Automatic Non-Destructive Growth Measurement of Leafy Vegetables Based on Kinect.
Ontology highlight
ABSTRACT:
SUBMITTER: Hu Y
PROVIDER: S-EPMC5876734 | biostudies-literature | 2018 Mar
REPOSITORIES: biostudies-literature
Publications
Automatic Non-Destructive Growth Measurement of Leafy Vegetables Based on Kinect.
Hu Yang Y Wang Le L Xiang Lirong L Wu Qian Q Jiang Huanyu H
Sensors (Basel, Switzerland) 20180307 3
Non-destructive plant growth measurement is essential for plant growth and health research. As a 3D sensor, Kinect v2 has huge potentials in agriculture applications, benefited from its low price and strong robustness. The paper proposes a Kinect-based automatic system for non-destructive growth measurement of leafy vegetables. The system used a turntable to acquire multi-view point clouds of the measured plant. Then a series of suitable algorithms were applied to obtain a fine 3D reconstruction ...[more]
Similar Datasets
Project description:In agriculture, information about the spatial distribution of plant growth is valuable for applications. Quantitative study of the characteristics of plants plays an important role in the plants' growth and development research, and non-destructive measurement of the height of plants based on machine vision technology is one of the difficulties. We propose a methodology for three-dimensional reconstruction under growing plants by Kinect v2.0 and explored the measure growth parameters based on three-dimensional (3D) point cloud in this paper. The strategy includes three steps-firstly, preprocessing 3D point cloud data, completing the 3D plant registration through point cloud outlier filtering and surface smooth method; secondly, using the locally convex connected patches method to segment the leaves and stem from the plant model; extracting the feature boundary points from the leaf point cloud, and using the contour extraction algorithm to get the feature boundary lines; finally, calculating the length, width of the leaf by Euclidean distance, and the area of the leaf by surface integral method, measuring the height of plant using the vertical distance technology. The results show that the automatic extraction scheme of plant information is effective and the measurement accuracy meets the need of measurement standard. The established 3D plant model is the key to study the whole plant information, which reduces the inaccuracy of occlusion to the description of leaf shape and conducive to the study of the real plant growth status.
| S-EPMC7285297 | biostudies-literature
Project description:BACKGROUND:Numerous studies acknowledged the importance of an adequate vegetable consumption for human health. However, current methods to estimate vegetable intake are often prone to measurement errors due to self-reporting and/or insufficient detail. More objective intake biomarkers for vegetables, using biological specimens, are preferred. The only concentration biomarkers currently available are blood carotenoids and vitamin C, covering total fruit and vegetable intake. Identification of biomarkers for specific vegetables is needed for a better understanding of their relative importance for human health. Within the FoodBAll Project under the Joint Programming Initiative "A Healthy Diet for a Healthy Life", an ambitious action was undertaken to identify candidate intake biomarkers for all major food groups consumed in Europe by systematically reviewing the existent literature. This study describes the review on candidate biomarkers of food intake (BFIs) for leafy, bulb, and stem vegetables, which was conducted within PubMed, Scopus and Web of Science for studies published through March 2019. RESULTS:In total, 65 full-text articles were assessed for eligibility for leafy vegetables, and 6 full-text articles were screened for bulb and stem vegetables. Putative BFIs were identified for spinach, lettuce, endive, asparagus, artichoke, and celery, but not for rocket salad. However, after critical evaluation through a validation scheme developed by the FoodBAll consortium, none of the putative biomarkers appeared to be a promising BFI. The food chemistry data indicate that some candidate BFIs may be revealed by further studies. CONCLUSION:Future randomized controlled feeding studies combined with observational studies, applying a non-targeted metabolomics approach, are needed in order to identify valuable BFIs for the intake of leafy, bulb, and stem vegetables.
