Leafy Vegetables Research Articles

Key neuroprotective mechanisms of the MIND diet - a review paper

Introduction and purpose: Impaired cognitive function is a growing public health problem, where dementia is affecting about 47 million people worldwide, and that number is expected to triple by 2050. The MIND (Mediterranean-DASH Intervention for Neurodegenerative Delay) diet is intended to overcome this problem. This article aims to raise awareness of the MIND diet, highlighting how dietary choices can promote cognitive health and delay disease progression. Brief description of the state of knowledge: The MIND diet focuses on foods that support cognitive health and may mitigate these degenerative processes. It emphasizes green leafy vegetables, berries, nuts, olive oil, whole grains, fish, and poultry while limiting red meat, dairy, sweets, and fried foods. These products contain several components with multidirectional neuroprotective effects. Material and method: This work was based on material found on Google Scholar. Articles were selected based on citation counts, publication dates, and relevance, ensuring a comprehensive review of recent findings on the MIND diet's impact on cognitive health. Summary: The MIND diet enhances brain health by incorporating nutrient-dense foods that reduce inflammation, combat oxidative stress, and support neuronal function. Green leafy vegetables, berries, nuts, whole grains, and healthy fats work together to improve cognitive function, support synaptic plasticity, and protect brain structure, leading to slower cognitive decline and a lower risk of neurodegenerative diseases.

Kinetics of Chlorophyll Degradation in Malabar Spinach (Basellae alba) and Waterleaf (Talinum triangulare) during Hydrothermal Processing

Hydrothermal processing of vegetables often results in a number of changes including degradation of chlorophyll, the green plant pigment that is considered to be of therapeutic benefits. This study was aimed at investigating the kinetic degradation of chlorophyll in Malabar spinach (Basella alba) and waterleaf (Talinum triangulare) during hydrothermal processing. Freshly harvested leafy vegetables-- Malabar spinach and waterleaf, were obtained and subjected to various hydrothermal conditions (60, 65, 70, 75 and 80˚C at 0, 5, 10, 15 and 20 minutes) simulating typical cooking conditions. The chlorophyll of the crushed leaf was extracted using acetone. Changes in chlorophyll was determined using spectrophotometric analysis and the kinetics of degradation for each of the vegetables were determined at varying temperatures and times. Kinetics analysis revealed that the degradation of chlorophyll in Malabar spinach and waterleaf followed the first order reaction. The rate constant obtained from the kinetic analysis provided insights into the reaction rates and allowed for the prediction of chlorophyll degradation during hydrothermal processing. The results showed that the lowest percentage decrease in chlorophyll concentration during the blanching process was obtained at 65˚C for 5 minutes for Malabar spinach and for waterleaf at 60˚C for 5 minutes. Blanching temperature and time have significant effects on degradation of chlorophyll of Malabar spinach and waterleaf which could consequently determine the economic value and overall degree of acceptability of the green leafy vegetables. The findings provide baseline against which future work can be compared and importance of maintaining quality of the vegetables during processing.

Assessment of climatic and anthropogenic influences on vegetation dynamics in China: a consideration of climate time-lag and cumulative effects.

Determining the factors that drive vegetation variation is complicated by the intricate interactions between climatic and anthropogenic influences. Neglecting the short-term time-lag and cumulative effects of climate on vegetation growth (i.e., temporal effects) exacerbates the uncertainty in attributing long-term vegetation dynamics. This study evaluated the climatic and anthropogenic influences on vegetation dynamics in China from 2000 to 2019 by analyzing normalized difference vegetation index (NDVI), temperature, precipitation, solar radiation, and ten anthropogenic indicators through linear regression, correlation, multiple linear regression (MLR), residual, and principal component analyses. Across most regions, growing season NDVI (G-NDVI) exhibited heightened sensitivity to climatic variables from earlier periods or from both earlier and current periods, signaling extensive temporal climatic effects. Constructing new time series for temperature, precipitation, and solar radiation from 2000 to 2019, based on the optimal vegetation response timing to each climatic variable, revealed significant correlations with G-NDVI across 27.9%, 26.7%, and 23.3% of the study area, respectively. Climate variability and anthropogenic activities contributed 45% and 55% to the G-NDVI increase in China, respectively. Afforestation significantly promoted vegetation greening, while agricultural development had a marginally positive influence. In contrast, urbanization negatively impacted vegetation, particularly in eastern China, where farmland conversion to constructed land has been prevalent over the past two decades. Neglecting temporal effects would significantly reduce the areas with robust MLR models linking G-NDVI to climatic variables, thereby increasing uncertainty in attributing vegetation changes. The findings highlight the necessity of integrating multiple anthropogenic factors and climatic temporal effects in evaluating vegetation dynamics and ecological restoration.

