Vegetation Categories Research Articles

The potential of sentinel-1 InSAR coherence for grasslands monitoring in Eastern Cape, South Africa

This study evaluates the potential of the repeat-pass synthetic aperture radar interferometry (InSAR) coherence for grasslands monitoring in Eastern Cape Province, in South Africa. We used 12 pairs of InSAR data in the Interferometric Wide swath mode (IW), in VV-polarization (with different spatial baseline B⊥ and different temporal repeat intervals between the subsequent acquisitions), covering grasslands in the study area during two growing seasons; drought season (2015/2016) and non-drought season (2016/2017). Results show that non-drought season has higher variability in the coherence between the different regions of interest (ROIs) than the drought season and higher variability in the backscattering coefficient. Based on our results, we conclude that InSAR-based data have shown potential for grasslands monitoring, and the regularity of Sentinel-1 data is well suited for InSAR applications. However, the potential to separate grasslands from other vegetation categories appears to be limited with longer temporal baselines of 12 days intervals using only Sentinel-1A data. This potential will be improved with the 6 days intervals that will become available with Sentinel-1B in the study area.

Study on SDE Distribution of Forest Vegetation in China Based on Trapezoidal Grid Segmentation

The trapezoidal grid segmentation of China was carried out at a scale of 1:10000 to form a grid system covering the Chinese mainland. Based on the standard deviation ellipse (SDE) distribution theory, seven major categories and 53 sub-categories of Chinese forest vegetation were studied respectively. The SDE distribution was obtained and the average area distribution rate of 51.75% major-category vegetation was also obtained. Broad-leaved forests and sparse forests accounted for the largest proportion in China, with a proportion of 68.11%, the deviation rate of the average was 31.61%, and the dispersion was 0.097; the average distribution rate of sub-category vegetation was 9.38%, and the temperate subalpine evergreen coniferous forests accounted for the largest proportion in China, with a distribution rate of 30.23% and a dispersion of 0.032. The spatial distribution pattern of vegetation is mostly "southwest-northeast", but the elliptical center of the major-category vegetation moves more; while in terms of the direction of sub-category vegetation, there were nine categories of vegetation with three long-axis azimuths [<45 degrees], 27 categories of vegetation with long-axis azimuth [>45°∪≤90°], and 27 categories of vegetation with long-axis azimuth [> 90°].

Examining Front-of-Package Product Names and Ingredient Lists of Infant and Toddler Food Containing Vegetables

ObjectiveTo investigate the alignment between vegetables and fruits listed in the ingredients of commercially produced infant and toddler food (ITF) and inclusion in front-of-package product names. DesignA database of commercial ITF containing vegetables (n = 548) was created. Inclusion of each vegetable or fruit in the product name (yes/no), form (ie, whole/puree, juice/juice concentrate, etc), and ingredient list position (ie, first, second) were recorded. Vegetables were classified per US Department of Agriculture categories; fruits were classified into 2 categories. AnalysisChi-square tests of association tested associations between product name inclusion and (1) vegetable and fruit category, (2) form, and (3) form by category. ResultsAssociations were observed between vegetable and fruit categories and inclusion in product names [χ2 (6, N = 1,462) = 70.3, P < 0.001]. Vegetables in the US Department of Agriculture dark green category were more likely to appear in product names (94%; standardized residual [SR] = 2.1), as were other vegetables (62%; SR = 4.9). Vegetable and fruit forms were associated with inclusion in product name [χ2 (4, N = 1,462) = 206.6, P < 0.001]. Juice/juice concentrates were less likely to be included in names (32.4%; SR = −5.4). Conclusions and ImplicationsSubstantial discrepancies exist between ITF ingredient lists and front-of-package product names. When only front-of-package information informs purchases, caregivers may not be purchasing products that facilitate children's building of vegetable preferences.

The role of emerging micro-scale vegetables in human diet and health benefits-an updated review based on microgreens.

