Chlorophyll Content Research Articles

Effects of green seaweed (<i>Ulva onhoi</i>) on the reproductive development of tomato (<i>Solanum lycopersicum)</i> plants

Algae-derived products have great potential as crop biostimulants due to their multiple beneficial effects at different stages of plant development. Green seaweeds of the genus <i>Ulva</i> are well suited for this purpose because they are widely distributed and grow rapidly in a wide range of conditions. In this study, a greenhouse experiment was conducted to evaluate the effects of dry seaweed powder (DSP) and liquid seaweed extract (LSE) of <i>Ulva ohnoi</i> on the reproductive development of tomato plants. The experiment included three treatments: 1) plants treated with 5 g of DSP, 2) plants treated with 250 mL of LSE, and (3) control plants (without algae). The reproductive parameters, chlorophyll content, and mineral composition were measured during the flowering and early fruiting periods. The application of DSP was the most effective treatment in promoting early flowering and significantly increased the number of buds (103%), flower clusters (55%), flowers (61%), and fruits (45%) per plant. Furthermore, the DSP-treated plants exhibited an enhancement in the levels of chlorophyll and nutrients in the plants and fruits. The results of the current work show that the application of <i>U. ohnoi</i> in its natural form (dry powder) stimulates the reproductive development of crop tomato. This represents a sustainable and natural alternative to synthetic inputs that growers can incorporate into horticultural production to improve yield attributes.

Impact of surface dielectric barrier discharge cold atmospheric plasma on quality and stability of fresh-cut iceberg lettuce

This study evaluated the impact of cold atmospheric plasma (CAP) on fresh-cut iceberg lettuce (FIL) quality and stability. CAP treatments were performed using a Surface Dielectric Barrier Discharge, applying 6 kV at 23 kHz and exposition times varying from 15 to 60 min. FIL was analysed before and after treatments for polyphenoloxidase (PPO) and peroxidase (POD) activity, microbial contamination, colour, surface microstructure properties, chlorophylls content, polyphenols (TPC), ascorbic acid (AA), and antioxidant activity (AoA). TPC, AA and AoA were evaluated also after storage (4 °C for 5 days). CAP treatments provoked a reduction of PPO and POD activity with a processing time- and ozone-concentration-dependent effect. After treatments, a slight inactivation of mesophilic and psychrotrophic bacteria was observed, while yeast counts remained unaffected. With increasing treatment times, increasing cell damages and colour variations were detected, and a decrease of chlorophylls, TPC, AA, and AoA. After storage, an overall AoA increase was observed due to increased extractability or production by living cells of antioxidant compounds. These findings provide insights into the efficacy of CAP treatment in preserving fresh-cut iceberg lettuce quality. Further investigations are needed to optimize the process conditions and increase microbial inactivation while limiting qualitative damage to the product.

A modified A* algorithm combining remote sensing technique to collect representative samples from unmanned surface vehicles.

Ensuring representativeness of collected samples is the most critical requirement of water sampling. Unmanned surface vehicles (USVs) have been widely adopted in water sampling, but current USV sampling path planning tend to overemphasize path optimization, neglecting the representative samples collection. This study proposed a modified A* algorithm that combined remote sensing technique while considering both path length and the representativeness of collected samples. Water quality parameters were initially retrieved using satellite remote sensing imagery and a deep belief network model, with the parameter value incorporated as coefficient Q in the heuristic function of A* algorithm. The adjustment coefficient k was then introduced into the coefficient Q to optimize the trade-off between sampling representativeness and path length. To evaluate the effectiveness of this algorithm, Chlorophyll-a concentration (Chl-a) was employed as the test parameter, with Chaohu Lake as the study area. Results showed that the algorithm was effective in collecting more representative samples in real-world conditions. As the coefficient k increased, the representativeness of collected samples enhanced, indicated by the Chl-a closely approximating the overall mean Chl-a and exhibiting a gradient distribution. This enhancement was also associated with increased path length. This study is significant in USV water sampling and water environment protection.

