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[Methods in Molecular Biology] Immune Checkpoint Blockade Volume 1913 (Methods and Protocols) || Multispectral Fluorescence Imaging Allows for Distinctive Topographic Assessment and Subclassification of Tumor-Infiltrating and Surrounding Immune Cells
摘要： Histomorphology has significantly changed over the last decades due to technological achievements in immunohistochemistry (IHC) for the visualization of specific proteins and in molecular pathology, particularly in the field of in situ hybridization of small oligonucleotides and amplification of DNA and RNA amplicons. With an increased availability of suitable methods, the demands regarding the observer of histomorphological slides were the supply of complex quantitative data as well as more information about protein expression and cell-cell interactions in tissue sections. Advances in fluorescence-based multiplexed IHC techniques, such as multispectral imaging (MSI), allow the quantification of multiple proteins at the same tissue section. In histopathology, it is a well-known technique for over a decade yet harboring serious problems concerning quantitative preciseness and tissue autofluorescence of multicolor staining when using formalin-fixed, paraffin-embedded (FFPE) tissue specimen. In recent years, milestones in tissue preparation, fluorescent dyes, hardware imaging, and software analysis were achieved including automated tissue segmentation (e.g., tumor vs. stroma) as well as in cellular and subcellular multiparameter analysis. This chapter covers the role that MSI plays in anatomic pathology for the analysis of FFPE tissue sections, discusses the technical aspects of MSI, and provides a review of its application in the characterization of immune cell infiltrates and beyond regarding its prognostic and predictive value and its use for guidance of clinical decisions for immunotherapeutic strategies.
关键词： Phenotyping,Immune cells,Fluorescence microscopy,Multispectral imaging
更新于2025-09-19 17:15:36
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A Cost-Effective and Portable Optical Sensor System to Estimate Leaf Nitrogen and Water Contents in Crops
摘要： Non‐invasive determination of leaf nitrogen (N) and water contents is essential for ensuring the healthy growth of the plants. However, most of the existing methods to measure them are expensive. In this paper, a low‐cost, portable multispectral sensor system is proposed to determine N and water contents in the leaves, non‐invasively. Four different species of plants—canola, corn, soybean, and wheat—are used as test plants to investigate the utility of the proposed device. The sensor system comprises two multispectral sensors, visible (VIS) and near‐infrared (NIR), detecting reflectance at 12 wavelengths (six from each sensor). Two separate experiments were performed in a controlled greenhouse environment, including N and water experiments. Spectral data were collected from 307 leaves (121 for N and 186 for water experiment), and the rational quadratic Gaussian process regression (GPR) algorithm was applied to correlate the reflectance data with actual N and water content. By performing five‐fold cross‐validation, the N estimation showed a coefficient of determination (??2) of 63.91% for canola, 80.05% for corn, 82.29% for soybean, and 63.21% for wheat. For water content estimation, canola showed an ??2 of 18.02%, corn showed an ??2 of 68.41%, soybean showed an ??2 of 46.38%, and wheat showed an ??2 of 64.58%. The result reveals that the proposed low‐cost sensor with an appropriate regression model can be used to determine N content. However, further investigation is needed to improve the water estimation results using the proposed device.
