Color Index Research Articles

Geochemical Parameters of Oil and Rock Samples from Murzuq Basin, Libya: An Application for Paleoenvironment Description

Seven sedimentary rocks and seven crude oils undertook a geochemical analysis to describe their organic matter type and then tag the Paleoenvironments based on the organic matter. The samples were collected from B1-NC151, A1-NC58, P1- NC1, E1-NC174, D1-NC151, H29-NC115, and D1-NC174 boreholes, located in Murzuq Basin. The study was established to understand life forms in the ecosystem based on biomarkers that biochemical techniques recognized. Microscopy was used for kerogen typing and Spore Color Index reference. Organic matter (EOM) was extracted from cutting samples. Furthermore, hydrocarbons were saturated and aromatic fractionated from the samples to investigate using Gas chromatograph system. Spore color index (SCI), range between 1.5-3.5, Amorphous organic matter (AOM) from 42 to 95 percentage, Phytoclasts % were 4-15.5, and Palynomorphs % range 0.5 to 7.5. The percentage of Carbon 85.66-86.29, Hydrogen 13.16-13.73, Nitrogen 0.06 -0.27, and Sulfur 0.31-0.70, besides wax were measured, ranging among 1.3 to 6.0 %. Pristine/n-C17, Phytane/n-C18, Pristine/Phytane, carbon preference index measurements (CPI) and DBT/P as saturated hydrocarbon ratios from whole oil chromatographs were established. Tricyclic terpanes, hopanes and n-alkanes were distinguishing as the most important oil biomarkers that reserved the characteristics in the Paleoenvironments.

Estimating Summer Maize Biomass by Integrating UAV Multispectral Imagery with Crop Physiological Parameters

The aboveground biomass (AGB) of summer maize is an important indicator for assessing crop growth status and predicting yield, playing a significant role in agricultural management and decision-making. Traditional on-site measurements of AGB are limited, due to low efficiency and a lack of spatial information. The development of unmanned aerial vehicle (UAV) technology in agriculture offers a rapid and cost-effective method for obtaining crop growth information, but currently, the prediction accuracy of summer maize AGB based on UAVs is limited. This study focuses on the entire growth period of summer maize. Multispectral images of six key growth stages of maize were captured using a DJI Phantom 4 Pro, and color indices and elevation data (DEM) were extracted from these growth stage images. Combining measured data such as summer maize AGB and plant height, which were collected on the ground, and based on the three machine learning algorithms of partial least squares regression (PLSR), random forest (RF), and long short-term memory (LSTM), an input feature analysis of PH was carried out, and a prediction model of summer maize AGB was constructed. The results show that: (1) using unmanned aerial vehicle spectral data (CIS) alone to predict the biomass of summer maize has relatively poor prediction accuracy. Among the three models, the LSTM (CIS) model has the best simulation effect, with a coefficient of determination (R2) ranging from 0.516 to 0.649. The R2 of the RF (CIS) model is 0.446–0.537. The R2 of the PLSR (CIS) model is 0.323–0.401. (2) After adding plant height (PH) data, the accuracy and stability of model prediction significantly improved. R2 increased by about 25%, and both RMSE and NRSME decreased by about 20%. Among the three prediction models, the LSTM (PH + CIS) model had the best performance, with R2 = 0.744, root mean square error (RSME) = 4.833 g, and normalized root mean square error (NRSME) = 0.107. Compared to using only color indices (CIS) as the model input, adding plant height (PH) significantly enhances the prediction effect of AGB (aboveground biomass) prediction in key growth periods of summer maize. This method can serve as a reference for the precise monitoring of crop biomass status through remote sensing with unmanned aerial vehicles.

Role of Chitosan in the Coloring of Berries and Phytochemical Changes in Physalis angulata L. During Harvest Maturity

Physalis angulata L. berries are green in the initial stage of maturity and turn yellow when fully mature due to an increase in carotenoids. However, the coloration of the epidermis of the berry should not be the reference for harvesting maturity, since the calyx is fully closed. The use of an edible chitosan coating delays the color changes in the berry by reducing the respiration rate. This work studies the effect of harvest maturity and chitosan on the shelf life and berry coloring in Physalis angulata L. Three factors were considered, being harvest maturity stage (green mature (GM), yellowish-green (YG) and yellow (Y)), chitosan coating (0, 0.5, and 1%), and storage time (10, 20, 30 days). The fruits were stored at 20 °C and 85% Rh. The results showed that on the harvesting stage, chitosan coating had a significant effect on the quality and shelf life of berries during storage time. The value of carotenoid and phenol contents, flavor index, chroma, and hue significantly increased with berry maturity. Chitosan delayed the decrease in chlorophyll, phenol contents, antioxidant capacity, berry maturity, and color change. The results show that in the berries coated with 1% chitosan during storage, changes in color were less in comparison with the control condition (no chitosan). The highest decrease of hue angle and color index (17.92°) was observed in the control. The highest total antioxidant (78.42%) was observed after 30 days of storage in MG berries treated with a 0.5% chitosan coating.