The Application of Aluminium- and Natural Clay- Based Compounds in the Treatment of Eutrophicated Waters in Semiarid Brazil

Objective: The presence of cyanobacteria in raw water can affect aquatic biota and human health, as some species are potentially toxic. In addition, these organisms can cause operational problems in water treatment plants, causing interference in the coagulation and flocculation processes, in addition to clogging the filters. The objective of this study was to test the efficiency of the application of poly aluminium chloride (PAC) and aluminium sulphate, with and without association with natural clay, in the removal of total phosphorus, chlorophyll a and cyanobacteria cells in eutrophic reservoir waters of the semi-arid region of Northeast Brazil. Theoretical Framework: The study is based on the application of materials (natural clays) with the capacity to adsorb and precipitate phosphorus from the aquatic environment, blocking its release after sedimentation. This application is efficient in removing sedimentation from cyanobacterial blooms with toxic potential from the aquatic environment Method: This is an experimental study, with tests carried out in Jar Test, with water from a eutrophic environment and with cyanobacteria blooms. Water samples were collected from the subsurface to analyze the parameters: pH, total phosphorus (PT), chlorophyll-a and quantity of cyanobacteria. PT pH and concentration were determined according to the techniques described in Standard Methods APHA (2012). Chlorophyll concentration was analyzed using the extraction technique with 96% ethanol (Jespersen; Christoffersen, 1987). For the qualitative and quantitative study of cyanobacteria, the analysis was carried out using an inverted microscope, according to the methodology of Utermöhl (1958), with sedimentation time in the counting chamber established according to the method of Margalef (1983). The density calculation was carried out according to Ross (1979), being expressed in number of individuals per milliliter (ind. mL-1). Results and Conclusion: The combined application of aluminium sulphate and PAC with natural clay (bentonite) functioned as an efficient technique to remove concentrations of total phosphorus and chlorophyll a, in addition to reducing the density of cyanobacteria. The reduction in the number of cyanobacterial cells with associated application of bentonite and coagulants was promising, with the removal of up to 100% of colonial species and 89% of filamentous species. Implications of the Researsh: The research highlights the relevance of applying low-cost techniques that optimize the quality of water offered for public supply. It should be noted that the presence of cyanobacteria in raw water can affect aquatic biota and human health, as some species have toxigenic potential. Furthermore, these organisms can cause operational problems in water treatment plants, interfering with the coagulation and flocculation processes, in addition to clogging filters. Originaly/Value: This study contributes to the understanding of the application of natural products (clays) as a phosphorus adsorbent and intact cyanobacteria cells. The research highlights that with additional studies, this approach could be a useful tool for removing cyanobacteria cells in water from eutrophic environments intended for public supply.

Mitigating the effects of polyethylene microplastics on Pisum sativum L. quality by applying microplastics-degrading bacteria: A field study

Polyethylene microplastics (PE-MPs) have been widely reported for their adverse effects on soil ecosystems. However, there are fewer field studies on addressing PE-MPs contamination in soil. This study investigated the effects of PE-MPs on soil properties, rhizosphere soil microorganisms, and pea (Pisum sativum L.) nutrient composition in a field experiment and mitigated the effects of PE-MPs by adding MPs-degrading bacteria. The results showed that the addition of MPs-degrading bacteria mitigated the effects of PE-MPs on the hydrolyzable nitrogen content in the soil. In addition, the introduction of MPs-degrading bacteria resulted in an increase in the Shannon indices of microorganisms in the soil. This also effectively regulates the structure of the soil microbial community to be closest to that of normal soil. Notably, the addition of MPs-degrading bacteria increased the protein, starch, cellulose, and chlorophyll contents of pea grains. This study demonstrated the ability to improve the nutrient content of peas affected by MPs by adding MPs-degrading bacteria. This study contributes to our understanding of the effects of PE-MPs on soil-microbe-plant systems and provides new insights into the bioremediation of PE-MPs in agricultural soils.