Changes in Vegetation Greenness and Responses to Land Use Changes in the Yongding River Basin (in North China) from 2002 to 2022

Vegetation is an important component of an ecosystem, fulfilling various ecological functions in areas such as soil and water conservation, climate regulation, and water source maintenance. This study focuses on the Yongding River Basin as a research area. This study used vegetation indices with long time series as a data source in combination with Landsat land use data. This study applied linear trend estimation to analyze the interannual variation trend in vegetation greenness from 2002 to 2022 in the Yongding River Basin and quantitatively analyzed the impact of land use changes on vegetation greenness. The results show that, from 2002 to 2022, the vegetation greenness in the Yongding River Basin has shown an overall increasing trend. The average growth season and the maximum annual normalized difference vegetation index (NDVI) growth rates were 0.006/10a and 0.008/10a, respectively, and the area of increased vegetation greenness accounted for 90% of the total area. During the main growth season (April to October) in the Yongding River Basin, the NDVI generally showed a spatial pattern of being higher in mountainous areas and lower in water areas, with the largest coefficient of variation in vegetation in the river water areas, and the most stable vegetation in forest land. In terms of the changes in vegetation greenness, the contribution rate of arable land was between 36.73% and 38.63%, followed by grassland and forest land, with contribution rates of 26.86% to 27.11% and 23.94% to 26.43%, respectively. The total contribution rate of water areas, construction land, and unused land was around 10.18%. This study can provide a theoretical basis for environmental protection and rational land use in the Yongding River Basin.

Impact of Extreme Drought on Vegetation Greenness in Poyang Lake Wetland

The Poyang Lake Wetland, an internationally significant ecosystem, frequently experiences drought during the flood season. However, the total impact of extreme drought on wetland vegetation remains poorly understood. This study determined the standardised precipitation evapotranspiration index (SPEI) and analysed drought trends within the Poyang Lake Basin. Additionally, spatiotemporal variations in wetland vegetation under drought conditions were examined by analysing the mean normalised difference vegetation index (NDVI) values and categorising NDVI classifications. The key factors affecting wetland vegetation and its respective thresholds were determined. The Poyang Lake Basin has experienced increasing aridity over the past 3 years. In response to this trend, the wetland vegetation area in Poyang Lake expanded, whereas vegetation greenness declined. Notably, in the year following an extreme drought, Poyang Lake’s vegetation greenness was lower than that during the same period in previous years. Regardless, the correlation analysis showed no significant relationship between the SPEI values and the wetland vegetation greenness; however, water level changes significantly impacted the wetland vegetation, with a correlation coefficient of −0.89 (p < 0.001). A critical water level of 14 m was identified as the threshold at which sudden changes in the mean NDVI were observed. This research offers valuable insights into hydrological management strategies to protect Poyang Lake Wetland’s vegetation under drought conditions. Future studies should enhance the differentiation of drought tolerance among different wetland plant species, thereby achieving differentiated hydrological management.