Monitoring Meat Freshness with Intelligent Colorimetric Labels Containing Red Cabbage Anthocyanins Copigmented with Gelatin and Gallic Acid

Polyvinyl alcohol (PVA)-based pH-responsive color indicators were developed using red cabbage anthocyanin (Anth) copigmented with gelatin and gallic acid (GA). The indicator prepared with gelatin and GA (GA/gelatin/Anth/PVA) was highly resistant to light exposure. GA/gelatin/Anth/PVA exhibited distinct color changes in pH 2–11 buffer solutions and stable color indication in acidic and neutral solid systems (pH 2 and 7) at 97% relative humidity. GA/gelatin/Anth/PVA exhibited the highest sensitivity to dimethylamine, followed by ammonia and trimethylamine. The addition of gelatin and GA facilitated hydrogen bonding, which enhanced thermal stability and water solubility without compromising tensile properties. A color change from purple to blue signaled spoilage when total volatile basic nitrogen values for beef and squid reached 21.0 and 37.8 mg/100 g, respectively. The GA/gelatin/Anth/PVA indicator shows potential for indicating the freshness of raw beef.

Characterisation of the stellar wind in Cyg X-1 via modelling of colour-colour diagrams

Context. Cygnus X-1 (Cyg X-1) is a high-mass X-ray binary where accretion onto the black hole (BH) is mediated by the stellar wind from the blue supergiant companion star HDE 226868. Due to its inclination, the system is a perfect laboratory to study the not yet well-understood stellar wind structure. In fact, depending on the position of the BH along the orbit, X-ray observations can probe different layers of the stellar wind. Deeper wind layers can be investigated at superior conjunction (i.e. null orbital phases). Aims. We aim to characterise the stellar wind in the Cyg X-1/HDE 226868 system, analysing one passage at superior conjunction covered by XMM-Newton during the ‘Cyg X-1 Hard state Observations of a Complete Binary Orbit in X-rays’ (CHOCBOX) campaign. Methods. To analyse the properties of the stellar wind, we computed colour-colour diagrams. Since X-ray absorption is energy-dependent, colour indices provide information on the parameters of the stellar wind, such as the column density, NH, w, and the covering factor, fc. We fitted colour-colour diagrams with models that include both a continuum and a stellar wind component. We used the kernel density estimation method to infer the unknown probability distribution of the data points in the colour-colour diagram, and selected the model corresponding to the highest likelihood. In order to study the temporal evolution of the wind around superior conjunction, we extracted and fitted time-resolved colour-colour diagrams. Results. We found that the model that best describes the shape of the colour-colour diagram of Cyg X-1 at superior conjunction requires the wind to be partially ionised. The shape of the colour-colour diagram strongly varies during the analysed observation, due to concurrent changes of the mean NH, w and the fc of the wind. Our results suggest the existence of a linear scaling between the rapid variability amplitude of NH, w (on timescales between 10 s and 11 ks) and its long-term variations (on timescales > 11 ks). Using the inferred best-fit values, we estimated the stellar mass loss rate to be ∼7 × 10−6 M⊙ yr−1 and the clumps to have a characteristic mass of ∼1017 g.