Development of VIIRS-OLCI chlorophyll-a product for the coastal estuaries

Coastal waters require monitoring of chlorophyll-a concentration (Chl-a) in a wide range of Chl-a from a few mg/m3 to hundreds of mg/m3, which is of interest to the fisheries industry, evaluation of climate change effects, ecological modeling and detection of Harmful Algal Blooms (HABs). Monitoring can be carried out from the Visible Infrared Imaging Radiometer Suite (VIIRS) and Ocean and Land Colour Instrument (OLCI) Ocean Color (OC) satellite sensors, which are currently on orbit and are expected to be the main operational OC sensors at least for the next decade. A Neural Network (NN) algorithm, which uses VIIRS M3-M5 reflectance bands and an I1 imaging band, was developed to estimate Chl-a in the Chesapeake Bay, for the whole range of Chl-a from clear waters in the Lower Bay to extreme bloom conditions in the Upper Bay and the Potomac River, where Chl-a can be used for bloom detection. The NN algorithm demonstrated a significant improvement in the Chl-a retrieval capabilities in comparison with other algorithms, which utilize only reflectance bands. OLCI NIR/red 709/665 nm bands red edge 2010 algorithm denoted as RE10 was also explored with several atmospheric corrections from EUMETSAT, NOAA and NASA. Good consistency between the two types of algorithms is shown for the bloom conditions and the whole range of waters in the Chesapeake Bay (with RE10 switch to OC4 for lower Chl-a) and these algorithms are recommended for the combined VIIRS-OLCI product for the estimation of Chl-a and bloom monitoring. The algorithms were expanded to the waters in Long Island Sound, demonstrating good performance.

Predicting chlorophyll-a dynamics in the Ashtamudi estuary using ANN and ANFIS techniques

Excessive nutrients and associated high chlorophyll-a concentration are of growing concern to the public health due to the occurrence of eutrophication in aquatic bodies. Continuous monitoring of chlorophyll-a has limitations, thereby necessitating the development of prediction models. Even though chlorophyll-a prediction models are numerous, they rarely fit into estuarine conditions, which is encountered with dynamic mixing of freshwater and sea water. Thus, the present study identifies the most appropriate driving factors that are relevant for estuarine conditions through chlorophyll-a prediction models developed using Artificial Neural Network and Adaptive Neuro Fuzzy Inference System (ANFIS) approaches in the Ashtamudi estuary, India. Salinity, which is an indirect measure of the estuarine mixing intensity, has been used to replicate the dynamic mixing in the estuary. The results indicate that the model incorporating salinity along with total nitrogen, total phosphorous and turbidity well-predicted chlorophyll-a concentration with a coefficient of determination ranging from 0.73 to 0.99. General Regression Neural Network (GRNN) and ANFIS models outperformed Back Propagation Neural Network (BPNN) and Recurrent Neural Network (RNN) models. Of the various ANFIS models, the ones that used Gaussian and Generalized Bell membership functions were most appropriate for the prediction of chlorophyll-a than the models with triangular and trapezoidal membership functions. The study identified that the models that considered salinity were less sensitive and can be used for modelling chlorophyll-a. The chlorophyll-a was observed to have a direct influence of salinity at salinity values greater than 5‰. The study highlighted that estuarine mixing further enhances the primary productivity through increased penetration of light leading to higher chlorophyll-a concentration. Further the study emplasized that the predictive models are important tools fitting well within estuarine environments due to its replicability.

Determining Seasonal Spatial and Temporal Distribution of Chlorophyll-a, and its Concentration in Kuwait and the Arabian Gulf using Satellite and In-situ Data