| S-EPMC7144047 | biostudies-literature
Project description:In living tissues, mechanical stiffness and biological function are intrinsically linked. Alterations in the stiffness of tissues can induce pathological interactions that affect cellular activity and tissue function. Underlying connections between tissue stiffness and disease highlights the importance of accurate quantitative characterizations of soft tissue mechanics, which can improve our understanding of disease and inform therapeutic development. In particular, accurate measurement of lung mechanical properties has been especially challenging due to the anatomical and mechanobiological complexities of the lung. Discrepancies between measured mechanical properties of dissected lung tissue samples and intact lung tissues in vivo has limited the ability to accurately characterize integral lung mechanics. Here, we report a non-destructive vacuum-assisted method to evaluate mechanical properties of soft biomaterials, including intact tissues and hydrogels. Using this approach, we measured elastic moduli of rat lung tissue that varied depending on stress-strain distribution throughout the lung. We also observed that the elastic moduli of enzymatically disrupted lung parenchyma increased by at least 64%. The reported methodology enables assessment of the nonlinear viscoelastic characteristics of intact lungs under normal and abnormal (i.e., injured, diseased) conditions and allows measurement of mechanical properties of tissue-mimetic biomaterials for use in therapeutics or in vitro models. STATEMENT OF SIGNIFICANCE: Accurate quantification of tissue stiffness is critical for understanding mechanisms of disease and developing effective therapeutics. Current modalities to measure tissue stiffness are destructive and preclude accurate assessment of lung mechanical properties, as lung mechanics are determined by complex features of the intact lung. To address the need for alternative methods to assess lung mechanics, we report a non-destructive vacuum-based approach to quantify tissue stiffness. We applied this method to correlate lung tissue mechanics with tissue disruption, and to assess the stiffness of biomaterials. This method can be used to inform the development of tissue-mimetic materials for use in therapeutics and disease models, and could potentially be applied for in-situ evaluation of tissue stiffness as a diagnostic or prognostic tool.
| S-EPMC9245063 | biostudies-literature
Project description:Sinorhizobium meliloti 1021 bacteria secretes a considerable amount of flavins (FLs) and can form a nitrogen-fixing symbiosis with legumes. This strain is also associated with non-legume plants. However, its role in plant growth promotion (PGP) of non-legumes is not well understood. The present study evaluated the growth and development of lettuce (Lactuca sativa) and kale (Brassica oleracea var. acephala) plants inoculated with S. meliloti 1021 (FL+) and its mutant 1021ΔribBA, with a limited ability to secrete FLs (FL-). The results from this study indicated that inoculation with 1021 significantly (p < 0.05) increased the lengths and surface areas of the roots and hypocotyls of the seedlings compared to 1021ΔribBA. The kale and lettuce seedlings recorded 19% and 14% increases in total root length, respectively, following inoculation with 1021 compared to 1021ΔribBA. A greenhouse study showed that plant growth, photosynthetic rate, and yield were improved by 1021 inoculation. Moreover, chlorophylls a and b, and total carotenoids were more significantly (p < 0.05) increased in kale plants associated with 1021 than non-inoculated plants. In kale, total phenolics and flavonoids were significantly (p < 0.05) increased by 6% and 23%, respectively, and in lettuce, the increments were 102% and 57%, respectively, following 1021 inoculation. Overall, bacterial-derived FLs enhanced kale and lettuce plant growth, physiological indices, and yield. Future investigation will use proteomic approaches combined with plant physiological responses to better understand host-plant responses to bacteria-derived FLs.
