Apple Leaves Research Articles

Estimation of Chlorophyll Content in Apple Leaves Infected with Mosaic Disease by Combining Spectral and Textural Information Using Hyperspectral Images

Leaf chlorophyll content (LCC) is an important indicator of plant nutritional status and can be a guide for plant disease diagnosis. In this study, we took apple leaves infected with mosaic disease as a research object and extracted two types of information on spectral and textural features from hyperspectral images, with a view to realizing non-destructive detection of LCC. First, the collected hyperspectral images were preprocessed and spectral reflectance was extracted in the region of interest. Subsequently, we used the successive projections algorithm (SPA) to select the optimal wavelengths (OWs) and extracted eight basic textural features using the gray-level co-occurrence matrix (GLCM). In addition, composite spectral and textural metrics, including vegetation indices (VIs), normalized difference texture indices (NDTIs), difference texture indices (DTIs), and ratio texture indices (RTIs) were calculated. Third, we applied the maximal information coefficient (MIC) algorithm to select significant VIs and basic textures, as well as the tandem method was used to fuse the spectral and textural features. Finally, we employ support vector regression (SVR), backpropagation neural network (BPNN), and K-nearest neighbors regression (KNNR) methods to explore the efficacy of single and combined feature models for estimating LCC. The results showed that the VIs model (R2 = 0.8532, RMSE = 2.1444, RPD = 2.6179) and the NDTIs model (R2 = 0.7927, RMSE = 2.7453, RPD = 2.2032) achieved the best results among the single feature models for spectra and texture, respectively. However, textural features generally exhibit inferior regression performance compared to spectral features and are unsuitable for standalone applications. Combining textural and spectral information can potentially improve the single feature models. Specifically, when combining NDTIs with VIs as input parameters, three machine learning models outperform the best single feature model. Ultimately, SVR achieves the highest performance among the LCC regression models (R2 = 0.8665, RMSE = 1.8871, RPD = 2.7454). This study reveals that combining textural and spectral information improves the quantitative detection of LCC in apple leaves infected with mosaic disease, leading to higher estimation accuracy.

Development of Eco-friendly Handmade Paper and Paper Board from Soft Bamboo, Whole Banana & Pine Apple Leaves Fibre- Available in N.e. Region of India

The studies were carried out to established suitability of lingo-cellulosic raw materials namely Soft Bamboo (Dendrocalamus arundinacea), Banana (Musa Sapientum) & Pineapple (Ananas Comosus) for making pulps for handmade paper industry which are abundantly available in north eastern part of India. This should help in providing a cost effective, good quality cellulosic raw material as an alternate to cost prohibitive traditionally used cotton hosiery waste traditionally used for manufacturing good quality handmade paper & it’s products. This will help in improving the cost economics & competitiveness of the Indian paper industry in the global market besides addressing the problems of environment & global warming. The Studies thus carried out provide useful information about the nature of these raw materials, suitable pulping process to produce an eco-friendly handmade paper and board & converted products. The research work provides a good quality cost effective lingo-cellulosic raw material for handmade paper industries with a possibility of replacement of the expensive and traditionally used cotton hosiery waste. The paper thus produced using environmental friendly pulping and bleaching process is characterized for its strength properties like tensile, tear, bursting, folding endurance and other parameters. Further the study will be useful in providing opportunities for employment generation and income enhancement among the rural masses as well as addressing the bio-mass dumping.

Analytical method for the determination of Hg from the organs of some terrestrial plants using cold vapor atomic absorption spectrometry

The aim of the study was to develop a new method for mercury determination from plants grown on mercury-polluted soils as well as to evaluate the mobility and bioavailability of mercury in the soil and its transfer to different plant organs (root, stem, leaves) from three different plants, such as mustard (Sinapis alba), thyme (Thymus serpyllum) and wild thyme. A cold vapor atomic absorption spectrometry (CV-AAS) method for the detection of mercury in plants was developed. The developed method was validated in the laboratory and was verified using two different certified reference materials (CRMs) type matrices, namely: NIST 1515 Apple Leaves and BCR-482 Lichen.

Stability of sodium mass fraction in agricultural certified reference materials

Certified values in reference materials are considered the best estimates of true values, being used for validation and verification of analytical methods. A long-term series (1998 to 2019) of neutron activation analysis (NAA) of agricultural certified reference materials was investigated at the Radioisotopes Laboratory (CENA/USP). The average sodium mass fraction in SRM 1515 Apple Leaves and SRM 1547 Peach Leaves did not agree with the certified values and the discrepancy was confirmed by triple quadrupole inductively coupled plasma mass spectrometry (TQ-ICP-MS). Long-term data showed a clear increase of Na mass fraction over time. Such behavior, corroborated by results from other authors, seems to confirm the hypothesis of migration of Na from glass bottle walls into the certified reference materials.