As an indicator of phytoplankton density in an area, the concentration of chlorophyll-a (Chl-a) is an important reflection of marine water quality. Remote sensing techniques have been developed to measure the near-surface concentration of Chl-a in water by combining spectral bands and in situ data. This algorithm can be applied to sensors of varying spatial, temporal and spectral resolutions. However, in this study, Chl-a level 2 and 3 products of SNPP – VIIRS spectrometer (Equation OC3) from NASA’s OceanColor suite were relied upon to establish the spatial and temporal distribution of Chl-a concentration in the Arabian Gulf (also known as the Persian Gulf) and the territorial waters of the State of Kuwait (located in the north-eastern part of the Arabian Gulf) in 2012-2019. Ground truthing points (n = 192) matched with level 2 products have been used to build and cross-validate an empirical model. The correlation was positive, with r^2 = 0.79 and validation RMSE = ± 0.64 mg/m-3. The derived algorithm was then applied to Chl-a level 3 seasonal products. Additionally, the Chl-a concentration values in Kuwaiti waters were enhanced using the IDW algorithm to increase spatial resolution, given its small size compared to the spatial resolution of level 3 Chl-a products. The model derived from IDW was tested using the Mann Whitney test (Sig = 0.948 p > 0.01). However, the result showed that Chl-a concentration was higher in the Kuwait Bay (average = 2.8 mg/m-3) than in Kuwaiti waters (average = 2.3 mg/m-3), and higher in Kuwaiti waters (average = 2.1 mg/m-3) than in the Arabian Gulf (average = 0.7 mg/m-3). Coasts have higher concentrations than open water. Generally, the Chl-a increases in winter and had a semi-regular cycle during the years of study; this cycle is more regular in the Gulf than in Kuwait.

Optimizing water use efficiency in greenhouse cucumber cultivation: A comparative study of intelligent irrigation systems.

This study investigated the use of an intelligent irrigation system for greenhouse cucumber cultivation, aiming to manage water consumption efficiently. During the initial phase, irrigation was tested at four levels: 80%, 90%, and 100% of Field Capacity (FC), and Conventional Flood Irrigation (CFI). Data on environmental conditions and water usage were meticulously recorded. Optimal yields and crop quality (measured by size and firmness) were achieved at CFI and 100% FC, with CFI consuming the most water (0.148 m3/m2) Consequently, 100% FC was identified as the best practice, informing the intelligent system's calibration in the subsequent phase. This adjustment resulted in reduced water consumption and a 15.6% improvement in Water Use Efficiency (WUE) over CFI. Additionally, by examining the product performance and the color characteristics, chlorophyll content, and photosynthesis of the leaves, it was observed that the quality and optimal water supply and the product performance were maintained in the smart irrigation system. The study concludes that, considering long-term outcomes, the intelligent irrigation system is preferable to CFI, offering significant water savings and enhanced WUE without compromising crop quality.

Enhancing Algal Bloom Level Monitoring with CYGNSS and Sentinel-3 Data

Algal blooms, resulting from the overgrowth of algal plankton in water bodies, pose significant environmental problems and necessitate effective remote sensing methods for monitoring. In recent years, Global Navigation Satellite System–Reflectometry (GNSS-R) has rapidly advanced and made notable contributions to many surface observation fields, providing new means for identifying algal blooms. Additionally, meteorological parameters such as temperature and wind speed, key factors in the occurrence of algal blooms, can aid in their identification. This paper utilized Cyclone GNSS (CYGNSS) data, Sentinel-3 OLCI data, and ECMWF Re-Analysis-5 meteorological data to retrieve Chlorophyll-a values. Machine learning algorithms were then employed to classify algal blooms for early warning based on Chlorophyll-a concentration. Experiments and validations were conducted from May 2023 to September 2023 in the Hongze Lake region of China. The results indicate that classification and early warning of algal blooms based on CYGNSS data produced reliable results. The ability of CYGNSS data to accurately reflect the severity of algal blooms opens new avenues for environmental monitoring and management.

