Fruit ripeness classification: A survey

Fruit is a key crop in worldwide agriculture feeding millions of people. The standard supply chain of fruit products involves quality checks to guarantee freshness, taste, and, most of all, safety. An important factor that determines fruit quality is its stage of ripening. This is usually manually classified by field experts, making it a labor-intensive and error-prone process. Thus, there is an arising need for automation in fruit ripeness classification. Many automatic methods have been proposed that employ a variety of feature descriptors for the food item to be graded. Machine learning and deep learning techniques dominate the top-performing methods. Furthermore, deep learning can operate on raw data and thus relieve the users from having to compute complex engineered features, which are often crop-specific. In this survey, we review the latest methods proposed in the literature to automatize fruit ripeness classification, highlighting the most common feature descriptors they operate on

Physiology and Biochemistry of Cold-hardy Table Grapevines

Grapes are grown worldwide to produce wine, grape juice and are also popular as fresh table grapes or dried raisins. Due to their nutritional value and importance in the multibillion-dollar wine industry, grapes are considered the most commercially important berry crop. Grape production has primarily concentrated on European wine grapes, Vitis vinifera, in the dry, hot Mediterranean and Central Asian climates. V. vinifera is not cold tolerant enough to endure winter temperatures below -15°C. The introduction of several interspecific hybrids (of both wine and table grape) cultivars in the 20th century and selection of a training system has helped propel the expansion of grapevine cultivation in cooler climates such as the Northeastern US and upper midwestern US states. Training and trellising systems are part of viticultural practices that influence many aspects of grapevine growth and productivity. Especially in cool climates like New Hampshire, choosing an appropriate training system will provide the grapevines with good exposure of leaves and berries to sunlight leading to fruits with improved berry composition and higher levels of sugar accumulation as well as increased concentrations of anthocyanins and phenolic compounds. However, there is limited research on the impact of training systems on cold-hardy table grapevine physiology and biochemistry. To address these knowledge gaps research was conducted at the UNH Woodman Horticultural Research Farm in Durham, NH, where cold-hardy grape varieties are growing on two different training systems. Mars and Canadice grape varieties grown on vertical shoot positioning (VSP) and Munson (M) training systems were used. Grapevine physiology and biochemistry were followed throughout three growing seasons using destructive and non-destructive methods to monitor grapevine health. Additionally, considering the current need for alternative environmentally friendly fungicides, plant material from these cold-hardy grape cultivars was tested for their putative antifungal properties. The objectives of this study were to: (1) Determine the physiological and biochemical parameters of Canadice and Mars cold-hardy grape varieties growing on vertical shoot positioning (VSP) and Munson training systems, and (2) Investigate the putative antifungal activity of field-collected grapevine leaves and cell suspension cultures obtained from Canadice and Mars grapevines against Botrytis cinerea. I hypothesized that the training system would influence the SPAD measurements, spectral indices (normalized difference vegetation index, red edge inflection point, moisture stress index, and phenology index), and gas exchange measurements (intercellular carbon dioxide concentration, stomatal conductance, net photosynthesis, transpiration rate, vapor pressure deficit, and water use efficiency) of Mars and Canadice leaves growing on two different training systems. I also hypothesized that the training system would have an effect on the amount of leaf photosynthetic pigments, leaf, juice, and skin metabolomes, titratable acidity and soluble solid contents of Canadice and Mars growing on two different training systems (Chapter 2). I hypothesized that field-collected leaves and cell suspension cultures established from Canadice and Mars grape varieties would contain compounds with antifungal activity against B. cinerea (Chapter 3). For objective 1, physiological parameters were measured with SPAD, spectral analysis, and gas exchange analysis on grapevine leaves throughout three growing seasons (2019, 2020, and 2021). Specifically, I determined the SPAD measurements, the spectral indices normalized difference vegetation index (NDVI), red edge inflection point (REIP), moisture stress index (MSI) and phenology index, and gas exchange measurements to determine intercellular carbon dioxide concentration (Ci), stomatal conductance (gs), vapor pressure deficit (VPD), net photosynthesis (A), transpiration (E), and water use efficiency (WUE). While no differences were found regarding training systems alone, there was a significant interaction of training system with time, suggesting that training system had different effects at different times. For the biochemical parameters, the same leaves that were used to perform SPAD measurements were used to analyze photosynthetic pigments and proton based nuclear magnetic resonance (1H-NMR spectroscopy)-based metabolomics. Consistent with the results of physiological parameters, no differences were found for photosynthetic pigments - chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids - between training systems, but the training system had different effects at different time points. The leaf metabolites studied using 1H-NMR spectroscopy coupled with multivariate statistical analysis did not distinguish samples based on training systems, but sample separation occurred based on phenological stages. The compounds identified showed variations between flowering, veraison, and harvest. Namely, sucrose gradually increased from flowering to harvest. Additionally, the 1H-NMR spectroscopy-based metabolome of grape juice was investigated in grape berries collected from veraison to harvest. Various kinds of metabolites were identified. Fructose, glucose, alanine, threonine, myo-Inositol, and 3-hydroxybutyrate were all shown to increase from veraison to harvest. The amount of fructose and glucose increased over time (between veraison and harvest) and are indicators of berry ripeness. Furthermore, at harvest, grape titratable acidity and total soluble solid content were determined, and berry skin composition was investigated using ultra performance liquid chromatography-mass spectrometry (UPLC-MS) analysis. Distinct sets of metabolites were identified in Mars and Canadice skin samples and were dependent on the training system. For my objective 2, I investigated the putative antifungal activity of Mars- and Canadice-derived products, specifically field-collected grapevine senescent leaves and cell suspension cultures, against B. cinerea. The aim was to gather knowledge that could lead to the development of new botanical fungicides that could be used as an alternative to synthetic fungicides for disease management in vineyards. This approach could contribute to sustainable management practices in the long term. Using grapevine debris (such as canes, wood, and leaves) from V. vinifera to suppress B. cinerea and other plant pathogens has been successfully demonstrated. However, there is limited research evaluating secondary metabolites with antifungal properties from cold-hardy grapevines. Our results show that grapevine-derived extracts have antifungal activity in vitro and in detached berry experiments when challenged with B. cinerea, but the antifungal activity was not translated to in planta experiments. The metabolic profiling of senescent leaves and cell suspension cultures of Mars and Canadice identified an array of compounds, including some reported to have antimicrobial properties. Given the list of compounds that have been identified in cold-hardy grapevine-derived products, future work should examine these unique compounds present in the senescent leaves and cell cultures under controlled experimental conditions. While our results indicated that Mars- and Canadice-derived products have antifungal activity, the materials used in this study were crude extracts. Future studies should focus on using finer grapevine-products to test the efficacy against B. cinerea, not only in vitro, but also using pilot-scale greenhouse trials, and vineyard trials