Flame atomic absorption spectrometric determination of multi element in apricot and soil samples after wet and microwave digestion method

Iron, copper, zinc, manganese, nickel, cobalt, lead, cadmium and chromium in various apricot and soil samples were determined by atomic absorption spectrometry in this study. Microwave digestion method and wet ashing method efficiency were compared for digestion of the samples. Recovery values were nearly found quantitative. The analysis results were evaluated. The accuracy of the digestion procedures was confirmed by analyzing Montana Soil and Apple Leaves certified reference materials. There are no important differences between digestion methods. The results were compared with literature values. Relative standard deviations were found below 10 %. Heavy metal levels in analyzed samples were not found toxic limits.

Endophytic Bacterial Communities in Apple Leaves Are Minimally Impacted by Streptomycin Use for Fire Blight Management

In apple fruit, streptomycin is routinely used to manage fire blight, a devastating disease that greatly affects commercial apple production. Applications of streptomycin may affect the endophytic bacterial communities, which are increasingly recognized for their valuable roles in plant hosts. Altering these communities may have implications for plant health and selection for streptomycin resistance in off-target bacteria. In a previous study, we found rapid selection of streptomycin-resistant epiphytes following season-long streptomycin use, and now sought to investigate the season-long impact of streptomycin applications (one, three, or nine postbloom applications) on endophytic bacterial communities. Studies were conducted in two orchards, and both culture-dependent and independent methods were used to assess the bacterial endophytic community. Streptomycin programs were compared with untreated trees and two programs approved for organic production. Treatments minimally affected abundance of culturable endophytic bacteria as determined by culture-dependent methods. Similarly, there were no significant differences in relative bacterial abundance or community composition between treatments as determined by 16S ribosomal RNA high-throughput sequencing (culture independent). There were greater differences between orchards than between treatments, suggesting a stronger influence of locality. Communities were dominated by the families Pseudomonadaceae, Enterobacteriaceae, Desulfovibrionaceae, Bacillaceae, and Burkholderiaceae, which are commonly described in other investigations of microbial communities of apple orchards. In addition, we found a high abundance of Amoebophiliaceae, a family dominated by arthropod parasites. Our results provide evidence that season-long applications of streptomycin in apple orchards have minimal impact on endophytic bacterial communities, which is in contrast to some reports on epiphytic communities.

Development of a Sensitive TaqMan qPCR Assay for Detection and Quantification of Venturia inaequalis in Apple Leaves and Fruit and in Air Samples.

A TaqMan quantitative PCR (qPCR) assay based on the translation elongation factor 1-α gene was developed for the quantification of Venturia inaequalis in leaves and fruits of Malus × domestica and in spore trap samples. The designed primers and hydrolysis probe amplified a specific 86-bp fragment for V. inaequalis. The specificity of the assay was tested using 35 strains of V. inaequalis and 20 different fungal species, including common pathogens of apple and other species of Venturia. The limit of detection was 20 fg, which is lower than a single genome of V. inaequalis. The selectivity of the assay was tested using DNA from three cultivars of Malus × domestica, and no influence on pathogen amplification was found. The assay was also validated for repeatability and reproducibility. With this assay, it was possible to detect and quantify V. inaequalis in four cultivars (Ambrosia, Florina, Golden Delicious, and Mondial Gala) in both symptomatic and asymptomatic leaves and in symptomatic Golden Delicious apple fruit stored for 2 months. Furthermore, the assay was successfully tested on spore trap samples originating from apple orchards. The quantification of the molecular assay when compared with the estimated number of V. inaequalis cells, using an optical microscope, showed a correlation coefficient of 0.8186. The developed technique could be used to detect V. inaequalis in asymptomatic samples without any cross-reaction with other fungal species. Furthermore, to improve the efficacy of disease management with a timely application of fungicides, this assay could be used for the analysis of spore trap samples by using an implemented extraction method.

ФУНКЦИОНАЛЬНАЯ АКТИВНОСТЬ ЛИСТОВОГО АППАРАТА ЯБЛОНИ ПРИ ВОЗДЕЙСТВИИ СТРЕССОРОВ ЛЕТНЕГО ПЕРИОДА

ФУНКЦИОНАЛЬНАЯ АКТИВНОСТЬ ЛИСТОВОГО АППАРАТА ЯБЛОНИ ПРИ ВОЗДЕЙСТВИИ СТРЕССОРОВ ЛЕТНЕГО ПЕРИОДА

Evaluation of the Physico-Chemical Properties of Soil and Apple Leaves (Malus Domestica) in Beni Mellal-Khenifra Region, Morocco

Evaluation of the Physico-Chemical Properties of Soil and Apple Leaves (Malus Domestica) in Beni Mellal-Khenifra Region, Morocco

Classification of Healthy and Rot Leaves of Apple Using Gradient Boosting and Support Vector Classifier

Conventional Techniques Such As Convolutional Neural Network (Cnn), Deep Neural Network Have Shown Its Own Footprints In The Field Of Image Classification With Promising Results. In The Past Decades, Classification Of Images Has Been Done With Varying Features Like Shape, Texture Etc. In This Paper, A Novel Approach Is Used To Classify The Leaf Images And Determine The Health And The Diseased Leaf. The Image Is Preprocessed By Extracting The Shape Feature And Classified The Leaves Of Apple As Healthy And Diseased (Rot Leaves) Using Two Novel Effective Approaches Gradient Boosting And Support Vector Classifier. We Have Collected 1813 Images Of Apple Leaves As Dataset And Out Of These, 70% Of The Data Is Used To Train And Remaining 30% Is Used To Test The Data. Our Algorithm Has Outperformed Other Traditional Techniques With Good Scale Of Accuracy(Gradient Boosting-87%, Support Vector Classifier-91%). Strong Comparison Of Both Gradient Boosting And Support Vector Is Made And There Is Dominant Show Off Of The Confusion Matrix. Classification Of Healthy And Diseased Leaf Well In Advance Gives Nice Warning To The Producer Thereby Decreasing The Rate Of Diseased.