Analysis of the Physiological Parameters of Cold Resistance in Core Winter and Spring Wheat Cultivars

We selected 46 core winter–spring wheat cultivars from China’s main wheat-producing areas as experimental materials to clarify the differences in the physiological parameters of their cold resistance and provide a theoretical basis and high-quality germplasm for cold resistance breeding. We investigated differences in their cold resistance under field conditions for two consecutive years, and determined the physiological parameters of the cold resistance, yield, and quality indicators of different winter–spring wheat cultivars. Our results showed that the cold resistance of winter wheat cultivars was higher than that of spring wheat cultivars. The chlorophyll (Chl), soluble sugar (SS), soluble protein (SP), and free proline (Pro) contents of different winter–spring wheat cultivars were positively correlated with cold resistance, and malondialdehyde (MDA) content was negatively correlated with cold resistance. The five physiological parameters can be used as physiological indicators for the breeding of cold-resistant cultivars. The cold resistance, yield, and quality indicators of different spring and winter wheat cultivars were comprehensively evaluated by using the average membership value and comprehensive score. It was found that the average membership value and comprehensive score of winter wheat cultivars were higher than those of spring wheat cultivars. Through classification using the K-means method, the cold-resistant, high-yield, and high-quality cultivars were screened out, namely, Jimai23 (JM23), Jimai44 (JM44), Shannong57 (SN57), and Jinmai 919 (JM919).

Estimation of bacterio‐, picophyto‐ and nanophytoplankton abundance in the Middle Caspian Sea by flow cytometry

Aim. For the first time, flow cytometry has been used to study the structure and functional characteristics of bacterio‐, pico‐ and nano‐ phytoplankton in the Middle Caspian during the bloom period in early September 2022.Water samples were taken at different horizons (from the surface to the bottom layer) at a series of stations along the western coast of the Caspian Sea on the border between its northern and central parts to quantitatively assess heterotrophic bacterioplankton, picophyto‐ and nanophy‐ toplankton. Sampling was undertaken in early September 2022 under summer hydrological conditions with water surface temperatures ranging from 24.7°C to 26.7°C. Sample analysis was performed using flow cytometry.Extremely high concentrations of picophytoplankton (up to 1.8×105 cells/mL), probably of Synechococcus picocyanobacteria, were detected off the northwestern coast of the Middle Caspian. Very high values of nanophytoplankton abundance (up to 1.6×105 cells/mL), dominated by small flagellates, were also found. A clear spatial uncoupling of pico‐ and nanophytoplankton was revealed. Maximum levels of nanophytoplankton were confined to the area of intensive phytoplankton blooming with high concentrations of chlorophyll a, while picophytoplankton reached peak abundance further south, outside this area. The influence of the thermocline on the vertical structure of microbial communities was detected. The concentrations of picophytoplankton and the proportion of physiologically active HNA‐bacteria decreased sharply under the thermocline.The results obtained indicate the leading role of the smallest phototrophs in the Caspian pelagial and emphasise the need for further comprehensive studies of Caspian microbial communities using modern methods.

Response of Different Exogenous Phytohormones to Rice Yield Under Low-Temperature Stress at the Filling Stage