关键词： plant phenotyping,non‐invasive,machine learning,reflectance,leaf nitrogen
更新于2025-09-19 17:13:59
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High throughput procedure utilising chlorophyll fluorescence imaging to phenotype dynamic photosynthesis and photoprotection in leaves under controlled gaseous conditions
摘要： Background: As yields of major crops such as wheat (T. aestivum) have begun to plateau in recent years, there is growing pressure to efficiently phenotype large populations for traits associated with genetic advancement in yield. Photosynthesis encompasses a range of steady state and dynamic traits that are key targets for raising Radiation Use Efficiency (RUE), biomass production and grain yield in crops. Traditional methodologies to assess the full range of responses of photosynthesis, such a leaf gas exchange, are slow and limited to one leaf (or part of a leaf ) per instrument. Due to constraints imposed by time, equipment and plant size, photosynthetic data is often collected at one or two phenological stages and in response to limited environmental conditions. Results: Here we describe a high throughput procedure utilising chlorophyll fluorescence imaging to phenotype dynamic photosynthesis and photoprotection in excised leaves under controlled gaseous conditions. When measured throughout the day, no significant differences (P > 0.081) were observed between the responses of excised and intact leaves. Using excised leaves, the response of three cultivars of T. aestivum to a user—defined dynamic lighting regime was examined. Cultivar specific differences were observed for maximum PSII efficiency (Fv′/Fm′—P < 0.01) and PSII operating efficiency (Fq′/Fm′—P < 0.04) under both low and high light. In addition, the rate of induction and relaxation of non-photochemical quenching (NPQ) was also cultivar specific. A specialised imaging chamber was designed and built in-house to maintain gaseous conditions around excised leaf sections. The purpose of this is to manipulate electron sinks such as photorespiration. The stability of carbon dioxide (CO2) and oxygen (O2) was monitored inside the chambers and found to be within ± 4.5% and ± 1% of the mean respectively. To test the chamber, T. aestivum ‘Pavon76’ leaf sections were measured under at 20 and 200 mmol mol?1 O2 and ambient [CO2] during a light response curve. The Fv′/Fm′was significantly higher (P < 0.05) under low [O2] for the majority of light intensities while values of NPQ and the proportion of open PSII reaction centers (qP) were significantly lower under > 130 μmol m?2 s?1 PPFD. Conclusions: Here we demonstrate the development of a high-throughput (> 500 samples day?1) method for phenotyping photosynthetic and photo-protective parameters in a dynamic light environment. The technique exploits chlorophyll fluorescence imaging in a specifically designed chamber, enabling controlled gaseous environment around leaf sections. In addition, we have demonstrated that leaf sections do not different from intact plant material even > 3 h after sampling, thus enabling transportation of material of interest from the field to this laboratory based platform. The methodologies described here allow rapid, custom screening of field material for variation in photosynthetic processes.
关键词： Dynamic,Imaging,Phenotyping,Wheat,Photo-protection,Photosynthesis,Chlorophyll fluorescence
更新于2025-09-16 10:30:52
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Fluctuating light experiments and semi-automated plant phenotyping enabled by self-built growth racks and simple upgrades to the IMAGING-PAM
摘要： Background: Over the last years, several plant science labs have started to employ fluctuating growth light conditions to simulate natural light regimes more closely. Many plant mutants reveal quantifiable effects under fluctuating light despite being indistinguishable from wild?type plants under standard constant light. Moreover, many subtle plant phenotypes become intensified and thus can be studied in more detail. This observation has caused a paradigm shift within the photosynthesis research community and an increasing number of scientists are interested in using fluctuating light growth conditions. However, high installation costs for commercial controllable LED setups as well as costly phenotyping equipment can make it hard for small academic groups to compete in this emerging field. Results: We show a simple do?it?yourself approach to enable fluctuating light growth experiments. Our results using previously published fluctuating light sensitive mutants, stn7 and pgr5, confirm that our low?cost setup yields similar results as top?prized commercial growth regimes. Moreover, we show how we increased the throughput of our Walz IMAGING?PAM, also found in many other departments around the world. We have designed a Python and R?based open source toolkit that allows for semi?automated sample segmentation and data analysis thereby reducing the processing bottleneck of large experimental datasets. We provide detailed instructions on how to build and functionally test each setup. Conclusions: With material costs well below USD$1000, it is possible to setup a fluctuating light rack including a constant light control shelf for comparison. This allows more scientists to perform experiments closer to natural light conditions and contribute to an emerging research field. A small addition to the IMAGING?PAM hardware not only increases sample throughput but also enables larger?scale plant phenotyping with automated data analysis.