The integration and transformative design research of plant dyeing techniques in Dong brocade with sustainable materials

Dong brocade, a fabric renowned for its intricate patterns and ethnic symbolism, has been woven by the Dong people for generations, showcasing their cultural significance. Traditional plant dyeing technology is one of the main aspects of Dong brocade but the documentation and understanding of this is still rather limited. With regard to the use of plant dye in Dong brocade, it is not as well explored as it should be since it has a traditional aspect. The main purpose is to investigate and apply the traditional plant dyeing technique to Dong brocade for the improvement of that sustainable concept and the preservation of cultural assets. Therefore, 121 Dong villagers were interviewed to elicit their awareness regarding prehistoric plant dyeing. By observing the dyeing conditions, this study provided accurate perception and learned how to differentiate between natural and synthetic mordants through ethnobotanical perception. The strategy is intended to integrate sustainable products into Dong brocade, employing orthogonal array development to find the right dyeing conditions for corresponding plant dyes. Research revealed that 8 genera of plants which include 7 species are used in dyeing Dong brocade. The findings presented in this work prove the effectiveness of the use of plant dyes in Dong brocade, showing its advantages with 30% of frequency and CI (Color Index) indices, 8% of them being cultural. 5 for ethnic cultural sustainment, developmental and bio-diversity reasons respectively. The unique integration between the traditional dyeing technique in Dong brocade and the utilization of sustainable resources is very promising for the improvement of identity enhancement and embodiment, and the preservation of the environment.

Variations of flare energy release behaviour and magnetic loop characteristics versus absolute stellar parameters

ABSTRACT In this paper, we examine how stellar flare activity varies with evolution stage, rotation period, and spectral type. To do this, we examine the distributions of the flare equivalent duration on a logarithmic scale, which we consider as an indicator of the maximum energy level that a star can reach in white-light flares. We conduct these analyses using two distinct statistical models of data obtained from white-light flare patrols of 33 stars. These models are the one-phase exponential association (OPEA) and cumulative flare frequency models. The results show that the value of the OPEA model parameter Plateau has a linear relationship with the stellar B – V colour index and the rotation period. In addition, it is shown that flare time-scales, and therefore the maximum magnetic loop height that stars can have, vary according to the evolutionary stage of the star. Finally, it is concluded that the cumulative flare frequency parameters of the stars are not as effective as the OPEA parameters at exhibiting these variations.

Brown algae of the White Sea as a promising source of fucoidan for increasing resistance in laying hens

The purpose of this study was to evaluate the effect of a feed additive from fucus algae on resistance indicators of laying hens in industrial poultry farming conditions. In the algae F. vesiculosus and A. Nodosum, it was revealed that the mass fraction of fucoidan in terms of a.d.w. is 3.92±0.12%.When assessing the effect of using a feed additive from fucus algae on resistance indicators of laying hens, it was revealed that it has an effect on white and red blood parameters, leukogram and phagocyte activity. In chickens of the experimental group, there was a tendency towards an increase in the number of erythrocytes, an increase in the color index, a tendency towards a decrease in the number of leukocytes relative to the increase in the control group, while the indicators were within the reference values, after 30 days of using the additive – in the experimental group the proportion of pseudoeosinovils increased by 50% and the proportion of lymphocytes decreased by 6% compared to the control group. After 60 days of using the supplement, this trend continues: the proportion of pseudoeosinophils increased by 22% and the proportion of lymphocytes decreased by 4% in the experimental group relative to the control group. In our opinion, this indicates a normalization of the ratio of leukocyte forms in the experimental group, and, consequently, the immune status. In addition, in the experimental group relative to the control group, there was a significant decrease in the number of eosinophils by 67%, which may indicate a lower allergic reaction of the body’s immune system. Indicators of blood phagocytosis significantly changed after 60 days of use: in the experimental group, phagocytic activity increased by 23%, which indicates a higher ability of leukocytes in the experimental group to absorb foreign bacteria, and, consequently, stronger cellular immunity compared to the control group. Thus, the use of a feed additive from fucus algae for laying hens containing fucoidan in an amount of 3.92±0.12% helps to normalize the ratio of leukocyte forms and increase blood phagocytosis rates, which significantly increases resistance in laying hens.

An Assessment of Water Quality and Pollution Sources in a Source Region of Northwest China

China prioritizes ensuring drinking water safety, particularly in the water-scarce northwest region. This study, utilizing water quality data from 52 village and town water sources since August 2022, assesses water quality, with a specific focus on key indicators related to organic pollution sources. This study provides a scientific foundation for enhancing water quality in these sources. Employing category factor analysis for classification and grading, principal component analysis for qualitative analysis of key evaluation indicators, and the absolute principal component linear regression equation for quantitative calculation of pollution sources, this study reveals that all 52 water sources meet quality standards. Principal component analysis categorizes pollution sources as diverse types of organic compounds in surface water. Source analysis calculations highlight decay-type organic substances as major contributors to increased water color and permanganate index, with pollution contribution rates of 54.78% and 31.31%, respectively. Fecal-type organic substances dominate the increase in dissolved total solids and total coliforms, with pollution contribution rates of 56.65% and 40.16%, respectively. Additionally, high-molecular-weight organic substances exhibit lower concentrations in the water. This article presents a systematic water quality assessment methodology, which is used for the first time to qualitatively assess the types of water sources and to quantitatively trace specific sources of organic pollution in source water in northwest China. This systematic study’s results, involving initial assessment followed by traceability, recommend the adoption of a simple contact filtration and disinfection process to enhance water quality in the region.

