scholarly journals Stress Detection Using Proximal Sensing of Chlorophyll Fluorescence on the Canopy Level

2021 ◽  
Vol 3 (3) ◽  
pp. 648-668
Author(s):  
Linnéa Ahlman ◽  
Daniel Bånkestad ◽  
Sammar Khalil ◽  
Karl-Johan Bergstrand ◽  
Torsten Wik
Keyword(s):  
Abiotic Stress ◽  
Chlorophyll Fluorescence ◽  
Powdery Mildew ◽  
Pythium Ultimum ◽  
Stress Factors ◽  
Biological Information ◽  
Proximal Sensing ◽  
Whole Plant ◽  
High Throughput Phenotyping ◽  
Light Excitation

Chlorophyll fluorescence is interesting for phenotyping applications as it is rich in biological information and can be measured remotely and non-destructively. There are several techniques for measuring and analysing this signal. However, the standard methods use rather extreme conditions, e.g., saturating light and dark adaption, which are difficult to accommodate in the field or in a greenhouse and, hence, limit their use for high-throughput phenotyping. In this article, we use a different approach, extracting plant health information from the dynamics of the chlorophyll fluorescence induced by a weak light excitation and no dark adaption, to classify plants as healthy or unhealthy. To evaluate the method, we scanned over a number of species (lettuce, lemon balm, tomato, basil, and strawberries) exposed to either abiotic stress (drought and salt) or biotic stress factors (root infection using Pythium ultimum and leaf infection using Powdery mildew Podosphaera aphanis). Our conclusions are that, for abiotic stress, the proposed method was very successful, while, for powdery mildew, a method with spatial resolution would be desirable due to the nature of the infection, i.e., point-wise spread. Pythium infection on the roots is not visually detectable in the same way as powdery mildew; however, it affects the whole plant, making the method an interesting option for Pythium detection. However, further research is necessary to determine the limit of infection needed to detect the stress with the proposed method.

scholarly journals Etiology and epidemiology of Pythium root rot in hydroponic crops: current knowledge and perspectives

2006 ◽  
Vol 32 (4) ◽  
pp. 307-321 ◽  
Author(s):  
John Clifford Sutton ◽  
Coralie Rachelle Sopher ◽  
Tony Nathaniel Owen-Going ◽  
Weizhong Liu ◽  
Bernard Grodzinski ◽  
...  
Keyword(s):  
Nutrient Solution ◽  
Root Rot ◽  
Root Zone ◽  
Pythium Ultimum ◽  
Stress Factors ◽  
Pythium Root Rot ◽  
Whole Plant ◽  
Phenolic Substances ◽  
Hydroponic Systems ◽  
The Impact

The etiology and epidemiology of Pythium root rot in hydroponically-grown crops are reviewed with emphasis on knowledge and concepts considered important for managing the disease in commercial greenhouses. Pythium root rot continually threatens the productivity of numerous kinds of crops in hydroponic systems around the world including cucumber, tomato, sweet pepper, spinach, lettuce, nasturtium, arugula, rose, and chrysanthemum. Principal causal agents include Pythium aphanidermatum, Pythium dissotocum, members of Pythium group F, and Pythium ultimum var. ultimum. Perspectives are given of sources of initial inoculum of Pythium spp. in hydroponic systems, of infection and colonization of roots by the pathogens, symptom development and inoculum production in host roots, and inoculum dispersal in nutrient solutions. Recent findings that a specific elicitor produced by P. aphanidermatum may trigger necrosis (browning) of the roots and the transition from biotrophic to necrotrophic infection are considered. Effects on root rot epidemics of host factors (disease susceptibility, phenological growth stage, root exudates and phenolic substances), the root environment (rooting media, concentrations of dissolved oxygen and phenolic substances in the nutrient solution, microbial communities and temperature) and human interferences (cropping practices and control measures) are reviewed. Recent findings on predisposition of roots to Pythium attack by environmental stress factors are highlighted. The commonly minor impact on epidemics of measures to disinfest nutrient solution as it recirculates outside the crop is contrasted with the impact of treatments that suppress Pythium in the roots and root zone of the crop. New discoveries that infection of roots by P. aphanidermatum markedly slows the increase in leaf area and whole-plant carbon gain without significant effect on the efficiency of photosynthesis per unit area of leaf are noted. The platform of knowledge and understanding of the etiology and epidemiology of root rot, and its effects on the physiology of the whole plant, are discussed in relation to new research directions and development of better practices to manage the disease in hydroponic crops. Focus is on methods and technologies for tracking Pythium and root rot, and on developing, integrating, and optimizing treatments to suppress the pathogen in the root zone and progress of root rot.