OCM 2013 - Optical Characterization of Materials - conference proceedings

The state of the art in optical characterization of materials is advancing rapidly. New insights into the theoretical foundations of this research field have been gained and exciting practical developments have taken place, both driven by novel applications that are constantly emerging. This book presents latest research results in the domain of Characterization of Materials by spectral characteristics of UV (240 nm) to IR (14 µm), multispectral image analysis, X-Ray, polarimetry and microscopy

OCM 2013 - 1st International Conference on Optical Characterization of Materials: March 6th - 7th, 2013, Karlsruhe, Germany

The state of the art in optical characterization of materials is advancing rapidly. New insights into the theoretical foundations of this research field have been gained and exciting practical developments have taken place, both driven by novel applications that are constantly emerging. This book presents latest research results in the domain of Characterization of Materials by spectral characteristics of UV (240 nm) to IR (14 µm), multispectral image analysis, X-Ray, polarimetry and microscopy

Grapes and Wine

Grape and Wine is a collective book composed of 18 chapters that address different issues related to the technological and biotechnological management of vineyards and winemaking. It focuses on recent advances, hot topics and recurrent problems in the wine industry and aims to be helpful for the wine sector. Topics covered include pest control, pesticide management, the use of innovative technologies and biotechnologies such as non-thermal processes, gene editing and use of non-Saccharomyces, the management of instabilities such as protein haze and off-flavors such as light struck or TCAs, the use of big data technologies, and many other key concepts that make this book a powerful reference in grape and wine production. The chapters have been written by experts from universities and research centers of 9 countries, thus representing knowledge, research and know-how of many regions worldwide

Incorporating standardised drift-tube ion mobility to enhance non-targeted assessment of the wine metabolome (LC×IM-MS)

Liquid chromatography with drift-tube ion mobility spectrometry-mass spectrometry (LCxIM-MS) is emerging as a powerful addition to existing LC-MS workflows for addressing a diverse range of metabolomics-related questions [1,2]. Importantly, excellent precision under repeatability and reproducibility conditions of drift-tube IM separations [3] supports the development of non-targeted approaches for complex metabolome assessment such as wine characterisation [4]. In this work, fundamentals of this new analytical metabolomics approach are introduced and application to the analysis of 90 authentic red and white wine samples originating from Macedonia is presented. Following measurements, intersample alignment of metabolites using non-targeted extraction and three-dimensional alignment of molecular features (retention time, collision cross section, and high-resolution mass spectra) provides confidence for metabolite identity confirmation. Applying a fingerprinting metabolomics workflow allows statistical assessment of the influence of geographic region, variety, and age. This approach is a state-of-the-art tool to assess wine chemodiversity and is particularly beneficial for the discovery of wine biomarkers and establishing product authenticity based on development of fingerprint libraries

