Loko I‘a

This is a manual on Hawaiian fishpond restoration and management. It includes information on the history of Hawaiian fishponds, permits and regulatory considerations, equipment for operations, net-pen production, optimizing pond health, troubleshooting, limu production, organizing a business plan and the economics of revitalizing Hawaiian fishpond production

ABC: Adaptive, Biomimetic, Configurable Robots for Smart Farms - From Cereal Phenotyping to Soft Fruit Harvesting

Currently, numerous factors, such as demographics, migration patterns, and economics, are leading to the critical labour shortage in low-skilled and physically demanding parts of agriculture. Thus, robotics can be developed for the agricultural sector to address these shortages. This study aims to develop an adaptive, biomimetic, and configurable modular robotics architecture that can be applied to multiple tasks (e.g., phenotyping, cutting, and picking), various crop varieties (e.g., wheat, strawberry, and tomato) and growing conditions. These robotic solutions cover the entire perception–action–decision-making loop targeting the phenotyping of cereals and harvesting fruits in a natural environment. The primary contributions of this thesis are as follows. a) A high-throughput method for imaging field-grown wheat in three dimensions, along with an accompanying unsupervised measuring method for obtaining individual wheat spike data are presented. The unsupervised method analyses the 3D point cloud of each trial plot, containing hundreds of wheat spikes, and calculates the average size of the wheat spike and total spike volume per plot. Experimental results reveal that the proposed algorithm can effectively identify spikes from wheat crops and individual spikes. b) Unlike cereal, soft fruit is typically harvested by manual selection and picking. To enable robotic harvesting, the initial perception system uses conditional generative adversarial networks to identify ripe fruits using synthetic data. To determine whether the strawberry is surrounded by obstacles, a cluster complexity-based perception system is further developed to classify the harvesting complexity of ripe strawberries. c) Once the harvest-ready fruit is localised using point cloud data generated by a stereo camera, the platform’s action system can coordinate the arm to reach/cut the stem using the passive motion paradigm framework, as inspired by studies on neural control of movement in the brain. Results from field trials for strawberry detection, reaching/cutting the stem of the fruit with a mean error of less than 3 mm, and extension to analysing complex canopy structures/bimanual coordination (searching/picking) are presented. Although this thesis focuses on strawberry harvesting, ongoing research is heading toward adapting the architecture to other crops. The agricultural food industry remains a labour-intensive sector with a low margin, and cost- and time-efficiency business model. The concepts presented herein can serve as a reference for future agricultural robots that are adaptive, biomimetic, and configurable

Using machine learning to support better and intelligent visualisation for genomic data

Massive amounts of genomic data are created for the advent of Next Generation Sequencing technologies. Great technological advances in methods of characterising the human diseases, including genetic and environmental factors, make it a great opportunity to understand the diseases and to find new diagnoses and treatments. Translating medical data becomes more and more rich and challenging. Visualisation can greatly aid the processing and integration of complex data. Genomic data visual analytics is rapidly evolving alongside with advances in high-throughput technologies such as Artificial Intelligence (AI), and Virtual Reality (VR). Personalised medicine requires new genomic visualisation tools, which can efficiently extract knowledge from the genomic data effectively and speed up expert decisions about the best treatment of an individual patient’s needs. However, meaningful visual analysis of such large genomic data remains a serious challenge. Visualising these complex genomic data requires not only simply plotting of data but should also lead to better decisions. Machine learning has the ability to make prediction and aid in decision-making. Machine learning and visualisation are both effective ways to deal with big data, but they focus on different purposes. Machine learning applies statistical learning techniques to automatically identify patterns in data to make highly accurate prediction, while visualisation can leverage the human perceptual system to interpret and uncover hidden patterns in big data. Clinicians, experts and researchers intend to use both visualisation and machine learning to analyse their complex genomic data, but it is a serious challenge for them to understand and trust machine learning models in the serious medical industry. The main goal of this thesis is to study the feasibility of intelligent and interactive visualisation which combined with machine learning algorithms for medical data analysis. A prototype has also been developed to illustrate the concept that visualising genomics data from childhood cancers in meaningful and dynamic ways could lead to better decisions. Machine learning algorithms are used and illustrated during visualising the cancer genomic data in order to provide highly accurate predictions. This research could open a new and exciting path to discovery for disease diagnostics and therapies

Strawberry Production Guide For the Northeast, Midwest, and Eastern Canada 2nd Edition

This guide is intended as a comprehensive resource for both novice and experienced strawberry growers in northeastern North America. It provides information on all aspects of strawberry culture. The second edition has been updated and revised throughout, and includes expanded and new information on variety selection (Ch. 3), production systems (Ch. 4), harvesting, handling and transportation (Ch. 12), marketing (Ch. 13) and budgeting/economics (Ch. 14). In addition, a new section on diagnosing problems in strawberry plantings has been added (Ch. 15)

The Importance of Communication Skills to Independent Crop Consultants

Independent crop consulting companies provide services to farmers by scouting (i.e., collecting field observations of plants and pests) and developing management recommendations for individual fields. In production agriculture, independent crop consultants (ICCs) are professionals who are independent of product sales. They are knowledgeable in many disciplines including plant pathology, entomology, weed science, plant science, economics, water management, and soil science. However, ICCs must also have extensive communication skills to communicate to their audience of field scout(s), farmers, industry professionals, and government officials. The goal of this document is to examine how ICCs use their communication skills and how they can refine and strengthen their communication skills. Communication is an important life skill, involving knowledge or information transfer to produce an outcome. Communication concepts and models can be applied to interpersonal communication between ICCs and their audience (Chapter 1). Communication between the field scout and ICC primarily occurs during the field training process for the scout. Educational methods of experiential learning and scaffolding can be applied to this field training process (Chapter 2). Interviews with farmers explored the motivations and values of farmers that aid the ICC in communicating management recommendations to farmers (Chapter 3). These interviews emphasized farmers have individual goals, motivations, values, and communication styles, in which an ICC must adapt to develop a trusting relationship. Independent crop consultants are also instrumental in the agricultural social system by bridging knowledge transfer between farmers, industry professionals, and government officials (Chapter 4). Advisor: Gary L. Hei

Remote sensing program

Research projects concerning the development and application of remote sensors are discussed. Some of the research projects conducted are as follows: (1) aerial photographic inventory of natural resources, (2) detection of buried river channels, (3) delineation of interconnected waterways, (4) plant indicators of atmospheric pollution, and (5) techniques for data transfer from photographs to base maps. On-going projects involving earth resources analyses are described