Increasing public concern about health has prompted humans to find new sources of food. Microgreens are young and immature plants that have been recently introduced as a new category of vegetables, adapting their production at the micro-scale. In this paper, the chemical compositions including micro-nutrients and some typical phytochemicals of microgreens are summarized. Their edible safety and potential health benefits are also reviewed. Microgreens play an increasingly vital role in health-promoting diets. They are considered good sources of nutritional and bioactive compounds, and show potential in the prevention of malnutrition and chronic diseases. Some strategies in the pre- or post-harvest stages of microgreens can be further applied to obtain better nutritional, functional, and sensorial quality with freshness and extended shelf life. This review provides valuable nutrient data and health information for microgreens, laying a theoretical foundation for people to consume microgreens more wisely, and providing great value for the development of functional products with microgreens.

Detection of various categories of fruits and vegetables through various descriptors using machine learning techniques

An accurate and efficient recognition system for fruits and vegetables is one major challenge. To solve this challenge, we have examined various feature descriptors based on colour and texture such as RGB, CMH, CCV, CDH, LBP, CSLBP and SEH. All process of proposed framework consists three phase: 1) background subtraction; 2) feature extraction; 3) training and classification. In this paper, Otsu's thresholding is used for background subtraction. Further all segmented image is used in the feature extraction phase. Finally, C4.5 and KNN is used for training and classification. The various performances metric such as CA, precision, recall, F-measure, MCC, PRC and FPR are used to evaluate the proposed system for recognition problem. We also analysed the performance accuracy of both classifiers. In that C4.5 and KNN classifier produce CA values of 94.63% and 90.25%, respectively.

Detection of various categories of fruits and vegetables through various descriptors using machine learning techniques

Detection of various categories of fruits and vegetables through various descriptors using machine learning techniques

Ethanol pretreatment in taioba leaves during vacuum drying

ABSTRACT Non-conventional vegetables are those with limited distribution, restricted to certain regions. As a globalization and food industrialization result, its cultivation and consumption has decreased. The taioba [Xanthosoma sagittifolium (L.) Schott] is an example of this vegetable category. The drying process increases the food stability, but it can negatively alter the nutritional value and the final quality of the product. Ethanol pretreatment reduces the drying time and can assist in the preservation of the nutritional characteristics. The aim of this work was to evaluate the effect of vacuum drying and ethanol pretreatment on the drying behavior, mathematical modeling, and final quality of taioba leaves. Higher temperatures and ethanol pretreatment lead to a shorter drying time. Thin-layer equations were evaluated for their ability to predict the drying kinetics, of which the Logarithmic and Midilli &amp; Kuçuk equations performed best. A significant difference (p ≤ 0.05) was observed in the ascorbic acid content, antioxidant activity and total phenolic compounds in the different treatments. There was preservation in ascorbic acid content in treatments in which ethanol was applied; moreover, lower total phenolic compounds and antioxidant activity were observed when ethanol was used. There was no significant difference (p &gt; 0.05) in pH values and titratable acidity.

Is it possible to obtain food consumption information through children's drawings? Comparison with the Free Listing

The aims of this research were 1) to study the children's drawings to obtain scientific information about food consumption; 2) to compare this method with an existing one (Free Listing); and 3) to compare fruits- and vegetables-consumed by children of different cultural groups within a same country. Children (n = 105) from two Argentinian cities (Salta in the northwest and 9 de Julio in the Pampean region), reported the fruits and vegetables they consumed, with the Free Listing and the new Free Drawing methods. Contingency tables were built and cognitive saliency indexes (CSI) were calculated. Children evoked 57 fruits and 54 vegetables by both methods, which were then grouped into 31 fruit and 27 vegetable categories. The advantages and limitations of the methods are discussed. Throughout Free Drawing, each food was defined by its name, shape and colour, which allowed better discrimination between varieties. Children from Salta reported consuming more fruits (63.7%) and vegetables (68.6%) than those from 9 de Julio (p < 0.05). Differences between cultural groups were found in 10 fruits and 7 vegetables, mentioned more frequently in Salta, where regional crops arose principally by Free Listing. The CSI did not depend on the method used but, for vegetables, they were affected by the cultural group. The fruits with the greatest CSI were banana and apples followed by orange (CSI≥0.19). Tomatoes, carrot and pumpkins showed the highest CSI in 9 de Julio; while carrot, tomatoes, varieties of lettuce and potatoes had the highest CSI in Salta (0.17 ≤ CSI≤0.33). Free Drawing is a qualitative alternative to study food consumption in children populations through a fun activity without the need for assistants.