| S-EPMC10488295 | biostudies-literature
Project description:Plants are primary source of nutrients for humans. However, the nutritional value of vegetables tends to decrease once organ and tissue sinks are detached from the plant. Minimal processing of leafy vegetables involves cutting and washing before packaging and storage. These processing procedures result in stressful conditions and post-harvest disorders senescence-related can also occur. The aim of this work is to define a methodological pipeline to evaluate the "quality" changes of fresh cut leafy vegetables over their shelf-life. At this purpose, intra-species variability has been investigated considering two varieties of Lactuca sativa (var. longifolia and capitata), showing different susceptibility to browning. Since browning mainly depends on phenol oxidation, redox parameters as well as the activity of the enzymes involved in phenol biosynthesis and oxidation have been monitored over storage time. At the same time, the metabolic changes of the lettuce leaves have been estimated as response patterns to chemical sensors. The obtained sensor outputs were predictive of browning-related biological features in a cultivar-dependent manner. The integration of the results obtained by this multivariate methodological approach allowed the identification of the most appropriate quality markers in lettuce leaves from different varieties. This methodological pipeline is proposed for the identification and subsequent monitoring of post-harvest quality of leafy vegetables.
| S-EPMC10667519 | biostudies-literature
Project description:Selenium deficiency in humans has been associated with various diseases, the risks of which can be reduced through dietary supplementation. Selenium accumulating plants may provide a beneficial nutrient for avoiding such illnesses. Thus, leafy vegetables such as Amaranthus hybridus, Amaranthus sp., Cucurbita maxima, Ipomoea batatas, Solanum villosum, Solanum scabrum, and Vigna unguiculata were explored for their capabilities to accumulate selenium when grown on selenium enriched soil and for use as a potential source of selenium enriched functional foods. Their selenium contents were determined by spectrophotometry using the complex of 3,3'-diaminobenzidine hydrochloride (DABH) as a chromogen. The mean concentrations in the leaves were found to range from 7.90 ± 0.40 to 1.95 ± 0.12 μg/g dry weight (DW), with C. maxima accumulating the most selenium. In stems, the accumulated selenium content ranged from 1.12 ± 0.10 μg/g in Amaranthus sp. to 5.35 ± 0.78 μg/g DW in C. maxima and was hence significantly different (P < 0.01). The cancer cell line MDA-MB-231 was used in cytotoxicity assays to determine the anticancer potential of these extracts. With exception of S. scabrum and S. villosum, no cytotoxicity was detected for the selenium enriched vegetable extracts up to 100 μg/mL concentration. Hence, following careful evaluation the studied vegetables may be considered as selenium enriched functional foods.
| S-EPMC4756630 | biostudies-literature
Project description:Cadmium (Cd) is a toxic element that can accumulate in edible plant tissues and negatively impact human health. Traditional Cd quantification methods are time-consuming, expensive, and generate a lot of toxic waste, slowing development of methods to reduce uptake. The objective of this study was to determine whether hyperspectral imaging (HSI) and machine learning (ML) can be used to predict Cd concentrations in plants using kale (Brassica oleracea) and basil (Ocimum basilicum) as model crops. The experiments were conducted in an automated phenotyping facility where all environmental conditions except soil Cd concentration were kept constant. Cd concentrations were determined at harvest using traditional methods and used to train the ML models with data collected from the imaging sensor. Visible/near infrared (VNIR) images were also collected at harvest and processed to calculate reflectance at 473 bands between 400 to 998 nm. All reflectance spectra were subject to the feature selection algorithm ReliefF and Principal Component Analysis (PCA) to generate data and provide input to evaluate three ML classification models: artificial neural network (ANN), ensemble learning (EL), and support vector machine (SVM). Plants were categorized according to Cd concentrations higher or lower than the safety threshold of 0.2 mg kg-1 Cd. Wavelengths with the highest ranks for Cd detection were between 519 and 574, and 692 and 732 nm, indicating that Cd content likely altered the plants' chlorophyll content and altered leaf internal structure. All models were able to sort the plants into groups, though the model with the best F1 score was the ANN for the validation subset that utilized reflectance from all wavelengths. This study demonstrates that HSI and ML are promising technologies for the fast and precise diagnosis of Cd in leafy green plants, though additional studies are needed to adapt this approach for more complex field environments.