Transcriptome analyses of shell color and egg production traits between the uteruses of blue-green eggshell chickens and Hy-Line brown layers

Blue-green eggs exhibit unique shell color; however, compared to commercial layers, blue-green eggshell chickens have lower egg production and lack uniform shell colors. Aiming to confirm the molecular mechanisms that affect shell color and egg production, this study collected the uteruses of 12 blue-green eggshell chickens (BG group) and six Hy-Line layers (Brown group), which had significantly different shell color indexes (SCI) and egg numbers at 300 days of age (EN300). Transcriptome sequencing and comparative analyses were subsequently performed. BG hens were divided into two groups for comparative analysis (BGblue vs. BGgreen and BGlow vs. BGhigh, respectively), based on the differences in SCI and EN300, respectively. The result of weighted gene co-expression network (WGCNA) analysis showed that the sequenced and mapped 16,785 genes were clustered into 18 modules, among which six modules with a total of 4270 genes were highly correlated with SCI and EN300 traits. Five hundred and eleven differentially expressed genes (DEGs) belonged to the six key modules. Through KEGG mapping, GO enrichment, and Cytoscape network analysis, nine Hub genes were tightly associated with SCI and EN300. The up-regulated genes were CCR2, CCR8, CD40LG, IL18RAP, INHBA, and P2RY13, while the down-regulated genes were ABCA13, ADCY2, and GRM1. Co-analyses with the results of comparisons between the BG subgroups revealed that the expression of solute carrier (SLC) proteins and ABC transporters were highly related to eggshell color, while cytokine-cytokine receptor interactions and neuroactive ligand-receptor interactions were key pathways affecting egg production. The expression of extracellular cytokines and membrane receptors were significantly up-regulated in low-yield chickens. The candidate DEGs and pathways found in the study will assist in clarifying the molecular mechanisms affecting shell color and egg production, and improve the breeding of blue-green eggshell chickens.

Impact of Plant Growth-Promoting Microorganism (PGPM) Consortium on Biochemical Properties and Yields of Tomato Under Drought Stress.

Drought is the most important abiotic stress that restricts the genetically predetermined yield potential of the crops. In the present study, four tomato varieties: Kashi Vishesh, Kashi Aman, Kashi Abhiman, and Kashi Amrit, were used to study the effect of PGPMs (plant growth-promoting microorganisms). PGPM strains, Bacillus megaterium BHUPSB14, Pseudomonas fluorescens BHUPSB06, Pseudomonas aeruginosa BHUPSB01, Pseudomonas putida BHUPSB0, Paenibacillus polymixa BHUPSB17, and Trichoderma horzianum, were used as the consortium. The control group was irrigated up to 80% of field capacity, while 7-, 14-, and 21-day water-deficit-exposed (DWD) plants' pot soil moisture was maintained to 40, 25, and 15% of the field capacity, both with and without the PGPM inoculation condition. The physiological parameters, such as electrolyte leakage, relative water content, photosynthetic efficiency, and chlorophyll color index, were significantly improved by PGPM application under progressive drought stress, compared to the control. PGPM application enhanced the proline accumulation and reduced the formation of hydrogen peroxide and lipid peroxidation under drought stress. The plant growth attributes were significantly increased by PGPM application. The Kashi Amrit variety showed the highest fruit yield among the four varieties under all the treatments. The PGPM consortium application also improved the soil physico-biological properties and nutrient availability in the soil. The PGPM consortium used in this study can potentially mitigate drought stress on tomato in drought-prone regions and act as a biofertilizer. The present study will open a new avenue of drought stress management in tomato.

Visualizing Plant Responses: Novel Insights Possible Through Affordable Imaging Techniques in the Greenhouse.

