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Filename: controllers/Detail.php
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File: /var/www/html/index.php
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Canopeo app was developed as a simple, accurate, rapid, and free tool to analyze ground cover fraction (GCF) from red-green-blue (RGB) images and videos captured in the field. With increasing interest in tools for plant phenotyping in controlled environments, the usefulness of Canopeo to identify differences in growth among Arabidopsis thaliana mutants in a controlled environment were explored. A simple imaging system was used to compare Arabidopsis mutants based on the FLAVIN-BINDING, KELCH REPEAT, F-BOX-1 (FKF1) mutation, which has been identified with increased biomass accumulation. Two FKF1 lines such as null expression (fkf1-t) and overexpression (FKF1-OE) lines were used along with wild type (Col-0). Canopeo was used to phenotype plants, based on biomass estimations. Under long-day photoperiod, fkf1-t had increased cellulose biosynthesis, and therefore biomass. Resource partitioning favored seedling vigor and delayed onset of senescence. In contrast, FKF1-OE illustrated a determinative growth habit where plant resources are primarily allocated for seed production. This study demonstrates the use of Canopeo for model plants and highlights its potential for phenotyping broadleaved crops in controlled environments. The value of adapting Canopeo for lab use is those with limited experience and resources have access to phenotyping methodology that is simple, accessible, accurate, and cost-efficient in a controlled environment setting.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10957076 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0300667 | PLOS |
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Wearable nanocomposite stretch sensors are an exciting new development in biomaterials for biomechanical motion-tracking technology, with applications in the treatment of low back pain, knee rehabilitation, fetal movement tracking, and other fields. When strained, the resistance of the low-cost sensors is reduced, enabling human motion to be monitored using a suitable sensor array. However, current sensor technologies have exhibited significant drift, in the form of increased electrical resistance, if left stored in typical room conditions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!