Nutrient composition of shade-dried Aldenia cissampeloides (monkey rope) leafy vegetable

Background: Our locally available vegetables are underutilized due to lack or insufficient information about their health benefit. Consequently, some are going into extinction due to low consumption. Adenia cissampeloides, a locally available vegetable used in the preparation of vegetable soup and or some therapeutic purposes is becoming unpopular due to insufficient nutritional and other information on it. Objective: The study investigated the nutrient composition of shade-dried Aldenia cissampeloides leafy vegetables. Methods: Fresh leaves of Adenia cissampeloides were harvested from Opi in Nsukka local Government Area of Enugu State in South Eastern Nigeria. The leaves were sorted, washed with water, and allowed to drain in a colander for about 20 minutes. The leaves were shade-dried for 7 days at room temperature and pulverized using Qlink electric blender model QBL/20L40. The proximate, mineral, and vitamins of the pulverized dried sample were analyzed using standard methods. Results: The proximate analysis showed an appreciable amount of carbohydrate (42.86%), crude fiber (16.79%), and protein (16.44%). Magnesium (2046.69mg), potassium (1031.33mg) and calcium (555.33mg) was the most abundant mineral while pro-vitamin A had the highest value (298.56 RE) among the analyzed vitamins. This was indicative that the vegetable is a good source of nutrients. Conclusion: Due to its nutrient-dense quality, it is recommended to be cultivated at home gardens for easy accessibility in meeting the family’s nutrient needs.

How the characteristics of land cover changes affect vegetation greenness in Guangdong, a rapid urbanization region of China during 2001-2022.

To evaluate the quantitative impacts of land cover change on vegetation greenness in the significantly human-impacted subtropical region, the characteristics of land cover change were explored by land use dynamic degree, transition matrix and normalized entropy. Various methods including Standardized coefficient, LMG (Lindeman-Merenda-Gold), GEN (Genizi measure) and CAR (Correlation-Adjusted Marginal Correlation) were employed to estimate the contributions of land cover changes on vegetation greenness using MODIS data during 2001-2022 in Guangdong. The conclusions revealed that land cover changes exhibited obvious temporal characteristics in Guangdong with a significantly increasing trend of normalized entropy indicating a more balanced distribution of land cover types under human intervention. NDVI (Normalized Difference Vegetation Index) tended to increase likely due to the large-scale increase in evergreen forest. With regard to the contributions of impact factors on vegetation greenness, the contributions evaluated by LMG, GEN and CAR showed that the natural variation of NDVI accounted for the major contribution (> 33%), while the changes of evergreen forest and grassland had the highest contribution (> 37%) according to Standardized coefficient. These differences were mainly due to the characteristics of land cover changes in Guangdong, the correlations among impact factors and the inherent attributions of the methods. Moreover, the expansions of evergreen forest and urban at the expense of the reductions of grassland and cropland also had significant impacts on NDVI (> 10%) according to LMG, GEN and CAR indicating that human-induced land cover changes had remarkable influences on NDVI.

Quality diversity of three calcium-rich Primulina vegetables: A comprehensive analysis of calcium content, metabolite profiles, taste characteristics, and medicinal potential

Primulina plants native to karst regions are exceptionally rich in calcium and have been developed into high‑calcium leafy vegetables. However, limited knowledge of their metabolites, taste characteristics, and potential medicinal value restricts further genetic improvements. This study conducted a comprehensive analysis on three breeding species of Primulina vegetables. Common garden experiment demonstrated significant calcium enrichment capability, with calcium content ranging from 204.45 to 391.52 mg/100 g. Through widely-targeted metabolomics, 1121 metabolites were identified within these Primulina vegetables. Furthermore, comparative analysis identified 976 differentially accumulated metabolites across nine comparison groups, driven mainly by flavonoids, phenolic acids, and lipids. Integration of electronic tongue analysis and metabolomics revealed taste profiles and identified 17 key candidate compounds related to taste. Based on network pharmacology analysis, 32 active ingredients were found in Primulina vegetables, which highlighted potential medicinal value. These findings provide a data-driven foundation for breeding programs aimed at enhancing nutritional and flavor traits.