3D food printing of fresh vegetables using food hydrocolloids for dysphagic patients

Three-dimensional food printing (3DFP) leads to advances in digital gastronomy by targeting consumers’ specific requirements for nutrition customization and visual appeal. Dysphagia, or difficulty swallowing, is prevalent in elderly people and patients suffering from debilitating illnesses. Dysphagic diets require textural modifications to render them soft and safe to swallow. Diets must be visually pleasing to enable a greater food uptake to prevent malnutrition in patients. 3DFP so far has mainly utilized freeze-dried vegetable powders for shaping 3D designs. Our work focuses on fresh and frozen vegetables having better nutritional profile and low costs. Three different categories of vegetables are identified based on the number of hydrocolloids required to render them printable. Garden pea, carrot and bok choy are chosen as representatives in each category, which requires no HC, one type of HC and two types of HCs, respectively. Food inks are prepared by the addition of HCs i.e. xanthan gum (XG), kappa carrageenan (KC) and locust bean gum (LBG) for texture modification. Rheological, textural, microstructural and syneresis properties of the inks are examined. International dysphagia diet standardisation initiative (IDDSI) tests are done to assess the potential of the inks for dysphagic diets. Optimized ink formulations display excellent 3D printability, minimal water seepage, and dense microstructures with minimal amount of HCs. Using fresh vegetables instead of freeze-dried foods serves the purpose of preserving flavour and nutrition like real food. This in turn may bring 3DFP closer to the hospital and nursing home kitchens.

Assessment of Landscape Change of Lesser Himalayan Road Corridor of Uttarakhand, India

Abstract The spatio-temporal monitoring and understanding of the pattern of land-use and land-cover (LULC) change in the Himalayas are essential for sustainable development, especially from environmental planning and management perspective. The increasing anthropogenic activities and climate change in the Siwalik and Lesser Himalayas have substantially experienced rapid change in the natural landscape; however, detailed investigation and documentation of such observed changes are limited. This study aims to assess the LULC changes along the Kalsi-Chakrata road corridor located in the Lesser Himalayan region of Uttarakhand state of India using remote sensing and geographic information system (GIS) for the periods 2000-2010 and 2010-2019. The LULC maps were generated from multi-temporal satellite images of the Landsat -7 Enhanced Thematic Mapper Plus (ETM+) series for 2000 and 2010, and the Linear Imaging Self-Scanning System IV (LISS IV) images from Resourcesat-1 for 2019. The extent of spatial landscape changes occurred in different LULC classes was performed through the cross-tabulation change matrix in the GIS module up to the individual village level. The results indicate that the forest cover of the area was intensively converted to open areas, sparse vegetation, and different land-use categories. These included agricultural land, built-up areas, and decreased from 47.27 % in 2000 to 36.66 % in 2019. During the same period, the open areas and agricultural areas were increased by 15.86 % and 4.49 %, respectively. Moreover, the built-up areas (both urban and rural settlements) were progressively increased from 0.33% in 2000 to 0.56 % in 2019. The conversion of forests and sparsely vegetative areas to agricultural land and rural settlements is closely associated with the increasing anthropogenic activities due to population growth, tourism, movement of heavy vehicles for mining and other economic activities. The changes in land-cover to land use classes are more prominent in Samalta Dadauli, Nithala, Bhugtari, and Udapalta villages located between Kalsi and Sahiya town. The reported maximum transition of forest areas into the open area, agricultural land, and sparse vegetation indicates the possible scarcity of water, which could link with the incidence of climatic or seasonal variation in the Lesser Himalayan terrain to the hydro-geomorphic and anthropogenic processes. The trend in LULC change at the village level gave the insight to help to prioritize future mitigation planning and sustainable development that are exceedingly convenient for the planners, policymakers, and local authorities for comprehensive forest management, biodiversity strategies, and necessary conservation

