3 Applications of Machine Vision In Agricultural and Food Sciences

Background: Thymus genus has been used since ancient times for their valuable health properties, which could be attributed to their chemical components, especially essential oils (EOs). Among these species, T. vulgaris has a long history of use for different food and medicinal purposes. Scope and approach: This paper reviews the chemical composition of Thymus plants EOs, including thyme, describes their antimicrobial and antioxidant properties as well as recent food applications as preservatives. The role of these plants in cancer is also covered, as well as the potential these plants have to manage and treat other diseases. Furthermore, clinical studies are also detailed. Key findings and conclusions: Food preservation with naturally occurring compounds is gaining increasing importance due to the consumer demand for safe and high-quality products and to reduce the use of synthetic T preservatives. For this purpose, not only thyme but also other thymus plants can be used as such and combined with high-pressure, cold nitrogen plasma, in edible films (active packaging), etc. Moreover, the potential of these plants have to treat several diseases and complications reinforce their use in nutraceuticals and functional foods, but further clinical evidence is required.

The ultimate objective is to develop an autonomous remote sensing platform by integrating UAV and a real-time robust machine-vision system for quantification of fresh fruit bunches (FFB), counting Oil Palm trees, and for smart inventory management via custom-built GIS software. The final prototype will utilize NDVI sensors for simultaneous autonomous vegetation stress detection in oil palm plantations.

The main objective of this research is to develop a robust non-destructive technique for rapid estimation of six chemical element concentration (N, P, K, Ca, Mg, and B) in oil palm leaflet. The outcome of this study would contribute nutrient deficiency determination for tree-specific variable rat fertilizer application. The focus of the research would be on developing a wavelet transformation codes for automatic analysing of reflectance spectra of oil palm leaves. Upon successful completion, this project will also discuss possibilities for further refining the wavelet approach and for extending the technique to the sensing of a variety of vegetation properties and disease detection at a range of spatial scales. (Please see codes in the Appendix)

International Journal of Computer Vision and machine learning (IJCVML) is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced vision computing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in vision computing and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of vision computing.

We present a machine vision system for simultaneous and objective evaluation of two important functional attributes of a fabric, namely, soil release and shrinkage. Soil release corresponds to the efficacy of the fabric in releasing stains after laundering and shrinkage essentially quantifies the dimensional changes in the fabric postlaundering. Within the framework of the proposed machine vision scheme, the samples are prepared using a prescribed procedure and subsequently digitized using a commercially available off-the-shelf scanner. Shrinkage measurements in the lengthwise and widthwise directions are obtained by detecting and measuring the distance between two pairs of appropriately placed markers. In addition, these shrinkage markers help in producing estimates of the location of the center of the stain on the fabric image. Using this information, a customized adaptive statistical snake is initialized, which evolves based on region statistics to segment the stain. Once the stain is localized, appropriate measurements can be extracted from the stain and the background image that can help in objectively quantifying stain release. In addition, the statistical snakes algorithm has been parallelized on a graphical processing unit, which allows for rapid evolution of multiple snakes. This, in turn, translates to the fact that multiple stains can be detected and segmented in a computationally efficient fashion. Finally, the aforementioned scheme is validated on a sizeable set of fabric images and the promising nature of the results help in establishing the efficacy of the proposed approach.

International Journal of Computer Vision and machine learning (IJCVML) is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced vision computing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in vision computing and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of vision computing.

International Journal of Computer Vision and machine learning (IJCVML)
ISSN : 2246 - 209N 2974-5962 (Print)
******March Issue*****

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Scope

International Journal of Computer Vision and machine learning (IJCVML) is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced vision computing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in vision computing and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of vision computing.

Topics of interest include, but are not limited to, the following
• Machine Vision
• Image Processing and Formation
• Document Imaging in Business
• Pattern Recognition
• Image and Video Understanding
• Applications and Services
• Motion, Tracking and Stereo Vision
• Biometrics
• Machine Intelligence
• Data structures and databases
• Multimedia
• Speech Recognition
• Computational Models
• Mobile Imaging
• Vision-based human-computer interaction
• Image/video analysis
• Image-based modeling
• Medical Image Analysis
• Face and Gesture
• Stereo and Structure from motion
• Feature extraction, grouping and segmentation
• Scene analysis
• Object recognition
• Learning and Statistical methods
• Human-computer interaction
• Tracking and surveillance
• Biometrics; Vision for robots
• Activity/behavior recognition
Paper Submission

Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.


Other journals

• International Journal of Education(IJE)
• Fuzzy Logic Systems: an International Journal(FLSIJ)

Important Dates

• Submission Deadline :March 17, 2019
• Notification :March 27, 2019
• Final Manuscript Due :April 03, 2019
• Publication Date : Determined by the Editor-in-Chief
• TO SUBMIT YOUR PAPER, PLEASE CLICK THE FOLLOWING LINK Submit
Contacts
Here's where you can reach us :ijcvmljournal@yahoo.com(or) ijcvmljournal@gmail.com

Agricultural production in Kenya has stagnated since 1980s resulting in malnutrition in over 89% of Kenya’s population. Food insecurity has been identified as the prime cause of malnutrition. Low agricultural productivity due to declining soil fertility resulting from poor cropping systems and use of non adapted exotic crop species has worsened this situation. Intercropping offers advantages if well planned including improved soil fertility and yields. Bambara groundnuts have shown high yield in low fertility soils and have been described as a complete food. NERICA rice has been reported to offer higher yields and shorter growing seasons. Cropping systems that combine both these crops in production systems will help alleviate malnutrition and food insecurity as well as enhance soil fertility. The objective of this study was to assess the soil fertility variation in bambara groundnut and NERICA rice intercrop system in small holder farms in Western Kenya. Five treatments including T1: Sole crop of bambara groundnuts, T2: Rice NERICA 4 without intercropping with bambara groundnuts, T3: Rice NERICA 4 intercropped with bambara groundnuts, T4: Rice NERICA 11 without intercropping with bambara groundnuts and T5: Rice NERICA 11 intercropped with bambara groundnuts were used. Soil analyses including nitrogen, phosphorous, pH and soil moisture were done to evaluate soil fertility variations in the course of the intercrop system. Data obtained was subjected to analysis of variance (ANOVA) to determine if the treatment effects were significant at 5% level. Separation of means was done by Least Significant Difference (LSD) at 5% level. Soil fertility under intercropping system was significantly higher in the subsequent seasons as compared to the initial season with bambara groundnuts replenishing the soil N through its association with N fixing bacteria. This study provides an understanding of the effect of NERICA rice and bambara groundnuts intercrop system on soil fertility. This allows us to understand the response mechanisms both below and above ground of the two crops to resources.