Dietary habits and genetic susceptibility: correlations between nutritional intake and genetic risks for schizophrenia and bipolar disorder

Dietary habits may impact the prevention and management of schizophrenia (SCZ) and bipolar disorder (BD), and genetic and environmental factors can influence both these habits and these disorders. This study investigated the effects of genetic predispositions to SCZ and BD on current dietary habits among older adults with lifestyle-related diseases, potentially offering insights for preventive mental health strategies. A cohort of 730 older patients who were diagnosed with or suspected of having lifestyle-related diseases was assessed for eight current dietary categories: miso soup, Japanese tea, green and yellow vegetables, light-colored vegetables, fruits, pickles, meats, and soybeans. Polygenic risk scores (PRSs) for the risk of SCZ and BD, including BD types I and II, the shared risk of SCZ and BD, and the differentiation of SCZ from BD, were calculated utilizing data from large-scale genome-wide association studies (GWASs). Our findings revealed that PRSs for SCZ and BD risk significantly influenced specific dietary habits, particularly decreased consumption of nutrient-rich foods such as light-colored vegetables (SCZ, R2 = 0.0096, p = 3.54 × 10−3; BD, R2 = 0.0074, p = 9.09 × 10−3) and soybeans (SCZ, R2 = 0.0061, p = 0.019; BD, R2 = 0.014, p = 8.38 × 10−4). Notable differences in dietary effects were observed between PRSs for BD I and BD II, with a more pronounced impact associated with BD I (e.g., light-colored vegetables, BD I, R2 = 0.015, p = 3.11 × 10−4; BD II, p > 0.05). Moreover, shared genetic factors for SCZ and BD were correlated with lower intakes of miso soup (R2 = 0.013, p = 1.21 × 10−3), Japanese tea (R2 = 0.0092, p = 5.59 × 10−3), light-colored vegetables (R2 = 0.010, p = 2.92 × 10−3), and soybeans (R2 = 0.014, p = 3.13 × 10−4). No significant correlations were found between PRSs for differentiating SCZ from BD and any dietary patterns (p > 6.25 × 10−3). Genetic risks shared by individuals with SCZ and BD may influence dietary choices in older adults, emphasizing the potential for dietary modifications as part of comprehensive strategies for the prevention of the SCZ and BD onset, as well as for the treatment of individuals at risk of or diagnosed with SCZ and BD.

Satellite-observed relationships between land cover, burned area, and atmospheric composition over the southern Amazon

Abstract. Land surface changes can have substantial impacts on biosphere–atmosphere interactions. In South America, rainforests abundantly emit biogenic volatile organic compounds (BVOCs), which, when coupled with pyrogenic emissions from deforestation fires, can have substantial impacts on regional air quality. We use novel and long-term satellite records of five trace gases, namely isoprene (C5H8), formaldehyde (HCHO), methanol (CH3OH), carbon monoxide (CO), and nitrogen dioxide (NO2), in addition to aerosol optical depth (AOD), vegetation (land cover and leaf area index), and burned area. We characterise the impacts of biogenic and pyrogenic emissions on atmospheric composition for the period 2001 to 2019 in the southern Amazon, a region of substantial deforestation. The seasonal cycle for all of the atmospheric constituents peaks in the dry season (August–October), and the year-to-year variability in CO, HCHO, NO2, and AOD is strongly linked to the burned area. We find a robust relationship between the broadleaf forest cover and total column C5H8 (R2 = 0.59), while the burned area exhibits an approximate fifth root power law relationship with tropospheric column NO2 (R2 = 0.32) in the dry season. Vegetation and burned area together show a relationship with HCHO (R2 = 0.23). Wet-season AOD and CO follow the forest cover distribution. The land surface variables are very weakly correlated with CH3OH, suggesting that other factors drive its spatial distribution. Overall, we provide a detailed observational quantification of biospheric process influences on southern Amazon regional atmospheric composition, which in future studies can be used to help constrain the underpinning processes in Earth system models.

Effect of Nutrient Solution pH on the Growth and Quality of Lactuca sativa Grown in a Static Hydroponic System