Acceptability and Antioxidant Activity Level of Shredded Banana Flower-Chicken Meat

Background: Data Riskesdas 2013 shows that the average amount portion of vegetable consumption in people aged 10 years or older is only 0.5 portions while the vegetable consumption category is said to be "sufficient" is at least 5 portions per day for 7 days a week. Banana blossom is a vegetable and commonly found in Bangka Belitung Islands Province. Banana blossom processing as a source of vegetables rich in antioxidant compounds and chicken meat as a source of animal protein, needs to be done by processing into shredded banana blossom-chicken meat.Objectives: To determine the acceptability and antioxidant activity level of shredded banana blossom-chicken meat.Methods: This research is true experimental. Shredded banana blossom-chicken meat, made using 3 treatment, banana blossom 75%:chicken meat 25% (F1), banana blossom 50%: chicken meat 50% (F2), and banana blossom 25%:chicken meat 75% (F3). Furthermore, the acceptance of taste, colour, aroma, texture, overall, and antioxidant activity level of shredded banana blossom-chicken meat. Results: There was a significant difference in the acceptance of the colours of shredded F1, F2 and F3 (p = 0,00), while aroma, taste, texture and overall of the shredded F1, F2 and F3 were not significant (p&gt; 0.05). Shredded F3 (banana blossom 25%: chicken meat 75%) is most preferred based on the parameters of colour, aroma, taste, texture and overall, and has the highest antioxidant activity value are 53.74%.Conclusions: Shredded banana blossom-chicken meat has a good acceptability and has a high antioxidant activity level.[AN1]

Hierarchical Geographic Object-Based Vegetation Type Extraction Based on Multi-Source Remote Sensing Data

Providing vegetation type information with accurate surface distribution is one of the important tasks of remote sensing of the ecological environment. Many studies have explored ecosystem structure information at specific spatial scales based on specific remote sensing data, but it is still rare to extract vegetation information at various landscape levels from a variety of remote sensing data. Based on Gaofen-1 satellite (GF-1) Wide-Field-View (WFV) data (16 m), Ziyuan-3 satellite (ZY-3) and airborne LiDAR data, this study comparatively analyzed the four levels of vegetation information by using the geographic object-based image analysis method (GEOBIA) on the typical natural secondary forest in Northeast China. The four levels of vegetation information include vegetation/non-vegetation (L1), vegetation type (L2), forest type (L3) and canopy and canopy gap (L4). The results showed that vegetation height and density provided by airborne LiDAR data could extract vegetation features and categories more effectively than the spectral information provided by GF-1 and ZY-3 images. Only 0.5 m LiDAR data can extract four levels of vegetation information (L1–L4); and from L1 to L4, the total accuracy of the classification decreased orderly 98%, 93%, 80% and 69%. Comparing with 2.1 m ZY-3, the total classification accuracy of L1, L2 and L3 extracted by 2.1 m LiDAR data increased by 3%, 17% and 43%, respectively. At the vegetation/non-vegetation level, the spatial resolution of data plays a leading role, and the data types used at the vegetation type and forest type level become the main influencing factors. This study will provide reference for data selection and mapping strategies for hierarchical multi-scale vegetation type extraction.

Assessment of Vegetation Cover of Bengaluru City, India, Using Geospatial Techniques

Bengaluru has a unique place due to its pleasant weather and green cover. Off late, the city has witnessed phenomenal urban growth, especially during last few decades. This study was envisaged to assess the decadal changes in vegetation cover of Bengaluru using multispectral IRS satellite imagery of 2006 and 2019 within Bruhat Bengaluru Mahanagara Palike (BBMP) area. Satellite datasets were analysed to assess changes in vegetation cover during the last decade. Vegetation (tree cover) within BBMP area was estimated to be 26.1% (18,572.2 ha) in 2019 as compared to 30.1% (21,414.9 ha) in 2006, indicating an overall reduction of 4%. Overall classification accuracy was estimated to be 92.1% for 2006 and 95.9% for 2019. Based on the analysis, a vegetation change map highlighting positive change areas, negative change areas and no change areas within vegetation categories were prepared for 198 BBMP wards. A total of 730 GT sample points were also collected along with geo-tagged field photographs, which covered diverse niche areas with different vegetation components and density classes, as well as non-vegetated urban and other areas. Recommendations have been given to sustain and improve existing vegetation cover.