| S-EPMC9800301 | biostudies-literature
Project description:The consumption of fresh produce is increasing due to its role in promoting a healthy and balanced diet. However, this trend is accompanied by increased foodborne disease cases associated with pathogens such as Escherichia, Listeria, and Salmonella. Previous studies provided evidence that the internalization of foodborne pathogens in fresh produce may be a potential contamination route and may pose a public health risk. This study investigates the combination effects of storage temperature and humidity on Salmonella internalization in six types of leafy greens (iceberg lettuce, romaine lettuce, red lettuce, green onion, spinach, and kale) during the storage stage. The results indicated that temperature plays a critical role in Salmonella internalization, with higher concentrations observed in samples stored at 25 °C compared to those stored at 7 °C. The mean concentration of internalized Salmonella in the iceberg lettuce sample was the highest and that in the green onion sample was the lowest (iceberg lettuce > red lettuce > romaine lettuce > spinach > kale > green onion). Mist conditions also had an impact on internalization. The group treated with mist showed an increase in Salmonella internalization of about 10-30% rather than the group without mist treatment. This research emphasizes the importance of understanding the factors influencing bacterial internalization in fresh produce and highlights the need for proper storage conditions to minimize the risk of contamination and ensure food safety.
| S-EPMC10453844 | biostudies-literature
Project description:In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers' expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects' attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import-export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods' application in the detection and classification of insect infestation in fruits and vegetables.
| S-EPMC7404779 | biostudies-literature
Project description:Vegetables cultivated in soil irrigated with untreated groundwater and municipal-waste-dominated (MWD) stream can elevate the concentration of heavy metals (Cd, Fe, Zn, Hg, Cr, and Ni) in edible parts of the crop, affecting food safety and public health worldwide. This study assessed the quality, sources, and distribution of heavy metals in surface soils, MWD stream and groundwater, and edible tissues of leafy and non-leafy vegetables from a major urban farm in the Sekondi-Takoradi metropolis, Ghana. Human health risk due to exposure to the metals in frequently consumed vegetables were investigated. Indigenous leafy vegetables (Corchorus olitorious and Amaranthus spinosus), exotic leafy vegetables (Lactuca sativa, Brassica oleracea, and Brassica rapa), and non-leafy vegetables (Capsicum annum, Raphanus sativus, Daucus carota, and Allium cepa) were collected from the urban farm. The mean concentration of Cd, Hg, and Fe ranged from 0.008 - 0.027, 0.001-0.013, and 4.517-36.178 mg/kg fw in edible parts of non-leafy vegetables, respectively and 0.011-0.035, 0.002-0.011, and 3.617-13.695 mg/kg fw in exotic or indigenous leafy vegetables. The vegetables were less impacted with the metals if compared to similar vegetables produced from other urban farms, locally and in some countries in Africa, Asia, and Europe. Water resource on the farm were not suitable for vegetable crop irrigation since mean concentration of E. coli (200 cfu/mL), Hg (0.009 mg/L), and Cd (0.019 mg/L) in the MWD stream and 80 % of the groundwater sources exceeded the safe limits recommended by the Food and Agriculture Organization. Geo-accumulation index for each metal in soil was ≤0, however, enrichment factor indicated a high anthropic enriched soil for Cr and Ni. Principal component analysis-multiple linear regression of the metals in soil identified mixed household waste/fertilizer, fertilizer, and crustal material as main sources for the heavy metal load in soil for which geogenic sources accounted for 74.3 %. Preferentially, Cd and Hg accumulated in Amaranthus spinosus, Daucus carota, and Corchorus olitorious. The estimated daily intake of each metal in the vegetables were below local and international daily dietary intake levels. At the 95th percentile concentration of each metal, target hazard quotient and the hazard index was <1 for adult male or female who consume the vegetables. Finally, appropriate agri-horticultural practices must be enforced to mitigate Cd, Ni, Cr, and Hg accumulation in the soil-vegetable system since the metals have profound adverse effect on human health.
| S-EPMC7785835 | biostudies-literature