关键词： Photosynthesis,Do?it?yourself,Phenotyping,Maker movement,Data analysis automation,Fluctuating light
更新于2025-09-12 10:27:22
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Optimal SVC placement for Maximizing Photovoltaic Hosting Capacity in Distribution Network
摘要： High throughput phenotyping holds promise of accelerating crop breeding programs and has gained great attention in the past several years. Although many platforms for data collection, including ground and aerial vehicles, have been developed to adapt to different crops and field setups, fully autonomous ground robots have not been readily available and widely used so far. In this study, we developed a ground robot that is capable of autonomously navigating in the field. We designed a sensor mounting frame that can be modified to mount different sensors for different data collection tasks. The robot was tested in a cotton breeding field and color images of the plants were collected. We developed an algorithm to count the cotton bolls using the color images. The preliminary results demonstrated that the system was capable of collecting data autonomously without human intervention and the collected data were useful to extract phenotypic traits.
关键词： cotton,phenotyping,high throughput,autonomous navigation,ground robot
更新于2025-09-11 14:15:04
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Ensemble Feature Selection for Plant Phenotyping: A Journey From Hyperspectral to Multispectral Imaging
摘要： Hyperspectral imaging is becoming an increasingly popular tool for high-throughput plant phenotyping, because it provides remarkable insights about the health status of plants. Feature selection is a key component in a hyperspectral image analysis, largely because a significant portion of spectral features are redundant and/or irrelevant, depending on the desired application. This paper presents an ensemble feature selection method to identify the most informative spectral features for practical applications in plant phenotyping. The hyperspectral data set contained the images of four wheat lines, each with a control and a salt (NaCl) treatment. To rank spectral features, six feature selection methods were used as the base for the ensemble: correlation-based feature selection, ReliefF, sequential feature selection, support vector machine-recursive feature elimination (SVM-RFE), LASSO logistic regression, and random forest. The best results were achieved by the ensemble of ReliefF, SVM-RFE, and random forest, which drastically reduced the dimension of the hyperspectral data set from 215 to 15 features, while improving the accuracy in classifying the salt-treated vegetation pixels from the control pixels by 8.5%. To transform the hyperspectral data set into a multispectral data set, six wavelengths as the center of broad multispectral bands around the most prominent features were determined by a clustering algorithm. The result of salt tolerance assessment of the four wheat lines using the derived multispectral data set was similar to that of the hyperspectral data set. This demonstrates that the proposed feature selection pipeline can be utilized for determining the most informative features and can be a valuable tool in the development of tailored multispectral cameras.
关键词： hyperspectral imaging,Band selection,multispectral imaging,wheat,ensemble feature selection,salt stress,machine learning,plant phenotyping,classification
更新于2025-09-10 09:29:36
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[American Society of Agricultural and Biological Engineers 2017 Spokane, Washington July 16 - July 19, 2017 - ()] 2017 Spokane, Washington July 16 - July 19, 2017 - <i>Phenotyping of Arabidopsis for drought stress response using kinetic chlorophyll fluorescence imaging</i>
摘要： Drought stress is one of the major concerns in global agricultural production. Developing an efficient phenotyping technology can bridge the knowledge gap between the plant phenotype and genotype, which can promote the progress of breeding for drought tolerant accessions and provide economic benefits for the producers and consumers. This research was aimed to investigate the plant phenotyping for drought stress responses of two different genotypes of Arabidopsis using chlorophyll fluorescence imaging. 59 treatment groups (three plants for each group) of each genotype were withholding being watered for 8 days as the drought stress treatment, and the other 59 groups considered as control were regularly watered with 6 ml 1% nutrient solution every day. The kinetic chlorophyll fluorescence images of the drought treatment groups and the control groups were acquired at day 1, 3, 5, 7 and 8 after the drought stress treatment started. The conventional chlorophyll fluorescence parameters and the leaf area index were then extracted from the images. In addition, associated morphological and physiological parameters were also assayed. To construct combinatorial images, the sequential forward selection (SFS) algorithm was used to select the maximum contrast images between two genotypes and the linear discriminant analysis (LDA) was used to build combinatorial images. Finally, combinatorial images were analyzed, indicating combinatorial images are valuable in drought stress studies. Above all, the study showed that AQ and osca1 presented different drought stress responses during the treatment period based on the conventional chlorophyll parameters and combinatorial images.