This paper aims to clarify the effects of different exogenous phytohormones on the physiological traits of rice (Oryza sativa L.) at the early stage of irrigation under low-temperature stress. In this study, two types of rice varieties with different temperature sensitivities screened out previously, namely, a cold-tolerant variety (Nan Jing 9108) and a low-temperature-sensitive variety (Hui Liang You 898), were used in pots to simulate the process of low-temperature stress in rice at the early stage of grouting (6–9 days after anthesis) with artificial low-temperature treatments. The experimental treatments were 450 mg L−1 Methyl jasmine acid (MJ), 46 mg L−1 Melatonin (MT), 69 mg L−1 Salicylate (SA), 40 mg L−1 Erythromycin (GA3), 25 mg L−1 Zeatin (Z), 145 mg L−1 Spermidine (SPD), and 5 mg L−1 Abscisic acid (ABA) sprayed on rice before low-temperature stress, while low-temperature treatment without spraying (DK) and conventional planting without spraying (CK) were added as the control. The results showed that compared with the room temperature control (CK, sprayed with deionized water), the low-temperature control (DK, low-temperature treatment, and sprayed with deionized water) all significantly reduced the rice grain yield. Different exogenous hormones sprayed before low-temperature stress could increase rice yield, among which, Z and SPD spraying treatments had a better effect on the yield of Hui Liang You 898, while different exogenous hormone treatments increased the yield of Nan Jing 9108 in an average manner. The Z and SPD treatments increased the yield of Hui Liang You 898 by 24.87% and 26.16% and that of Nan Jing 9108 by 15.87% and 17.80%, respectively. This was mainly attributed to the significant increase in thousand-grain weight and fruiting rate, while there was no significant difference in the number of spikes and number of grains. The different exogenous hormone treatments were able to delay leaf senescence, enhance the photosynthetic production capacity of plants by increasing leaf chlorophyll content, and thus increase the accumulation of photosynthetic assimilation products and population growth rate after flowering. Among them, both Z and SPD treatments resulted in a population growth rate of more than 30% from spike flushing to maturity, which led to a higher dry matter accumulation of the plant at maturity. In addition, in the dry matter distribution of the plant at maturity, the seeds occupied a higher accumulation amount and proportion compared with the respective DK; the SPD treatment resulted in the maximum distribution rate of seeds at maturity of Hui Liang You 898, with an increase of 8.27%, and the Z treatment resulted in the maximum distribution rate of seeds at maturity of Nan Jing 9108, with an increase of 7.34%. At the same time, the Z treatment significantly increased the activities of adenosine diphosphate glucose phosphorylated enzyme (AGP) and starch branching enzyme (SBE) in the grains of both varieties, which resulted in the accumulation of more starch and ultimately increased the rice grain yield. The results verified that different exogenous phytohormones could be used to regulate the insufficiency of grouting caused by low-temperature stress during the grouting and fruiting stages of rice and enriched their agronomic and physiological traits in response at the same time.

Foliar Nourishment with Different Potassium Sources to Maximize Yield Through Improving Nutrient Uptake in Citrus Aurantifolia Trees Grown in Potassium-Deficient Soil

AbstractPurpose: Based on its crucial regulatory role in several biochemical processes, potassium (K) is considered to greatly influence fruit yield and quality. Methods: Two field experiments were carried out in two seasons (2021 and 2022) to explore the response of lemon (Baladi cv.) trees grown in K-deficient soil to four different K fertilizer sources applied individually as a foliar spray. K citrate (KC1 = 1.3 vs. KC2 = 2.6 g L− 1), K nitrate (KN1 = 1.5 vs. KN2 = 3.0 g L− 1), K tartrate (KT1 = 1.5 vs. KT2 = 3.0 g L− 1), and K thiosulfate (KS1 = 1.25 vs. KS2 = 2.5 g L− 1) were applied three times, and the treated trees were compared with untreated trees. This study was established with a randomized complete block design (RCBD) using four replicates. Results: The findings revealed that the KC treatment, regardless of dosage, showed clear superiority in terms of the values for the leaf phosphorus (%), manganese, and zinc contents (mg kg− 1), as well as fruit firmness, fruit dry matter, and total soluble solids in both seasons. In second place was the KT treatment, which yielded the best values for fruit length and width in 2021, the best values for leaf nitrogen and iron contents and fruit weight and volume in 2022, and the best values regarding variable fluorescence by maximum fluorescence, relative chlorophyll content (SPAD readings), the photosynthetic performance index, total acidity, and vitamin C in both seasons. Furthermore, the highest total lemon yield and leaf potassium contents were achieved with the KN treatment in both seasons. The heat map illustrating that most of the studied characteristics were positively and significantly correlated with total lemon yield (TLY). Conclusions: The KN treatment, closely followed by the KC treatment, is regarded to be the best treatment for most of the studied trails.

A point mutation in the zinc-finger transcription factor CqLOL1 controls the green flesh color in chieh-qua (Benincasa hispida Cogn. var. Chieh-qua How).