Efficient and affordable plant phenotyping methods are an essential response to global climatic pressures. This study demonstrates the continued potential of consumer-grade photography to capture plant phenotypic traits in turfgrass and derive new calculations. Yet the effects of image corrections on individual calculations are often unreported. Turfgrass lysimeters were photographed over 8 weeks using a custom lightbox and consumer-grade camera. Subsequent imagery was analyzed for area of cover, color metrics, and sensitivity to image corrections. Findings were compared to active spectral reflectance data and previously reported measurements of visual quality, productivity, and water use. Results confirm that Red-Green-Blue imagery effectively measures plant treatment effects. Notable correlations were observed for corrected imagery, including between yellow fractional area with human visual quality ratings (r = -0.89), dark green color index with clipping productivity (r = 0.61), and an index combination term with water use (r = -0.60). The calculation of green fractional area correlated with Normalized Difference Vegetation Index (r = 0.91), and its RED reflectance spectra (r = -0.87). A new chromatic ratio correlated with Normalized Difference Red-Edge index (r = 0.90) and its Red-Edge reflectance spectra (r = -0.74), while a new calculation correlated strongest to Near-Infrared (r = 0.90). Additionally, the combined index term significantly differentiated between the treatment effects of date, mowing height, deficit irrigation, and their interactions (p < 0.001). Sensitivity and statistical analyses of typical image file formats and corrections that included JPEG, TIFF, geometric lens distortion correction, and color correction were conducted. Findings highlight the need for more standardization in image corrections and to determine the biological relevance of the new image data calculations.

Prepartum supplementation of dairy cows with inorganic selenium, organic selenium or rumen-protected choline does not affect carotenoid composition or colour characteristics of bovine colostrum or transition milk.

Minerals are supplemented routinely to dairy cows during the dry period to prevent metabolic issues postpartum. However, limited information exists on the impacts of mineral supplementation on colostrum carotenoids. This study aimed to determine the effects of prepartum supplementation with three micro-nutrients; inorganic selenium (INORG), organic selenium (ORG) or rumen-protected choline (RPC) on the carotenoid content of bovine colostrum and transition milk (TM) from pasture-based dairy cows. A total of 57 (12 primiparous and 45 multiparous) Holstein-Friesian (HF) and HF × Jersey (JEX) cows were supplemented daily for 49 ± 12.9 d before calving. Colostrum samples were collected from all cows immediately postpartum and TM one to five (TM1-TM5) were collected from a sub-set of 15 cows (five per treatment group) at each consecutive milking postpartum. Carotenoid concentration was determined using ultra-high performance liquid chromatography - diode array detection (UHPLC-DAD). With the use of transmittance, the colour index and colour parameters a*, b* and L* were used to determine colour variations over this period. Prepartum supplementation did not have a significant effect on colostrum β-carotene concentration or colour. Positive correlations between β-carotene and colour parameter b* (R2 = 0.671; P < 0.001) and β-carotene and colour index (R2 = 0.560; P < 0.001) were observed. Concentrations of β-carotene were highest in colostrum (1.34 μg/g) and decreased significantly with each milking postpartum (TM5 0.31 μg/g). Breed had a significant effect on colostrum colour with JEX animals producing a greater b* colostrum than HF animals (P = 0.030). Primiparous animals produced colostrum with the weakest colour compared to second or ≥third parity animals (P = 0.042). Despite statistical increases in the b* parameter in colostrum from JEX cows and multiparous cows, β-carotene concentrations did not significantly increase suggesting that other factors may influence colostrum colour. The b* parameter may be used as an indicator for estimating carotenoid concentrations in colostrum and TM, particularly when assessed via transmittance spectroscopy.

Productivity, quality and suitability for processing of various potato varieties when grown in the conditions of the Central region of the Russian Federation

Relevance. The study of the reaction of potato varieties, especially new ones, to the use of a complex of agrotechnical techniques, including foliar top dressing with water-soluble fertilizers, is an urgent task. For this purpose, 4 potato varieties of different ripeness groups (Red Scarlett, Nevsky, Golubizna, Grand) were studied in two regions of Russia using agrochemicals Agrovin Micro. Methods. The article presents experimental data on the study of biometric indicators, yield and quality of potatoes for non-root top dressing in conditions of leached chernozem and sod-podzolic sandy loam soils of the Central region of Russia. The objects of research were potato varieties of various ripeness groups. Foliar fertilization of plants with agrochemicals Agrovin Micro was carried out in the phases of germination, budding and 20 days after the last treatment in two consumption rates – 1.0 and 2.0 l / ha. Control – without processing (K) with background N90Р90К135.Results. On average, over the years of research, the best options for all varieties turned out to be options with the use of additional leaf treatment with an agrochemical at a maximum dose of 2 liters /ha. Due to three-fold foliar top dressing for the critical phases of potato plant growth, the greatest yield increases and maximum values of dry matter and starch content to the mineral background were obtained. In the conditions of the Tambov region, the increase in yield, depending on the variety, ranged from 24.2 to 59.3% or 6.0-10.5 /ha and in the conditions of the Moscow region – 3.3-28.9% or 1.2-7.1 t/ha. The most suitable for processing into fried potato products from the studied varieties turned out to be Red Scarlett and Grand. All other things being equal, the color index of crispy potatoes and fries on these varieties was higher than the Nevsky variety by 1.0-1.5 points.