Lettuce is an easy-to-grow and nutrient-rich leafy vegetable. It grows well using a static hydroponic system, which saves space and is easy to maintain. However, understanding pH’s impact on lettuce growth in static hydroponic systems is limited. Hence, this study was conducted to determine the effect of pH nutrient solution on the growth performance and eating quality of lettuce grown in a static hydroponic system. Lettuce was grown in pH 5.2, 6.2, and 7.2 nutrient solutions. Its growth performance was collected weekly, including plant height, root length, number of leaves, leaf area, leaf chlorophyll content, total dry weight, and total moisture content. The harvested lettuce was analyzed for firmness, soluble solids concentration, titratable acidity, pH, and ascorbic acid content by the fourth week after transplanting. The plant height, root length, number of leaves, leaf area, and total dry weight of lettuce were affected by the interaction between nutrient solution pH and weeks after transplanting. By the third week after transplanting, lettuce grown in pH 6.2 was 11.12 and 18.67% taller than those grown in pH 7.2 and 5.2 nutrient solutions, respectively. By the fourth week after transplanting, the firmness of lettuce grown in pH 6.2 was significantly higher than those grown in pH 5.2 and 7.2 nutrient solutions by 2.34 and 7.32%, respectively. It is concluded that lettuce should be grown in a pH 6.2 nutrient solution when using a static hydroponic system.

Performance of different leafy vegetables under coastal saline soil of Konkan Region of Maharashtra State of India

Performance of different leafy vegetables under coastal saline soil of Konkan Region of Maharashtra State of India

Epiphytic, Attached, and Internal Escherichia coliO157:H7 Subpopulations Associating With Romaine Lettuce Are Strain‐Dependent and Affected by Relative Humidity and Pre‐ and Postharvest Plant State

ABSTRACTRomaine lettuce is susceptible to Escherichia coli O157:H7 contamination. We evaluated strain and pre‐ and postharvest lettuce product differences in E. coli O157:H7 subpopulation distribution on romaine lettuce at two relative humidity (RH) levels. Plants of romaine lettuce cultivar 'Carlsbad' harvested and processed 'Carlsbad' leaves, and store‐bought ready‐to‐eat romaine lettuce were inoculated with E. coli O157:H7 reference strain EDL933 and romaine lettuce outbreak strain 2705C. Using four processing methods, we determined pathogen cell fractions representing All (entire population), Epiphytic (loosely attached cells), Strongly Attached + Internal (excluding loosely attached cells), and Internal (excluding epiphytic cells) subpopulations. Preharvest, 80% RH favored subpopulations in each cell fraction, compared to 40% RH (p < 0.01 for both strains) and yielded 92%–100% internalization incidence of E. coli O157:H7, compared to 50%–57% at 40% RH. Levels of internal EDL933 cells were also 1.1 log higher than 2705C cells from plants kept at 80% RH (p < 0.001). While EDL933 had lower measures of Strongly Attached + Internal cells compared to All and Epiphytic fractions (p < 0.01), 2705C yielded no difference. Taken together, data suggest that the lettuce outbreak strain had a higher propensity for strong attachment to leaves and EDL933 internalized more successfully. Moreover, the Strongly Attached + Internal fractions of both strains were lower on preharvest 'Carlsbad' compared to 'Carlsbad' processed leaves (p < 0.01), suggesting that E. coli O157:H7 attached less strongly to preharvest plants than postharvest cut and stored leaves of the same variety. Our study uncovers important factors influencing cultivar‐ and strain‐specific differences in association and internalization of enteric pathogens on leafy greens.

Development of a flexible produce supply chain food safety risk model: Comparing tradeoffs between improved process controls and additional product testing for leafy greens as a test case

The produce industry needs a tool to evaluate food safety interventions and prioritize investments and future research. A model was developedin R for a generic produce supply chain and made accessible via Shiny. Microbial contamination events, increases, reductions, and testing can be modeled. The output for each lot was the risk of one, 300-gram sample testing positive, described by two industry-relevant risk metrics, the overall risk of a positive test (proxy for recall risk) and the number of lots with the highest risk (>1 in 10 chance) of testing positive (proxy for public health risk). A leafy green supply chain contaminated with Shiga-toxin-producing Escherichia coli was modeled with a mean of 1 pathogen cell per pound (µ=1 CFU/lb or -2.65 Log(CFU/g)) under high (σ=0.8 Log(CFU/g)) and low (σ=0.2 Log(CFU/g)) variability. Baseline risk of a positive test in the low-variability scenario (1 in 20,000) was lower than for high-variability (1 in 4,500), showing rare high-level contamination drives risk. To evaluate tradeoffs, we modeled two well-studied, frequently used interventions: additional product testing (8 of 375-gram tests/lot) and improved process controls (additional -0.87±0.32 Log(CFU/g) reduction). Improved process controls better reduced recall risk (to 1 in 115,000 and 1 in 26,000 for low- and high-variability, respectively), compared to additional product testing (to 1 in 21,000 and 1 in 11,000 for low- and high-variability, respectively). For low variability contamination, no highest risk lots existed. Under high variability contamination, both interventions removed all highest risk lots (about 0.05% of total). Yet, additional product testing rejected more lower-risk lots (about 1% of total), suggesting meaningful food waste tradeoffs. This model evaluates tradeoffs between interventions using industry-relevant risk metrics to support decision-making and can be adapted to assess other commodities, process stages, and less-studied interventions.