Flesh color is an essential trait in chieh-qua (Benincasa hispida Cogn. var. Chieh-qua How); however, the inheritance and molecular basis of green flesh trait remain unclear. In the present study, two F2 populations, derived from 1742 (white flesh) × FJ3211 (green flesh) and J16 (white flesh) × FJ5 (green flesh), were used to identify the green flesh (Cqgf) locus. Genetic analysis revealed that the presence of green flesh was a quantitative trait that closely followed a normal distribution. Combining the results from QTL mapping and BSA-seq analysis, the Cqgf locus was preliminarily determined to be located on chromosome 05 and was narrowed down to a 2.55-Mb interval by linkage analysis. A large J16 × FJ5 F2 population comprising 3,180 individuals was subsequently used to screen the recombinants, and the Cqgf locus was fine-mapped to a region of 329.70 kb that harbors six genes. One of the candidate genes, Bch05G003700, the zinc-finger transcription factor LOL1 (lsd one like 1 protein; CqLOL1), was the strongest candidate gene for the Cqgf locus according to sequence variation and expression analysis. Additionally, a point mutation (A > C) in CqLOL1 resulted in the substitution of threonine (T) with proline (P) in the amino acid sequence, showing a complete relationship linked with flesh color in a panel of 45 germplasms. The study suggests that CqLOL1 promotes the accumulation of chlorophyll content in chieh-qua and lead to green flesh. Our findings establish a theoretical and technical foundation for breeding different flesh color lines and elucidating the underlying mechanisms of flesh color in chieh-qua.

PHOTOINACTIVATION OF CANDIDA ALBICANS BIOFILM WITH GREEN LASER MEDIATED BY THE PAPAYA LEAF EXTRACT CHLOROPHYLL

This study aims to activate the effectiveness of Photodynamic Inactivation (PDI) as an antibacterial agent by using a green laser and papaya leaf chlorophyll extract to prevent Candida albicans cell death. Papaya leaf extract chlorophyll is known to have potential as a photosensitizer (PS) through its antimicrobial properties and ability to absorb optimal light photons at a wavelength range of 405–680 nm. Activation of chlorophyll molecules with appropriate light produces Reactive Oxygen Species (ROS), which are toxic to pathogenic microbes such as Candida albicans. The research method involves using PDI with a green laser light source and chlorophyll extract on Candida albicans biofilms. Four main treatment groups were applied, negative control (C-), positive controls with 10% (C1+) and 15% chlorophyll (C2+), irradiation for 60, 120, 180, 240, and 300 seconds (L1–L5), and combinations of irradiation with chlorophyll (L1F1–L5F2, where F1 for 10% chlorophyll and F2 for 15% chlorophyll), with measurements performed three times for each treatment. Living Candida albicans cells were detected using the XTT assay staining method. The results showed a significant decrease in activity in all treatment groups. Maximum activity was achieved in the L5F1 and L5F2 treatment groups with inactivation of 80% (p<0.05) and 83% (p<0.05), respectively. This study concludes that high papaya leaf extract chlorophyll concentrations combined with a green laser effectively inhibit Candida albicans biofilm.

Response of Upwelling Parameter Before, During, and After Tropical Cyclone (Case Study: Tropical Cyclone Marcus)

Tropical cyclones (TC) can cause damage when they are on the land surface, but on the other hand TC contribute to ocean productivity through upwelling or downwelling when they pass through the ocean. Information of the location and timing of upwelling and downwelling is important for fishing - activities estimation. High chlorophyll-a concentrations and low sea surface temperatures are proxies for upwelling events in the ocean. This study aims to investigate the effects of the TC Marcus on the chlorophyll-a distribution in the Timor Sea using a combination of remotely sensed data from Aqua MODIS chlorophyll-a and ocean-atmosphere reanalysis outputs. The results showed that wind speed, sea surface temperature, salinity, and ocean currents were increased during the TC Marcus event. Spatial analysis reveals that the concentration of chlorophyll-a is high in the waters of the Timor Sea, at coordinates around 12°–13° S and 125°–129° E. High chlorophyll-a concentrations occurred before and after TC Marcus event, according to temporal analysis. The distribution of chlorophyll-a concentrations decreased on March 17–24, 2018, during the occurrence of the TC Marcus in the Timor Sea.