Effects of subsurface drip fertigation on potato growth, yield, and soil moisture dynamics

AimsThis study aimed to evaluate the impact of subsurface drip fertigation (SDF) on soil moisture content, potato growth, and tuber yield in loam soils, and compare these results with conventional surface drip fertigation (CF). The focus was on determining whether SDF could improve water use efficiency and yield quality, particularly in water-scarce regions.MethodsThe experiment was conducted during the 2022 spring growing season in Xunyang, Ankang, Shaanxi Province, China. A randomized complete block design (RCBD) was used with three treatments: subsurface drip fertigation (SDF), conventional surface drip fertigation (CF), and a no-fertilization control (NF), with four replications per treatment. Soil moisture content at a 20 cm depth was monitored, and plant growth parameters such as plant height, stem diameter, leaf color index, and chlorophyll fluorescence index were measured during the flowering and harvest stages. Tuber yield characteristics, including tuber diameter, number of tubers per plant, total yield, and marketable yield, were also assessed.Important findingsThe results indicated that subsurface drip fertigation significantly improved soil moisture content, with up to 45.5% higher moisture retention compared to conventional fertigation, particularly in the early stages of fertilization. This improved moisture availability led to enhanced plant growth and tuber development. Tuber diameter increased by 6.9 mm, and the number of tubers per plant increased by 18.1% under SDF. Marketable tuber yield was approximately 10% higher in the SDF treatment compared to CF. However, the study found that soil texture plays a critical role in the effectiveness of SDF, and further research is needed to explore its application in other soil types.

Exogenous N Supply on N Transportation and Reuse during the Rice Grain-Filling Stage and Its Relationship with Leaf Color-Changing Parameters

During the later reproductive period of rice growth, the chlorophyll in the leaves degraded, accompanied by the nitrogen (N) transportation from leaves to panicle, resulting in a change in leaf color from green to yellow. This study aimed to investigate the effects of exogenous N supply on leaf color-changing, N accumulation, N transportation, and N loss of indica-japonica hybrid rice during the grain-filling stage. Two indica-japonica hybrid rice cultivars, Chunyou 167 (CY167) and Chunyou 927 (CY927), which exhibited significant differences in leaf color-changing during the grain-filling stage, were selected as materials for field experiment and hydroponic experiment with low, medium, and high N treatments (LN, MN, and HN). The dynamic changes in SPAD value from heading to maturity were measured and fitted with quadratic function to extract leaf color-changing parameters; labeled 15N was used as N source after heading to trace the source of N in the panicle and the remobilization of vegetative organ N. The results showed that 67.37–72.38% of the panicle N was transported from vegetative organs, the N transport efficiency was the upper three leaves &gt; lower leaves &gt; stem, and about 3.1–35.0% of the transported N was lost via volatilization. The effects of exogenous N concentration on N harvest index, N dry matter/grain production efficiency, N reuse efficiency, and N loss were closely related to leaf color-changing parameters. In MN and HN treatment, the N loss was negatively correlated with the onset time of leaf color-changing (T0) and the final leaf color index (CIf), but positively correlated with the leaf color-changing rate (Rmean). Increasing the supply of exogenous N increased T0 and CIf, but decreased Rmean, N transport/reuse efficiency, N harvest index, and N dry matter/grain production efficiency. Compared to the cultivar CY167 with normal leaf color-changing, the “stay-green” cultivar CY927 had higher T0, CIf, and lower Rmean, resulting in less N volatilization loss, lower N harvest index and N transport efficiency, while higher N reuse efficiency. In conclusion, the exogenous N supply affects leaf color by influencing the transportation and reuse of leaf N during the grain-filling stage.