Evaluating Land Surface Temperature Variation and Its Responses to Climate Change and Human Activities on the Southeastern Tibetan Plateau

ABSTRACTThe Yarlung Zangbo River Basin (YZRB), situated within the Qinghai‐Tibetan Plateau, has experienced significant alterations due to global warming and vegetation greening. This region serves as a critical indicator of the interplay between vegetation growth and climatic fluctuations, as evidenced by substantial changes in spatiotemporal land surface temperature (LST) over recent decades. In this research, we assessed the components of the water and energy cycles from 1980 to 2015 utilising the variable infiltration capacity (VIC) model to generate a continuous daily LST data over a 35‐year period. Subsequently, we analysed the variations in LST and identified the influence of environmental factors on temperature changes. Notably, while greening was observed, LST exhibited an upward trend. By differentiating the effects of climatic and anthropogenic factors on LST, we found that climate was the predominant influence, accounting for a contribution rate of 70.36% from 1980 to 1995. In contrast, human activities became the primary driver of LST changes, contributing 55% after 1995. Grasslands with moderate coverage demonstrated potential cooling effects. Among the various environmental factors examined, albedo exhibited a negative and delayed impact on LST, while temperature, precipitation and evapotranspiration were positively correlated with LST, displaying relatively synchronous variations. Additionally, soil moisture and the normalised difference vegetation index (NDVI) were identified as leading contributors to positive changes in LST. This study enhances the understanding of the mechanisms influencing LST and provides essential insights for socio‐economic development in areas with sensitive ecosystem.

Global Wind Erosion Reduction Driven by Changing Climate and Land Use

AbstractWhile significant progress has been achieved in researching water erosion, our understanding of global patterns and the magnitude of wind soil erosion remains limited. Here, we present a comprehensive assessment using the revised wind erosion equation (RWEQ) of the global rates and long‐term trends (1982–2019) of wind erosion using a spatially explicit (0.05° × 0.05°) quantitative model. On average, in this study global wind erosion caused 312.5 Pg yr−1 of soil loss, with a decreasing trend of 1.04 ± 0.48 Pg yr−1 (p < 0.05) during 1982–2019. Excluding stable regions, approximately 36% of the modeled areas exhibit a significant decrease in wind erosion, accounting for 3.13 ± 0.18 Pg yr−1, while only 9% experience a notable increase, amounting for 1.83 ± 0.16 Pg yr−1. The decrease of wind erosion primarily occurs in the southern hemispheres. Notably, wind erosion decreases considerably in grassland and cropland, while it remains unchanged in dryland. Although grassland and cropland account for only 11% and 1.8% of the total erosion, they contribute to 68% and 17% of the total erosion reduction, respectively. This study highlights global wind stilling and vegetation greening as important factors contributing to the decline in wind erosion and offers valuable insights into the intricate relationship between climate change and terrestrial ecosystems, including carbon sequestration and agricultural productivity.