Inversion of biophysical parameters of potato based on an active learning pool-based sampling strategy

ABSTRACT Timely estimations of leaf chlorophyll content (LCC) and leaf area index (LAI) can provide critical information for potato field management. We employed a hybrid method that integrated machine learning with a radiative transfer model to estimate potato growth parameters. A look-up table was generated using the PROSAIL model, which was used as an unlabelled sample set. Measurements were taken from a potato field, and the data were labelled according to growth period and variety. Then, training samples for potato LCC, LAI, and canopy chlorophyll content (CCC) were selected from the simulated unlabelled sample set using the Euclidean distance-based diversity algorithm based on different labelled data sets. The training sample size required to accurately estimate the parameters varied considerably depending on the parameter, variety, and growth period, despite using the same labelled data set. Moreover, our results indicate that the growth period has a substantial impact on model accuracy and needs to be considered when constructing the labelled data set. The study results indicate that the hybrid method combined with the radiative transfer model and active learning can effectively select informative training samples from a data pool and improve the accuracy of potato parameter estimation, which provides a valid tool for accurately monitoring crop growth and growth health.

Physicochemical characteristics of cold-pressed blackcurrant-, strawberry-, and raspberry seed oils during storage and its influence on thermo-oxidative stability

The storage characteristics of cold-pressed blackcurrant-, strawberry- and raspberry seed oils and the factors influencing thermo-oxidative stability during storage were determined. It was established that throughout one year there were no significant (p ≤ 0.05) changes of thermo-oxidative stability (OIT at 120 and 140 °C) and fatty acid composition in all berry seed oils (BSO), despite a minor reduction in antioxidant activity (DPPH radical scavenging) and tocopherol content, and an increase in acid value, p-anisidine value, and K232, K268 values. Pigment degradation became noticeable after 6 months, resulting from a decrease in chlorophyll and carotenoid content, and observed in changes of colour parameters (angle hue, chroma, ΔE). The study also showed that many compositional factors play an important role in maintaining the thermo-oxidative stability of berry seed oils at a constant level over a period of one year, among which the most significant parameters influencing OIT values were the content of fatty acid c18:1, tocopherols and carotenoids, as revealed by the multiple linear regression analysis (MLR).

Cerium Oxide Nanoparticles (CeO2 NPs) Enhance Salt Tolerance in Spearmint (Mentha spicata L.) by Boosting the Antioxidant System and Increasing Essential Oil Composition

Salinity represents a considerable environmental risk, exerting deleterious effects on horticultural crops. Nanotechnology has recently emerged as a promising avenue for enhancing plant tolerance to abiotic stress. Among nanoparticles, cerium oxide nanoparticles (CeO2 NPs) have been demonstrated to mitigate certain stress effects, including salinity. In the present study, the impact of CeO2 NPs (0, 25, and 100 mg L−1) on various morphological traits, photosynthetic pigments, biochemical parameters, and the essential oil profile of spearmint plants under moderate (50 mM NaCl) and severe (100 mM NaCl) salinity stress conditions was examined. As expected, salinity reduced morphological parameters, including plant height, number of leaves, fresh and dry weight of leaves and shoots, as well as photosynthetic pigments, in comparison to control. Conversely, it led to an increase in the content of proline, total phenols, malondialdehyde (MDA), hydrogen peroxide (H2O2), and antioxidant enzyme activities. In terms of CeO2 NP applications, they improved the salinity tolerance of spearmint plants by increasing chlorophyll and carotenoid content, enhancing antioxidant enzyme activities, and lowering MDA and H2O2 levels. However, CeO2 NPs at 100 mg L−1 had adverse effects on certain physiological parameters, highlighting the need for careful consideration of the applied concentration of CeO2 NPs. Considering the response of essential oil compounds, combination of salinity stress and CeO2 treatments led to an increase in the concentrations of L-menthone, pulegone, and 1,8-cineole, which are the predominant compounds in spearmint essential oil. In summary, foliar application of CeO2 NPs strengthened the resilience of spearmint plants against salinity stress, offering new insights into the potential use of CeO2 NP treatments to enhance crop stress tolerance.