Annual Report: 2009

I submit herewith the annual report from the Agricultural and Forestry Experiment Station, School of Natural Resources and Agricultural Sciences, University of Alaska Fairbanks, for the period ending December 31, 2009. This is done in accordance with an act of Congress, approved March 2, 1887, entitled, “An act to establish agricultural experiment stations, in connection with the agricultural college established in the several states under the provisions of an act approved July 2, 1862, and under the acts supplementary thereto,” and also of the act of the Alaska Territorial Legislature, approved March 12, 1935, accepting the provisions of the act of Congress. The research reports are organized according to our strategic plan, which focuses on high-latitude soils, high-latitude agriculture, natural resources use and allocation, ecosystems management, and geographic information. These areas cross department and unit lines, linking them and unifying the research. We have also included in our financial statement information on the special grants we receive. These special grants allow us to provide research and outreach that is targeted toward economic development in Alaska. Research conducted by our graduate and undergraduate students plays an important role in these grants and the impact they make on Alaska.Financial statement -- Grants -- Students -- Research Reports: Partners, Facilities, and Programs; Geography; High-Latitude Agriculture; High-Latitude Soils; Management of Ecosystems; Natural Resources Use and Allocation; Index to Reports -- Publications -- Facult

Greenhouse application of light-drone imaging technology for assessing weeds severity occurring on baby-leaf red lettuce beds approaching fresh-cutting

Aim of study: For baby-leaf lettuces greenhouse cultivations the absence of weeds is a mandatory quality requirement. One of the most promising and innovative technologies in weed research, is the use of Unmanned Aerial Vehicles (or drones) equipped with acquisition systems. The aim of this study was to provide an estimation of the exact weed amount on baby-sized red lettuce beds using a light drone equipped with an RGB microcamera.Area of study: Trials were performed at specialized organic farm site in Eboli (Salerno, Italy), under polyethylene multi-tunnel greenhouse.Material and methods: The RGB images acquired were processed with specific algorithms distinguishing weeds from crop yields, estimating the weeds covered surface and the severity of weed contamination in terms of biomass. A regression between the percentage of the surface covered by weed (with respect to the image total surface) and the weight of weed (with respect to the total harvested biomass) was calculated.Main results: The regression between the total cover values of the 25 calibration images and the total weight measured report a significant linear correlation. Digital monitoring was able to capture with accuracy the highly variable weed coverage that, among the different grids positioned under real cultivation conditions, was in the range 0-16.4% of the total cultivated one.Research highlights: In a precision weed management context, with the aim of improving management and decreasing the use of pesticides, this study provided an estimation of the exact weed amount on baby-sized red lettuce beds using a light drone

Annual Report: 2008

I submit herewith the annual report from the Agricultural and Forestry Experiment Station, School of Natural Resources and Agricultural Sciences, University of Alaska Fairbanks, for the period ending December 31, 2008. This is done in accordance with an act of Congress, approved March 2, 1887, entitled, “An act to establish agricultural experiment stations, in connection with the agricultural college established in the several states under the provisions of an act approved July 2, 1862, and under the acts supplementary thereto,” and also of the act of the Alaska Territorial Legislature, approved March 12, 1935, accepting the provisions of the act of Congress. The research reports are organized according to our strategic plan, which focuses on high-latitude soils, high-latitude agriculture, natural resources use and allocation, ecosystems management, and geographic information. These areas cross department and unit lines, linking them and unifying the research. We have also included in our financial statement information on the special grants we receive. These special grants allow us to provide research and outreach that is targeted toward economic development in Alaska. Research conducted by our graduate and undergraduate students plays an important role in these grants and the impact they make on Alaska.Financial statement -- Grants -- Students -- Research reports: Partners, Facilities, and Programs; Geographic Information; High-Latitude Agriculture; High-Latitude Soils, Management of Ecosystems; Natural Resources Use and Allocation; Index to Reports -- Publications -- Facult

Life Cycle Assessment Tool for Food Supply Chain Environmental Evaluation

Food is at the centre of efforts to combat climate change, reduce water stress, pollution, and conserve the world’s wildlife. Assessing the environmental performance of food companies is essential to provide a comprehensive view of the production processes and gain insight into improvement options, but such a tool is currently non-existent in the literature. This study proposed a tool based on the life cycle assessment methodology focused on six stages of the food chain, raw materials acquisition, supplier, manufacturing, distribution, retail and wastes. The user can also evaluate the implementation of Internet of Things (IoT) technologies to reduce food waste applied in the real-world problems. The tool was validated through a case study of a food manufacturing company that prepares frozen meals via vending machines. The LCA results provided by the tool showed that food raw materials production is the main hotspot of nine impact categories. The IoT technologies’ contribution increased the company’s impact by around 0.4%. However, it is expected that employing these monitoring technologies would prevent food waste generation and the associated environmental impacts. Therefore, the results of this paper provide evidence that the proposed tool is suitable for determining environmental impacts and savings of food supply chain companies

Effect of curing conditions and harvesting stage of maturity on Ethiopian onion bulb drying properties

The study was conducted to investigate the impact of curing conditions and harvesting stageson the drying quality of onion bulbs. The onion bulbs (Bombay Red cultivar) were harvested at three harvesting stages (early, optimum, and late maturity) and cured at three different temperatures (30, 40 and 50 oC) and relative humidity (30, 50 and 70%). The results revealed that curing temperature, RH, and maturity stage had significant effects on all measuredattributesexcept total soluble solids

Definition and Application of a Computational Parameter for the Quantitative Production of Hydroponic Tomatoes Based on Artificial Neural Networks and Digital Image Processing.