关键词： drought stress,Arabidopsis,plant phenotyping,combinatorial imaging,Chlorophyll fluorescence imaging
更新于2025-09-10 09:29:36
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Raspberry (Breeding, Challenges and Advances) || Use of Imaging Technologies for High Throughput Phenotyping
摘要： In this chapter we describe a high throughput phenotyping system that we have developed for raspberry and other soft fruit crops and its application to against individual (water stress regimes, vine weevil and Phytophthora root rot) and combined stresses. The term phenotype is used to describe the morphology, physiology, biochemistry and ontogeny of a plant, encompassing the diverse array of traits that contribute to the plant’s functional form. Plant phenotype is expressed as a consequence of the interaction between the plant genetic background (i.e. genotype) and the biotic and abiotic conditions experienced by the plant in its growing environment. A key focus of raspberry and other crop breeding is to understand the genetic control of desirable plant traits and the influence of environmental conditions on trait expression, which relies on the ability to collect quantitative information on target traits across genetically-characterised populations of plants. The process of characterising plant traits in detail, referred to as plant phenotyping, is a major challenge when relating plant genetic information to traits for plants in realistic growing environments.
关键词： high throughput phenotyping,raspberry,soft fruit crops,plant breeding,imaging technologies
更新于2025-09-10 09:29:36
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Smart Plant Factory (The Next Generation Indoor Vertical Farms) || Plant Factories with Artificial Lighting (PFALs): Benefits, Problems, and Challenges
摘要： The bene?ts, unsolved problems, and challenges for plant factories with arti?cial lighting (PFALs) are discussed. The remarkable bene?ts are high resource use ef?ciency, high annual productivity per unit land area, and production of high-quality plants without using pesticides. Major unsolved problems are high initial investment, electricity cost, and labor cost. A major challenge for the next-generation smart PFAL is the introduction of advanced technologies such as arti?cial intelligence with the use of big data, genomics, and phenomics (or methodologies and protocols for noninvasive measurement of plant-speci?c traits related to plant structure and function).
关键词： Smart LED lighting system,Cultivation system module (CSM),Phenotyping,Annual productivity,Standardization,Arti?cial intelligence,Resource use ef?ciency (RUE)
更新于2025-09-10 09:29:36
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Image-based tracking of ripening in wheat cultivar mixtures: A quantifying approach parallel to the conventional phenology
摘要： Developing the quantitative methods independent of the conventional qualitative phenology is a vital necessity for evaluating the temporal trends in the crop growth cycle, particularly in the heterogeneous canopies of cultivar mixtures. A digital camera was used to take ground-based nadir images during two years (2014–15 and 2015–16) of a ?eld experiment conducted at the School of Agriculture, Shiraz University, Iran, for monitoring and quantifying the ripening trends in wheat cultivar mixtures with di?erent ripening patterns grown under two irrigation conditions. The experimental treatments consisted of 4 early- to middle-ripening wheat cultivars and their 10 mixtures, under post-well- and de?cit-irrigated conditions, arranged in a randomized complete block design with 3 replicates. Then the images were processed and three image-derived indices including CC (canopy cover), GR [(G-R)/G; RGB color system], and CCGR (CC × GR) were used as the quantifying criteria. The de- clining trends of these indices during ripening showed strong ?ts to binomial equations, based on which simple prediction models were suggested and validated. Furthermore, the split linear trends and their slopes were estimated to assess the short-term variations. Some agronomic aspects were also evidenced using the mixtures- monoculture diversions, and the relationship between CC and GR. The frameworks evaluated appear to provide reliable and simple solutions for quantifying the crop temporal trends parallel to the conventional phenology.
关键词： Ripening pattern,Phenotyping,Thermal time,Canopy cover,Digital camera
更新于2025-09-10 09:29:36