Multilevel Extraction of Vegetation Type Based on Airborne LiDAR Data

Precise determination of vegetation type is important in remote sensing of the ecological environment. Many studies have explored ecosystem structure on explicit spatial scales using specific remote sensing data, but few studies have considered vegetation information extraction at various landscape levels using LiDAR-derived raster layers. This study determined vegetation information based on LiDAR-derived canopy height model (CHM) and LiDAR-derived forest canopy coverage (FCC) from the typical natural secondary forest of Maoershan Experimental Forest Farm (Northeast China). Geographic object-based image analysis was adopted for all experiments. Optimal classification characteristics and thresholds were determined and classification rule sets established for vegetation type extraction at four levels: vegetation-not-vegetation, vegetation type, forest type, and canopy—canopy gap. We compared and analyzed the capability of LiDAR-derived raster layers extraction to describe vegetation features at these four levels. An area-based assessment method was used for accuracy verification. The research showed that physical information such as vegetation height and canopy density provided by LiDAR point cloud is effective for extracting vegetation characteristics and categories. Moreover, results showed that high-resolution LiDAR-derived raster layers could provide more detailed vegetation information. This study represents a reference for data selection and mapping strategies for hierarchical and multiscale vegetation type extraction.

Future and recent developments in the retail vegetable category – a value chain and food systems approach

In this study, the value chain perspective was combined with a food systems approach to assess food system responses in the value chain and external drivers from environmental and socioeconomic perspectives. The research object was the Swedish value chain for vegetables, with the aim of providing a comprehensive picture of current trends and drivers and identifying future developments important for vegetable growers, producer organizations, wholesalers and retailers. The empirical data is based on in-depth interviews with key-decision makers in the Swedish value chain, constituting a single case. The point of departure is that key actors in this chain, from producer organizations to retailers, can provide a comprehensive picture on the category’s past development and future directions. A combined food systems and value chain approach has been applied. Drivers and chain responses have been identified and categorized into six main categories related to: (1) health; (2) consumer interest for food and variation; (3) convenience; (4) origin; (5) sustainability; and (6) urbanization. Value chain responses and future challenges as well as aspects on value chain dynamics and sustainability issues in the food system are presented and discussed.

Macroevolutionary patterns in European vegetation

AbstractQuestionHabitat‐specific species pools are shaped by ecological and evolutionary processes such as speciation, extinction, and migration. However, their role is poorly known because of the lack of robust data on species pools across a large number of plant community types and large areas. Here, we analyse a unique dataset of species pools of diagnostic species for all European vegetation types, asking: (a) what are the patterns of phylogenetic structure and phylogenetic beta‐diversity across European vegetation types and biomes; (b) what are the drivers of these patterns; and (c) is there a signal of niche conservatism at the level of biomes and broad categories of vegetation types?LocationEurope, Canary Islands, Madeira, Azores, Cyprus, Caucasus, Iceland and Greenland.MethodsWe built a dataset comprising 10,804 vascular plant species (almost 85% of the European flora) assigned to 106 vegetation types representing all European vegetated habitats, grouped into 11 biomes. This dataset represented habitat‐specific species pools. We analysed the phylogenetic structure of the species pools and related it to distribution range sizes of individual vegetation types, their successional status, levels of disturbance and environmental stress.ResultsIn European vegetation, phylogenetic overdispersion is associated with late‐successional habitats: several forest types, aquatic vegetation, and rock‐cliff vegetation serve as depositories of relict lineages. In contrast, phylogenetic clustering is typical of early successional and disturbed vegetation in anthropogenic, coastal and saline habitats, and in open‐canopy Mediterranean vegetation. The phylogenetic similarity of vegetation types is higher within than between broad categories of vegetation types and biomes.ConclusionsThe variable phylogenetic structure of European vegetation types is a heritage of evolutionary processes in the Tertiary and Quaternary. Habitat‐specific species pools of different vegetation types and biomes have been formed by different evolutionary processes as indicated by the observation that certain clades are significantly associated with certain vegetation types or biomes, hence indicating the phylogenetic niche conservatism.

