/f(o)), the macroscopic elastic constant of the leaf in the Z direction (c(33)) and, specially, the variation of the attenuation coefficient with the frequency (n), were highly correlated with changes in RWC. Once turgor is lost, a shift in the parameters directly related to the attenuation of the signal was also observed. The use of both techniques allows for a more convincing knowledge of the water status in V. vinifera.

Future scenarios for plant phenotyping

With increasing demand to support and accelerate progress in breeding for novel traits, the plant research community faces the need to accurately measure increasingly large numbers of plants and plant parameters. The goal is to provide quantitative analyses of plant structure and function relevant for traits that help plants better adapt to low-input agriculture and resource-limited environments. We provide an overview of the inherently multidisciplinary research in plant phenotyping, focusing on traits that will assist in selecting genotypes with increased resource use efficiency. We highlight opportunities and challenges for integrating noninvasive or minimally invasive technologies into screening protocols to characterize plant responses to environmental challenges for both controlled and field experimentation. Although technology evolves rapidly, parallel efforts are still required because large-scale phenotyping demands accurate reporting of at least a minimum set of information concerning experimental protocols, data management schemas, and integration with modeling. The journey toward systematic plant phenotyping has only just begun.

Advanced phenotyping offers opportunities for improved breeding of forage and turf species

BACKGROUND AND AIMS

Advanced phenotyping, i.e. the application of automated, high-throughput methods to characterize plant architecture and performance, has the potential to accelerate breeding progress but is far from being routinely used in current breeding approaches. In forage and turf improvement programmes, in particular, where breeding populations and cultivars are characterized by high genetic diversity and substantial genotype × environment interactions, precise and efficient phenotyping is essential to meet future challenges imposed by climate change, growing demand and declining resources.

SCOPE

This review highlights recent achievements in the establishment of phenotyping tools and platforms. Some of these tools have originally been established in remote sensing, some in precision agriculture, while others are laboratory-based imaging procedures. They quantify plant colour, spectral reflection, chlorophyll-fluorescence, temperature and other properties, from which traits such as biomass, architecture, photosynthetic efficiency, stomatal aperture or stress resistance can be derived. Applications of these methods in the context of forage and turf breeding are discussed.

CONCLUSIONS

Progress in cutting-edge molecular breeding tools is beginning to be matched by progress in automated non-destructive imaging methods. Joint application of precise phenotyping machinery and molecular tools in optimized breeding schemes will improve forage and turf breeding in the near future and will thereby contribute to amended performance of managed grassland agroecosystems.

Elements of a dynamic systems model of canopy photosynthesis

Improving photosynthesis throughout the full canopy rather than photosynthesis of only the top leaves of the canopy is central to improving crop yields. Many canopy photosynthesis models have been developed from physiological and ecological perspectives, however most do not consider heterogeneities of microclimatic factors inside a canopy, canopy dynamics and associated energetics, or competition among different plants, and most models lack a direct linkage to molecular processes. Here we described the rationale, elements, and approaches necessary to build a dynamic systems model of canopy photosynthesis. A systems model should integrate metabolic processes including photosynthesis, respiration, nitrogen metabolism, resource re-mobilization and photosynthate partitioning with canopy level light, CO(2), water vapor distributions and heat exchange processes. In so doing a systems-based canopy photosynthesis model will enable studies of molecular ecology and dramatically improve our insight into engineering crops for improved canopy photosynthetic CO(2) uptake, resource use efficiencies and yields.

Development of synchronized, autonomous, and self-regulated oscillations in transpiration rate of a whole tomato plant under water stress

Plants respond to many environmental changes by rapidly adjusting their hydraulic conductivity and transpiration rate, thereby optimizing water-use efficiency and preventing damage due to low water potential. A multiple-load-cell apparatus, time-series analysis of the measured data, and residual low-pass filtering methods were used to monitor continuously and analyse transpiration of potted tomato plants (Solanum lycopersicum cv. Ailsa Craig) grown in a temperature-controlled greenhouse during well-irrigated and drought periods. A time derivative of the filtered residual time series yielded oscillatory behaviour of the whole plant's transpiration (WPT) rate. A subsequent cross-correlation analysis between the WPT oscillatory pattern and wet-wick evaporation rates (vertical cotton fabric, 0.14 m(2) partly submerged in water in a container placed on an adjacent load cell) revealed that autonomous oscillations in WPT rate develop under a continuous increase in water stress, whereas these oscillations correspond with the fluctuations in evaporation rate when water is fully available. The relative amplitude of these autonomous oscillations increased with water stress as transpiration rate decreased. These results support the recent finding that an increase in xylem tension triggers hydraulic signals that spread instantaneously via the plant vascular system and control leaf conductance. The regulatory role of synchronized oscillations in WPT rate in eliminating critical xylem tension points and preventing embolism is discussed.