Multivariate NIR studies of seed-water interaction in Scots Pine Seeds (Pinus sylvestris L.)

This thesis describes seed-water interaction using near infrared (NIR) spectroscopy, multivariate regression models and Scots pine seeds. The presented research covers classification of seed viability, prediction of seed moisture content, selection of NIR wavelengths and interpretation of seed-water interaction modelled and analysed by principal component analysis, ordinary least squares (OLS), partial least squares (PLS), bi-orthogonal least squares (BPLS) and genetic algorithms. The potential of using multivariate NIR calibration models for seed classification was demonstrated using filled viable and non-viable seeds that could be separated with an accuracy of 98-99%. It was also shown that multivariate NIR calibration models gave low errors (0.7% and 1.9%) in prediction of seed moisture content for bulk seed and single seeds, respectively, using either NIR reflectance or transmittance spectroscopy. Genetic algorithms selected three to eight wavelength bands in the NIR region and these narrow bands gave about the same prediction of seed moisture content (0.6% and 1.7%) as using the whole NIR interval in the PLS regression models. The selected regions were simulated as NIR filters in OLS regression resulting in predictions of the same quality (0.7 % and 2.1%). This finding opens possibilities to apply NIR sensors in fast and simple spectrometers for the determination of seed moisture content. Near infrared (NIR) radiation interacts with overtones of vibrating bonds in polar molecules. The resulting spectra contain chemical and physical information. This offers good possibilities to measure seed-water interactions, but also to interpret processes within seeds. It is shown that seed-water interaction involves both transitions and changes mainly in covalent bonds of O-H, C-H, C=O and N-H emanating from ongoing physiological processes like seed respiration and protein metabolism. I propose that BPLS analysis that has orthonormal loadings and orthogonal scores giving the same predictions as using conventional PLS regression, should be used as a standard to harmonise the interpretation of NIR spectra

Multispectral Method for Apple Defect Detection using Hyperspectral Imaging System

Hyperspectral imaging is a non-destructive detection technology and a powerful analytical tool that integrates conventional imaging and spectroscopy to get both spatial and spectral information from the objects for food safety and quality analysis. A recently developed hyperspectral imaging system was used to investigate the wavelength between 530nm and 835nm to detect defects on Red Delicious apples. The combination of band ratio method and relative intensity method were developed in this paper, which using the multispectral wavebands selected from hyperspectral images. The results showed that the hyperspectral imaging system with the properly developed multispectral method could generally identify 95% of the defects on apple surface accurately. The developed algorithms could help enhance food safety and protect public health while reducing human error and labor cost for food industr

Coal industry in the context of Ukraine economic security

Purpose. To rate the main factors and indicators of the national economic security, in particular the degree of the country’s provision with primary natural resources which determine the global energy consumption trends. Methods. Analysis of components comprising the fuel and energy complex of Ukraine in view of survivability and heuristic algorithm for finding economically feasible reserves. The problem of finding the optimal flow distribution is solved by graphs. Findings. Emergencies are ranked in the descending order of optimal flows in the normal mode, the sorting sequence is defined, which results in the optimal solution via a minimum number of the algorithm computational steps. Originality. A universal algorithm for the development of fuel and energy complex of Ukraine has been designed. Practical implications. It was found that the vitality of integrated energy systems can be defined as the property to resist a large scale external disturbance, maintaining the ability to operate with acceptable performance and backup indicators. When considering large energy systems, the levels of the industry reserve can be reduced due to interchangeability of energy resources.Мета. Оцінити головні чинники та індикатори національної економічної безпеки, зокрема ступеня забезпеченості країни основними природними ресурсами, які зумовлюють тенденції світового енергоспоживання. Методика. Проведено аналіз елементів паливно-енергетичного комплексу України з урахуванням живучості та евристичний алгоритм знаходження економічно обґрунтованого резерву. Завдання знаходження оптимального потокорозподілення вирішене методом графів. Результати. Проранжовані аварійні ситуації у порядку зменшення величини оптимальних потоків у нормальному режимі, визначено послідовність перебору, що призводить за мінімальне число кроків обчислювального алгоритму до оптимального рішення. Наукова новизна. Розроблено універсальний алгоритм розвитку паливно-енергетичного комплексу України. Практична значимість. Встановлено, що живучість інтегрованих систем енергетики можна визначити як властивість протистояти великомасштабним зовнішнім обуренням, зберігаючи здатність функціонувати із допустимими показниками ефективності та резервування. При розгляді суттєвих енергетичних систем рівні галузевого резерву можуть знижуватися за рахунок взаємозамінності енергетичних ресурсів.Цель. Оценить главные факторы и индикаторы национальной экономической безопасности, в частности степени обеспеченности страны основными природными ресурсами, обуславливающими тенденции мирового энергопотребления. Методика. Произведен анализ элементов топливно-энергетического комплекса Украины с учетом живучести и эвристический алгоритм нахождения экономически обоснованного резерва. Задача нахождения оптимального потокораспределения решена методом графов. Результаты. Проранжированы аварийные ситуации в порядке убывания величины оптимальных потоков в нормальном режиме, определена последовательность перебора, что приводит за минимальное число шагов вычислительного алгоритма к оптимальному решению. Научная новизна. Разработан универсальный алгоритм развития топливно-энергетического комплекса Украины. Практическая значимость. Установлено, что живучесть интегрированных систем энергетики можно определить как свойство противостоять крупномасштабным внешним возмущением, сохраняя способность функционировать с допустимыми показателями эффективности и резервирования. При рассмотрении крупных энергетических систем уровни отраслевого резерва могут снижаться за счет взаимозаменяемости энергетических ресурсов.The authors express their gratitude to Laureate of National Prize of Ukraine, Doctor of Technical Sciences, Professor, Head of the Underground Mining Department, Volodymyr Bondarenko for his guidance while performing work on this topic

Hyperspectral Imaging and Their Applications in the Nondestructive Quality Assessment of Fruits and Vegetables

Over the past decade, hyperspectral imaging has been rapidly developing and widely used as an emerging scientific tool in nondestructive fruit and vegetable quality assessment. Hyperspectral imaging technique integrates both the imaging and spectroscopic techniques into one system, and it can acquire a set of monochromatic images at almost continuous hundreds of thousands of wavelengths. Many researches based on spatial image and/or spectral image processing and analysis have been published proposing the use of hyperspectral imaging technique in the field of quality assessment of fruits and vegetables. This chapter presents a detailed overview of the introduction, latest developments and applications of hyperspectral imaging in the nondestructive assessment of fruits and vegetables. Additionally, the principal components, basic theories, and corresponding processing and analytical methods are also reported in this chapter

Artificial Intelligence : Implications for the Agri-Food Sector

Artificial intelligence (AI) involves the development of algorithms and computational models that enable machines to process and analyze large amounts of data, identify patterns and relationships, and make predictions or decisions based on that analysis. AI has become increasingly pervasive across a wide range of industries and sectors, with healthcare, finance, transportation, manufacturing, retail, education, and agriculture are a few examples to mention. As AI technology continues to advance, it is expected to have an even greater impact on industries in the future. For instance, AI is being increasingly used in the agri-food sector to improve productivity, efficiency, and sustainability. It has the potential to revolutionize the agri-food sector in several ways, including but not limited to precision agriculture, crop monitoring, predictive analytics, supply chain optimization, food processing, quality control, personalized nutrition, and food safety. This review emphasizes how recent developments in AI technology have transformed the agri-food sector by improving efficiency, reducing waste, and enhancing food safety and quality, providing particular examples. Furthermore, the challenges, limitations, and future prospects of AI in the field of food and agriculture are summarized