Ungulate Species and Abundance as well as Environmental Factors Determine the Probability of Terminal Shoot Browsing on Temperate Forest Trees

Ungulate browsing is a major factor influencing tree regeneration. However, it is unclear if the observed increase in ungulate abundance in Central Europe implies increased browsing, and which other factors influence the incidence of browsing. We investigated the impact of forty variables (site, climate, forest and ungulates) on the probability of leader shoot browsing of six tree species which are frequent in Switzerland. The analysis was based on a large dataset including 49 monitoring areas, each containing 25–64 circular plots, in which 10 to 130 cm tall seedlings were repeatedly assessed. Browsing probability was estimated for each plot and year by mixed effects logistic regression and used as a response in random forests to disentangle the influence of the explanatory variables. Browsing probability was positively correlated with ungulate density measures (number culled by hunting or found dead) for all six tree species. Where beyond roe deer, some red deer and/or chamois were present, the browsing probability was higher. Small timber tree stands had less browsing than young growth and thicket stands. Seedlings tended to be more frequently browsed in stands with &gt;80% canopy shading. Browsing increased with increasing understory cover, independent of vegetation category. In conclusion, browsing is a multifactorial phenomenon and ungulate density estimates alone do not explain the whole browsing probability.

Temporary analysis of land use changes in Pine and mixed forests in Mexico

Objective: to evaluate the changes in land use that occurred in Pine and mixed forests, at the national level during the period 2001 to 2013.Design/Methodology/Approach: layers of Land Use and Vegetation (Sp. equ. USV) of Series II (from 2001) and V (from 2013) of the Instituto Nacional de Estadística y Geografía, scale 1: 250,000 were used. Different categories of vegetation under study were reclassified and homogenized for both covers. Rates of change and indicators of transitions were estimated for the spatial-temporary analysis: surfaces of estimated losses and gains, indices of persistence, exchanges and net changes; also, indices of gain and loss to persistence.Results: the rate of negative change for primary forests (Pine and mixed) ranges from 0.80 to 1.84. It was observed that 120 047 km2 (57.72%) were stable surfaces. However, 36 986 km2 (18.00%) were losses, 14 369 km2 gains and 28 738 km2 (14.00%) between categories. It was observed from 2001 to 2013 that 13.69% of the area corresponding to primary forests which existed in 2001 became part of secondary vegetation in 2013.Study limitations/Implications: in order to observe the influence of other categories, it would be important to incorporate more classes throughout the study to be analyzed globally in the system throughout the country.Findings/Conclusions: The persistence of the coverage of primary forests is important to design conservation policies

Концепция классификации растительности России как отражение современных задач фитоценологии

Концепция классификации растительности России как отражение современных задач фитоценологии

Urban forest development at landside of Hang Nadim Batam Airport based on the microclimate and noise study

The landside of Hang Nadim Batam Airport can be adapted to urban forests to reduce emissions, stabilize the microclimate, and reduce noise. The purpose of this research are to study the microclimate and noise around the Hang Nadim Batam Airport, and develop landside based on the condition of the airport urban forest. Research was conducted on April, 8th-15th 2019 based on the density of vegetation. Location determining, characteristics of trees and leaf area index, air temperature and humidity, and noise were used as the methods of this research. The factors that analyzed by this research were NDVI, tree profile diagrams, LAI, air temperature and humidity, thermal humidity, and noise. The result showed that there were 55 trees of 11 species from 6 families. The profile diagram showed the densest vegetation was at point F, one of the points of measurements with dense vegetation category, seen by horizontally and vertically. The highest air temperature and thermal humidity was at point E and the lowest was at point F. The highest humidity was at point F and the lowest was at point E. The highest noise was at rare vegetation and the lowest was at dense vegetation. Landside development needs to look at ecology, technical, and aesthetic.