PHYSIOLOGICAL RESPONSES OF WHITE GRAPE BERRIES TO SUNLIGHT EXPOSURE

Reflectance spectroscopy was used in 2013, to investigate about varietal behaviors to different agronomics condition: (i) composition and quantification of pigments by using non-invasive method; (ii) photosynthetic pigments assessment by new reflectance indices (iii) how different microclimatic bunch conditions could affect the appearance of sunburn. The experiment was performed in the Regional Research Station of Riccagioia (Lombardy region, Northern Italy), at the University of Milan, on 16 white grape accessions, during 3 phenological stages: pre-veraison (77 BBCH), veraison (81 BBCH) and harvest (89 BBCH). New specific indices for the evaluation and estimation of photosynthetic pigments were proposed on the basis of grape berry reflectance spectra. Validations with classical extraction analysis were done. About 200 berries were analyzed (over 1000 reflectance spectra were collected). First the chlorophyll a and b absorption maxima in the reflectance spectra were established: 675 and 650 nm respectively. These new equations are also able to discriminate between chlorophyll a and b. Indeed, the wavelengths of major interest for their absorption detection were identified. If chlorophyll quantifications were achieved directly from reflectance spectra, for carotenoids the absorption bands did not allow good reflectance correlations. Nonetheless, thanks to the physiological relation of photosynthetic pigments, the chlorophyll/carotenoid ratio was used to estimate carotenoid content. Because their proportion changes during berry development, the index coefficients can be adapted in relation to the BBCH phenological stage. These indices demonstrated good correlations with the destructive quantifications. Also, the degradation intensity of the chlorophyll was different from that of the carotenoid during maturation, leading to a change in their absorption proportion throughout ripening. This finding allows suggesting that in white berries, the colour change during berry development is not related to the activation of a specific biosynthetic pathway, but is mostly the result of catabolic processes. Chardonnay and Riesling showed different susceptibility to sunburn. The results suggest that for each variety, the timing of leaf removal during the day is fundamental to reducing the appearance of brown color in the berry skin. In Chardonnay it would be better to avoid any leaf removal especially in pre-veraison, in the morning. Because Riesling was more susceptible during the afternoon, it would be recommendable to remove leaves, if necessary, during the early morning. The aims of the last two years (2014-2015) data collection were: (i) to evaluate phenolics in Riesling and Chardonnay berries in response to sunlight exposure under different irrigation regimes; (ii) to study the relation of water stress to sunburn appearance. The experiment was carried out in the Columbia Crest vineyards (Columbia Valley, Washington State, USA). Chardonnay and Riesling berries were collected from two different vineyards. Two different irrigation regimes were applied in both vineyards. Full irrigation (FI): vines were irrigated to replace 100% crop evapotranspiration, from fruit set to harvest, with no water stress imposed. Deficit irrigation (DI): vines were irrigated to maintain a moderate water stress (stem water potential (\uf059stem) at midday between -0.7 and -1 MPa) from fruit set to harvest. For compositional analysis two cluster exposures were considered: one exposed to direct sunlight (sun), and the other totally shaded from sunlight (shade). Skin flavonol, flavan3ol and proanthocyanidin content were analysed by HPLC methods. Total tannins were measured by spectrophotometer. Six temperature/light sensors per irrigation treatment were randomly installed on 3 sun and 3 shade bunches. In terms of absolute concentration in both varieties, several statistical tests indicate greater amount of variance accounted for by the effect exposure and phenological stages, and their interaction. No effect was due to the irrigation, in both varieties. Chardonnay had much higher flavanol concentration than Riesling. Chardonnay had much higher flavanols in the pre- veraison than during ripening. In Chardonnay the amount of monomers, dimers, trimers and polymers was greater in sun exposed berries than in shaded berries. Unlike in Chardonnay, in Riesling no flavan3ols monomers were detected by HPLC during the pre-veraison and veraison. In Riesling the amount of monomers, dimers and trimers was greater in sun exposed berries than in shaded berries. In both varieties flavonol concentrations were much higher in sun exposed berries than in shaded berries, with absolute much higher concentration in Chardonnay. Flavonols increased during ripening, especially in the sun in both Chardonnay and Riesling. Under similar light conditions the difference in temperature within the two irrigation treatments in the sun, could be due to the less vigorous canopy of DI plants compared with FI plants, which overall lead to greater cluster exposure, in both varieties. Nonetheless, the temperatures were always lower in FI and higher in DI, supporting the hypothesis of a possible no (or little) effect on flavonol biosynthesis. Shaded-bunch temperatures were always lower as compared to sun exposed ones, as direct solar heating did not occur in the shaded-conditions

Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems

The implementation of artificial intelligence (AI), together with robotics, sensors, sensor networks, Internet of Things (IoT), and machine/deep learning modeling, has reached the forefront of research activities, moving towards the goal of increasing the efficiency in a multitude of applications and purposes related to environmental sciences. The development and deployment of AI tools requires specific considerations, approaches, and methodologies for their effective and accurate applications. This Special Issue focused on the applications of AI to environmental systems related to hazard assessment in urban, agriculture, and forestry areas