Digital Commons Network^™

A Step Forward Towards Advanced And Self-Sustainable Greenhouse Agriculture, Mohammad Nur E Alam, Mikhail Vasiliev, Jacqualine Anne Thomas

Research outputs 2014 to 2021

It is now time for the future-generation and advanced greenhouse design practices to address a range of issues, from the energy and land use efficiency to providing plant-optimised growth techniques. In this Encyclopaedia record, we report on the practical development of spectrally selective and specialist-type advanced metal-dielectric thin-film filters that produce the optimized illumination spectrum when exposed to natural sunlight that can help maximize the biomass productivity of coated-glass greenhouse crops. Our experimental case study has been performed for the lettuce species, Lactuca sativa, L., yielding promising results.

Increasing The Yield Of Lactuca Sativa, L. In Glass Greenhouses Through Illumination Spectral Filtering And Development Of An Optical Thin Film Filter, Jacqualine Anne Thomas, Mikhail Vasiliev, Mohammad Nur-E-Alam, Kamal Alameh

Research outputs 2014 to 2021

With the increase in world population, the continued advances in modern greenhouse agriculture and plant growth practices are expected to help overcome the global problem of future food shortages. The next generation greenhouse design practices will need to address a range of issues, ranging from energy and land use efficiency to providing plant-optimized growth techniques. In this paper, we focus on investigating the optimum irradiation spectra matched to the lettuce species (Lactuca sativa, L.), commonly grown in greenhouse environments, in order to develop low-emissivity glass panes that maximize the biomass productivity of glass greenhouses. This low-emissivity glass passes the solar …

Investigating Optimum Wavelength(S) For Growth Of Lactuca Sativa, L. Using Tunable Led Sources And Developing Thin-Film Filters For Glass Greenhouses, Jacqualine Anne Thomas

Theses: Doctorates and Masters

With the increase in world population, the continued advances in modern greenhouse agriculture and plant growth practices are expected to help overcome the global problem of future food shortages. This research investigates a way to assist in stemming the problem of food shortage by using optimised light irradiation (within the constraints of the experiment) on a sample plant species of lettuce (Lactuca sativa, L.). Whilst lettuce is often grown in hydroponic systems, the current research is conducted in stand-alone pots with hand watering, due to the requirements of health and safety and available resources.

The experiments were designed …

A Novel Method For Detecting Morphologically Similar Crops And Weeds Based On The Combination Of Contour Masks And Filtered Local Binary Pattern Operators, Vi Nguyen Thanh Le, Selam Ahderom, Beniamin Apopei, Kamal Alameh

Research outputs 2014 to 2021

Background: Weeds are a major cause of low agricultural productivity. Some weeds have morphological features similar to crops, making them difficult to discriminate. Results: We propose a novel method using a combination of filtered features extracted by combined Local Binary Pattern operators and features extracted by plant-leaf contour masks to improve the discrimination rate between broadleaf plants. Opening and closing morphological operators were applied to filter noise in plant images. The images at 4 stages of growth were collected using a testbed system. Mask-based local binary pattern features were combined with filtered features and a coefficient k. The classification of …

Application Of Advanced Algorithms And Statistical Techniques For Weed-Plant Discrimination, Saman Akbar Zadeh

Theses: Doctorates and Masters

Precision agriculture requires automated systems for weed detection as weeds compete with the crop for water, nutrients, and light. The purpose of this study is to investigate the use of machine learning methods to classify weeds/crops in agriculture. Statistical methods, support vector machines, convolutional neural networks (CNNs) are introduced, investigated and optimized as classifiers to provide high accuracy at high vehicular speed for weed detection.

Initially, Support Vector Machine (SVM) algorithms are developed for weed-crop discrimination and their accuracies are compared with a conventional data-aggregation method based on the evaluation of discrete Normalised Difference Vegetation Indices (NDVIs) at two different …

Local Binary Pattern Based Algorithms For The Discrimination And Detection Of Crops And Weeds With Similar Morphologies, Vi Nguyen Thanh Le

Theses: Doctorates and Masters

In cultivated agricultural fields, weeds are unwanted species that compete with the crop plants for nutrients, water, sunlight and soil, thus constraining their growth. Applying new real-time weed detection and spraying technologies to agriculture would enhance current farming practices, leading to higher crop yields and lower production costs. Various weed detection methods have been developed for Site-Specific Weed Management (SSWM) aimed at maximising the crop yield through efficient control of weeds. Blanket application of herbicide chemicals is currently the most popular weed eradication practice in weed management and weed invasion. However, the excessive use of herbicides has a detrimental impact …