This work presents an alternative method, referred to as Productivity Index or PI, to quan tify the production of hydroponic tomatoes using computer vision and neural networks, in contrast to other well-known metrics, such as weight and count. This new method also allows the automation of processes, such as tracking of tomato growth and quality control. To compute the PI, a series of computational processes are conducted to calculate the total pixel area of the displayed tomatoes and obtain a quantitative indicator of hydroponic crop production. Using the PI, it was possible to identify objects belonging to hydroponic tomatoes with an error rate of 1.07%. After the neural networks were trained, the PI was applied to a full crop season of hydroponic tomatoes to show the potential of the PI to monitor the growth and maturation of tomatoes using different dosages of nutrients. With the help of the PI, it was observed that a nutrient dosage diluted with 50% water shows no difference in yield when compared with the use of the same nutrient with no dilution.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Vegetable Crops

In ancient times, people benefited from ingesting different parts of various weeds (root, stem, shoot, leaf, flower, fruit, seed, etc.) to maintain a healthy life. People have obtained the vegetables we grow today by succeeding in cultivating these weeds. This book explains the health benefits of vegetable crops, organic vegetable growing, greenhouse management, and principles of irrigation management for vegetable crops

Postharvest losses along the cooking banana, potato and cassava fresh value chains in Uganda

Policy makers and development practitioners are challenged by the paucity of reliable data on the extent of postharvest losses (PHL) for devising suitable policies and strategies for their reduction. This study estimates PHL at different stages of the cooking banana, potato and cassava fresh value chains in Uganda by using cross-sectional data. A distinction was made between physical losses (product disappearing from the chain) and economic losses (partially deteriorated product sold at discounted price). Our findings indicate that the non-marketed output incurs very low physical losses (apart from potatoes, primarily during harvesting and storage) and, by definition, no economic losses. Conversely, substantial losses are found along the market chain. Physical losses affect about 30% of traded potatoes, followed by bananas (21%) and cassava (3%). However, the cassava value chain is characterized by much higher economic losses (about 47% of marketed roots sold at discount due to their rapid postharvest deterioration) than in the case of bananas and potatoes (10% and 8%, respectively). Overall, out of the total marketed output, 50% of cassava, 38% of potatoes and 30% of bananas incur either physical or economic losses. However, unlike banana and cassava that are mainly subsistence crops, potato in Uganda is primarily produced for the market. This results in a proportion of total potato production incurring PHL much higher (36%) than for banana and cassava (about 12%). Nevertheless, being its annual production enormous in the country, the quantity of bananas affected by PHL is about 7 and 25 times higher than the one of cassava and potato, respectively. Banana and cassava retailers - primarily women - are the value chain actors incurring the highest losses while, for potato, wholesalers are the most affected. Our findings contribute to policy prioritization and show that a diverse set of interventions is required to tackle PHL

Computer vision reading on stickers and direct part marking on horticultural products : challenges and possible solutions

Traceability of products from production to the consumer has led to a technological advancement in product identification. There has been development from the use of traditional one-dimensional barcodes (EAN-13, Code 128, etc.) to 2D (two-dimensional) barcodes such as QR (Quick Response) and Data Matrix codes. Over the last two decades there has been an increased use of Radio Frequency Identification (RFID) and Direct Part Marking (DPM) using lasers for product identification in agriculture. However, in agriculture there are still considerable challenges to adopting barcodes, RFID and DPM technologies, unlike in industry where these technologies have been very successful. This study was divided into three main objectives. Firstly, determination of the effect of speed, dirt, moisture and bar width on barcode detection was carried out both in the laboratory and a flower producing company, Brandkamp GmbH. This study developed algorithms for automation and detection of Code 128 barcodes under rough production conditions. Secondly, investigations were carried out on the effect of low laser marking energy on barcode size, print growth, colour and contrast on decoding 2D Data Matrix codes printed directly on apples. Three different apple varieties (Golden Delicious, Kanzi and Red Jonaprince) were marked with various levels of energy and different barcode sizes. Image processing using Halcon 11.0.1 (MvTec) was used to evaluate the markings on the apples. Finally, the third objective was to evaluate both algorithms for 1D and 2D barcodes. According to the results, increasing the speed and angle of inclination of the barcode decreased barcode recognition. Also, increasing the dirt on the surface of the barcode resulted in decreasing the successful detection of those barcodes. However, there was 100% detection of the Code 128 barcode at the company’s production speed (0.15 m/s) with the proposed algorithm. Overall, the results from the company showed that the image-based system has a future prospect for automation in horticultural production systems. It overcomes the problem of using laser barcode readers. The results for apples showed that laser energy, barcode size, print growth, type of product, contrast between the markings and the colour of the products, the inertia of the laser system and the days of storage all singularly or in combination with each other influence the readability of laser Data Matrix codes and implementation on apples. There was poor detection of the Data Matrix code on Kanzi and Red Jonaprince due to the poor contrast between the markings on their skins. The proposed algorithm is currently working successfully on Golden Delicious with 100% detection for 10 days using energy 0.108 J mm-2 and a barcode size of 10 × 10 mm2. This shows that there is a future prospect of not only marking barcodes on apples but also on other agricultural products for real time production