Identification of powdery mildew (Erysiphe graminis sp. tritici) and take-all disease (Gaeumannomyces graminis sp. tritici) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements

2006 ◽  
Vol 1 (2) ◽  
pp. 275-288 ◽  
Author(s):  
Simone Graeff ◽  
Johanna Link ◽  
Wilhelm Claupein
Keyword(s):  
Powdery Mildew ◽  
Disease Severity ◽  
Near Infrared ◽  
Plant Stress ◽  
Stress Factors ◽  
Gaeumannomyces Graminis ◽  
Disease Assessment ◽  
Leaf Reflectance ◽  
Reflectance Measurements ◽  
Take All

AbstractThe ability to identify diseases in an early infection stage and to accurately quantify the severity of infection is crucial in plant disease assessment and management. A greenhouse study was conducted to assess changes in leaf spectral reflectance of wheat plants during infection by powdery mildew and take-all disease to evaluate leaf reflectance measurements as a tool to identify and quantify disease severity and to discriminate between different diseases. Wheat plants were inoculated under controlled conditions in different intensities either with powdery mildew or take-all. Leaf reflectance was measured with a digital imager (Leica S1 Pro, Leica, Germany) under controlled light conditions in various wavelength ranges covering the visible and the near-infrared spectra (380–1300 nm). Leaf scans were evaluated by means of L*a*b*-color system. Visual estimates of disease severity were made for each of the epidemics daily from the onset of visible symptoms to maximum disease severity. Reflectance within the ranges of 490780 nm (r2 = 0.69), 510780nm (r2 = 0.74), 5161300nm (r2 = 0.62) and 5401300 nm (r2 = 0.60) exhibited the strongest relationship with infection levels of both powdery mildew and take-all disease. Among the evaluated spectra the range of 490780nm showed most sensitive response to damage caused by powdery mildew and take-all infestation. The results of this study indicated that disease detection and discrimination by means of reflectance measurements may be realized by the use of specific wavelength ranges. Further studies have to be carried out, to discriminate powdery mildew and take-all infection from other plant stress factors in order to develop suitable decision support systems for site-specific fungicide application.

scholarly journals Remote Sensing and Machine Learning in Crop Phenotyping and Management, with an Emphasis on Applications in Strawberry Farming

2021 ◽  
Vol 13 (3) ◽  
pp. 531
Author(s):  
Caiwang Zheng ◽  
Amr Abd-Elrahman ◽  
Vance Whitaker
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Precision Agriculture ◽  
Image Data ◽  
Fruit Shape ◽  
Biological Information ◽  
Genetic Traits ◽  
Multiple Sensors ◽  
Fruit Maturity ◽  
High Throughput Phenotyping

Measurement of plant characteristics is still the primary bottleneck in both plant breeding and crop management. Rapid and accurate acquisition of information about large plant populations is critical for monitoring plant health and dissecting the underlying genetic traits. In recent years, high-throughput phenotyping technology has benefitted immensely from both remote sensing and machine learning. Simultaneous use of multiple sensors (e.g., high-resolution RGB, multispectral, hyperspectral, chlorophyll fluorescence, and light detection and ranging (LiDAR)) allows a range of spatial and spectral resolutions depending on the trait in question. Meanwhile, computer vision and machine learning methodology have emerged as powerful tools for extracting useful biological information from image data. Together, these tools allow the evaluation of various morphological, structural, biophysical, and biochemical traits. In this review, we focus on the recent development of phenomics approaches in strawberry farming, particularly those utilizing remote sensing and machine learning, with an eye toward future prospects for strawberries in precision agriculture. The research discussed is broadly categorized according to strawberry traits related to (1) fruit/flower detection, fruit maturity, fruit quality, internal fruit attributes, fruit shape, and yield prediction; (2) leaf and canopy attributes; (3) water stress; and (4) pest and disease detection. Finally, we present a synthesis of the potential research opportunities and directions that could further promote the use of remote sensing and machine learning in strawberry farming.