On the рossibility of multichannel optical backscattering sondes for joint balloon and lidar studies of the aerosol composition of the middle atmosphere

Aerosol backscattering sondes in the practice of aerological sounding, along with lidar observations, are used at night to study and monitor polar stratospheric clouds, tropospheric and stratospheric aerosol, cirrus clouds, pyroconvection, volcanic aerosol, as well as to verify remote methods and means of ground-based and satellite-based aerosol observations. For aerosol sondes, a simple two-wave measurement technique is used, which makes it possible to diagnose changes in aerosol composition by color index. The possibilities of the two-wave technique have limitations, which are discussed in this article. Aerological sounding combined with lidar observations expands the wavelength range for multi-wavelength studies, and direct measurements of atmospheric temperature increase the accuracy of aerosol sensing. The paper considers the application of 3 or more wavelenght techniques. Data from probe measurements using wavelengths of 470, 528, 850 and 940 nm and lidar sensing at wavelengths of 355 and 532 nm are presented.

Development of ExG, ExR, ExGR, HSV, CIELAB Images from RGB Images Using Image Segmentation Algorithm in Computer Vision Based Herbicide Spraying Applications

Weed management in agriculture is critical for preventing crop yield losses, with traditional methods often leading to environmental harm and increased production costs. This study explores the development of color indices and models for weed detection in computer vision-based herbicide spraying applications. Among the all sensors, RGB colour cameras offer several advantages, including low cost and wide availability of image processing libraries tailored for RGB image analysis. In present study a Logitech C270 webcam was used for acquiring the RGB images and a specially python algorithm was developed for image segmentation based on color. Excess Green (ExG), Excess Red (ExR), Excess Green minus Red (ExGR), HSV, and CIELAB color model images are developed by using algorithm. The research demonstrates that while ExG and ExGR indices are effective under specific conditions, the CIELAB model offers superior segmentation results across varying lighting environments. Among all these color indices and models, particularly CIELAB, can enhance the precision of weed detection in automated herbicide applications, thereby reducing environmental impact and improving agricultural efficiency.

Determining the effect of high hydrostatic pressure on the refrigerated stability of avocado puree

The present study aimed to extend refrigerated stability of locally grown avocado fruit by applying High Hydrostatic Pressure (HHP) treatment. HHP was applied at 600 MPa for 3 min to avocado puree and stored at 4 °C for 28 days. Physicochemical (colour CIE L*, a*, b*, total oil amount, chlorophyll, pH, moisture) and microbiological (mesophilic, yeast-mould) analyses were performed at seven-day intervals on both control (untreated) and HHP-treated sample packs. It could be judged that HHP treatment effectively controlled the colour indices, preventing undesired changes during the cold storage period of avocado puree. In conclusion, this study demonstrated that HHP-processed avocado puree exhibited stability for 28 days compared to unprocessed puree at 4 °C. The shelf-life stability of avocado puree under chilled conditions was extended from 7 to 28 days.Graphical

Re-evaluating winter carbon sink in Southern Ocean by recovering MODIS-Aqua chlorophyll-a product at high solar zenith angles

Satellite ocean color observations are extensively utilized in global carbon sink evaluation. However, the valid coverage of chlorophyll-a concentration (Chla, mg m−3) measurements from these observations is severely limited during autumn and winter in high latitude oceans. The high solar zenith angle (SZA) stands as one of the primary contributors to the reduced quality of Chla products in the high-latitude Southern Ocean during these seasons. This study addresses this challenge by employing a random forest-based regression ensemble (RFRE) method to enhance the quality of Moderate Resolution Imaging Spectroradiometer (MODIS) Chla products affected by high SZA conditions. The RFRE model incorporates the color index (CI), band-ratio index (R), SZA, sensor zenith angle (senz), and Rayleigh-corrected reflectance at 869 nm (Rrc(869)) as predictors. The results indicate that the RFRE model significantly increased the MODIS observed Chla coverage (1.03 to 3.24 times) in high-latitude Southern Ocean regions to the quality of standard Chla products. By applying the recovered Chla to re-evaluate the carbon sink in South Ocean, results showed that the Southern Ocean’s ability to absorb carbon dioxide (CO2) in winter has been underestimated (5.9–18.6 Tg C year−1) in previous assessments. This study underscores the significance of improving the Chla products for a more accurate estimation of winter carbon sink in the Southern Ocean.