Responses of vegetation to hydroclimatic variables on the Loess Plateau after large scale vegetation restoration

AbstractUnderstanding plant‐water relations is essential for effective regional water management and promoting ecologically sustainable development on the Loess Plateau, especially in the context of the Grain for Green project initiated in 1999. This study evaluated the variations in vegetation variables (leaf area index, enhanced vegetation index, solar‐induced chlorophyll fluorescence and gross primary production) and hydroclimatic variables (precipitation, total water storage, aridity index and standardized precipitation evapotranspiration index) from 2003 to 2020, along with their interactions across the Loess Plateau. Our analysis revealed a general increase in vegetation variables, with the largest increase observed in the forest expansion areas. Precipitation and the aridity index exhibited significant upwards trends, while total water storage showed a significant decline, particularly in the forest expansion areas. Vegetation variables were more sensitive to changes in total water storage across the Loess Plateau. In the northwest region, where large‐scale croplands and grasslands expansion occurred, vegetation variables also showed sensitivity to precipitation. Lag effect analysis revealed short time lags (1–3 months) between vegetation and hydroclimatic variables, expect for total water storage (6 months). Overall, human activities and climate factors contributed 58.4% and 41.6% to the increase in leaf area index, and 52.2% and 47.8% to the increase in gross primary production, respectively. In relatively arid environments, precipitation contributed over 50% to the observed vegetation greening. This study underscores the increasingly significant role of human activities in driving vegetation greening on the Loess Plateau, particularly in large‐scale afforestation areas.

Spatio-Temporal Analysis of Water Hyacinth Density (Eichhornia crassipes) in Lake Rawa Pening 2019 - 2023 Using NDVI Algorithm on Google Earth Engine (GEE)

Abstract Water hyacinth (Eichhornia crassipes) is an aquatic plant that floats in freshwater waters that has the ability to grow very fast and is invasive. This plant is able to reproduce vegetatively and generatively and is able to double its population within two weeks so that it can endanger the ecosystem in the waters. The purpose of this research is to map the distribution pattern, dynamics of changes in vegetation density and changes in water hyacinth area with spatial-temporal techniques using remote sensing technology processed using GEE in Lake Rawa Pening. The satellite image used is Sentinel level-2A with high spatial resolution with a recording time of May 2019 - 2023. This study uses the NDVI method to measure the greenness of vegetation and help identify the density of water hyacinth vegetation. The results of the vegetation density index show that there are five classification for vegetation density levels, and the outcomes of the accuracy test that was conducted range from -0.15 to 0.94. obtained an overall accuracy of 86.6% and a kappa coefficient value of 0.81. These results show that the use of Sentinel 2A imagery can be used for vegetation density index mapping using the NDVI algorithm in GEE with a good level of accuracy and conformity between map and field and the image processing that has been done is appropriate.

Mathematical modelling of vacuum cooling of leafy vegetables using bidirectional conjugate model combining heat and mass transfer with leaf structural deformation

The numerical model is an effective solution to regulate the uneven temperature distribution, water loss, and structural shrinkage of leafy vegetables during vacuum cooling (VC). Nevertheless, the developed models mainly concentrate on the heat and mass transfer of leafy vegetables during the cooling, ignoring the structural deformation and its interaction with heat and mass transfer. For a better understanding of the cooling process, a macroscopic bidirectional coupled thermo-hydro-mechanical (THM) model was developed to describe the VC of leafy vegetables using spinach as a representative case. The simulations, validated by the experimental results, accurately predicted the changes in vapour pressure, weight loss, evaporation rate, moisture concentration, and shrinkage of the leafy vegetable, as well as the cooling gradients of the stem, blade, midvein, and lateral veins. Results showed that the cooling of the blade was easier, but the cooling gradient of the blade was lower than that of the leaf stem, with a maximum temperature gradient of stem, veins, and blade after cooling being 2.09 °C. Reducing the cooling end pressure could shorten the cooling time to the desired cooling temperature and minimise the water loss. Sensitivity analysis revealed that porosity significantly affected the changes in temperature, moisture concentration, and shrinkage. Notably, water evaporation was the primary reason for the shrinkage of the leaf tip and edge, but the contraction of the solid matrix cannot significantly aggravate further water evaporation. These findings highlight the potential of the THM model to promote the commercialisation of VC for leaf vegetables.

S2092 Gastrointestinal Health Status and Intaking of Dark Leafy Greens, Fruits, Carbonated Beverages, Savory Snacks and Whole Milk Nutrition

S2092 Gastrointestinal Health Status and Intaking of Dark Leafy Greens, Fruits, Carbonated Beverages, Savory Snacks and Whole Milk Nutrition