scholarly journals Jute Responses and Tolerance to Abiotic Stress: Mechanisms and Approaches

Plants ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1595
Author(s):  
Khussboo Rahman ◽  
Naznin Ahmed ◽  
Md. Rakib Hossain Raihan ◽  
Farzana Nowroz ◽  
Faria Jannat ◽  
...  
Keyword(s):  
Abiotic Stress ◽  
Stress Responses ◽  
Growth Yield ◽  
Climatic Conditions ◽  
Stress Factors ◽  
Growth Physiology ◽  
Abiotic Stress Factors ◽  
Hot And Humid Climates ◽  
Adverse Environmental Conditions ◽  
Cold Metal

Jute (Corchorus spp.) belongs to the Malvaceae family, and there are two species of jute, C. capsularis and C. olitorious. It is the second-largest natural bast fiber in the world according to production, which has diverse uses not only as a fiber but also as multiple industrial materials. Because of climate change, plants experience various stressors such as salt, drought, heat, cold, metal/metalloid toxicity, and flooding. Although jute is particularly adapted to grow in hot and humid climates, it is grown under a wide variety of climatic conditions and is relatively tolerant to some environmental adversities. However, abiotic stress often restricts its growth, yield, and quality significantly. Abiotic stress negatively affects the metabolic activities, growth, physiology, and fiber yield of jute. One of the major consequences of abiotic stress on the jute plant is the generation of reactive oxygen species, which lead to oxidative stress that damages its cellular organelles and biomolecules. However, jute’s responses to abiotic stress mainly depend on the plant’s age and type and duration of stress. Therefore, understanding the abiotic stress responses and the tolerance mechanism would help plant biologists and agronomists in developing climate-smart jute varieties and suitable cultivation packages for adverse environmental conditions. In this review, we summarized the best possible recent literature on the plant abiotic stress factors and their influence on jute plants. We described the possible approaches for stress tolerance mechanisms based on the available literature.

scholarly journals Creation of competitive varieties of melon and pumpkin with valuable economic trends

2021 ◽  
pp. 36-41
Author(s):  
M. S. Kornilova ◽  
D. P. Kurunina ◽  
G. V. Varivoda
Keyword(s):  
Powdery Mildew ◽  
Climatic Conditions ◽  
Matter Content ◽  
Stress Factors ◽  
Mass Selection ◽  
Dry Matter Content ◽  
Average Yield ◽  
Experimental Station ◽  
Economically Valuable Traits ◽  
New Varieties

Relevance. The soil and climatic conditions of the Lower Trans-Volga region are considered favorable for melon growing and make it possible to obtain high-quality products. The purpose of the research was to create new competitive varieties and hybrids of melon and pumpkin.Materials and methods. The object of the research is new varieties of melon and butternut pumpkin created at the Bykovskaya melon breeding experimental station. Melon cultivar Osen and pumpkin cv. Zhemchuzhina were used as standards. The methods of creation are intervarietal hybridization, individual and mass selection. During the growing season, appropriate observations and counts were carried out.Results. As a result of many years of breeding work at the Bykovskaya cucurbits selection experimental station, a melon cultivar 251 and a pumpkin cultivar 509 have been created. both producers and consumers. Therefore, the obtained varieties were evaluated for taste, yield, resistance to biological and abiofactors of the environment, dry matter content, fruit size, fruit and pulp color. During the comparative assessment of the accessions, it was determined that the new varieties of melon and pumpkin exceed the standards in terms of the main economically valuable traits. The average yield during the study, in the melon cultivar 251, exceeded the standard by 47.8%. In the pumpkin cultivar, the average yield for three years of research exceeded the standard by 69.6%. In terms of taste, the new melon variety was at the level of the standard, the cv. Osen. A variety of butternut pumpkin exceeded the standard in all quality indicators. The susceptibility to powdery mildew in the melon cultivar varied depending on the year of research. The melon sample showed resistance to anthracnose higher than the standard by 16.4 and 18.6%, over the years of study. In the pumpkin cultivar, resistance to powdery mildew and anthracnose was higher than the standard, on average by 34.9% to powdery mildew and by 28.6% to anthracnose. Thus, new varieties of melon and pumpkin meet the modern requirements of the industrial melon industry, are resistant to environmental stress factors, common diseases, and have economically valuable traits.

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