An environment-friendly supramolecular solvent-based liquid–phase microextraction method for determination of aluminum in water and acid digested food samples prior to spectrophotometry

Aluminum (III) has high toxic impacts in some human pathologies like renal osteodystrophy, Parkinson's and Alzheimer's disease. So, it is very important to assess and determine the trace concentrations of Aluminum (III) in various water and acid digested food samples. The present work proposed a new green supramolecular solvent liquid–phase microextraction procedure has been sophisticated to preconcentrate and determine Aluminum (III) in various samples. The proposed method was based on the application of Undecanol/THF supramolecular solvent system and thymol blue as a chelating agent. Aluminum (III)-thymol blue complex was formed at pH 6.0, extracted into (Undecanol/THF) supramolecular solvent phase, centrifuged and spectrophotometrically measured at 550 nm. The influence of different analytical parameters was studied and optimized. The validation of the suggested preconcentration method was checked using certified reference materials. The calibration curve was linear in the range of 5.0–200 μg L−1. The developed method has preconcentration factor of 50 and detection limit was 1.20 μg L−1. The method precision was confirmed with relative standard deviation ≤1.80%. The accuracy of the new preconcentration procedure was checked by the analysis of the certified reference materials (SRM 1643e trace element in water and NIST SRM 1515 Apple Leaves), and successfully applied to determine Aluminum (III) in real samples with relative recovery values in the range of 95.0%–100% for the spiked samples. This study explores the effectiveness of thymol blue for the first time together with supramolecular solvent to develop green supramolecular solvent liquid–phase microextraction method to preconcentrate and separate of trace amount of Aluminum (III) in real samples.

Field Assessment of Macronutrients and Nitrogen in Apple Leaves Using a Chlorophyll Meter

Nutrient content assessment of plant tissues is widely performed by farmers to determine the appropriate amount of fertilization to use for their crops. A nondestructive leaf chlorophyll meter is one of the most commonly used devices for performing field assessments of the nutrient status of leaves. However, it is challenging to use a chlorophyll meter to assess the nutritional status of perennial plants, such as the apple (Malus ×domestica) tree, because of the difficulty estimating nitrogen (N) during the entire growing period. We compared the chlorophyll meter readings with leaf nutrient profiles collected from young ‘Arisoo’/M.9 apple trees throughout the growing period. A significant positive correlation between the chlorophyll meter readings and leaf N content was found from May to August during the midseason. Regression analysis indicated that the best sampling time for predicting the foliar N content of apple tress is from late June to late July. This result suggests that a reliable leaf N assessment can be performed in a rapid, nondestructive way in apple orchards.

Phosphomethylated Polyethyleneimine-immobilized Chelating Resin: Role of Phosphomethylation Rate on Solid-Phase Extraction of Trace Elements.

Chelating resins immobilizing phosphomethylated polyethyleneimine (PM-PEI) with different phosphomethylation (PM) rates were prepared by using different amounts of both phosphonic acid and paraformaldehyde in the phosphomethylation of PEI immobilized on a methacrylate resin as a base resin. The extraction of many elements improved with increasing PM rate; REEs, Be, Fe, Mo, Ti, and V were quantitatively extracted at pH 2. The elution of the elements tended to become difficult with increasing PM rate. When a PM-PEI resin with a PM rate of 0.26 was used, REEs and Be could be eluted using 0.2 mol L-1 EDTA solution adjusted to a pH of 7 and 3 mol L-1 nitric acid, respectively, although the elution of Fe, Mo, Ti, and V was insufficient. The PM-PEI resin could be reused at least 10 times to recover REEs and Be without the influence of any other elements. The PM-PEI resin could be applied to a recovery test using artificial seawater spiked with REEs, except for Sc, Tm, Yb, and Lu, and the separation of the REEs in NIST SRM 1515 Apple Leaves.

Exposure assessment of trace elements in fresh eggs from free-range and home-grown hens analysed by inductively coupled plasma optical emission spectrometry (ICP-OES)

A total of 21 metals (Na, K, Ca, Mg, V, Mn, Fe, Cu, Zn, Cr, Mo, Co, B, Ba, Li, Sr, Ni, Si, Al, Pb, Cd) have been analysed, using inductively coupled plasma atomic emission spectroscopy (ICP-OES), in a total of 288 eggs from free-range and home-grown hens in order to establish differences in metallic content according to the breeding system. Method accuracy was checked by the analysis of certified reference materials (SRM 1515 Apple Leaves, SRM 1548a Typical Diet and SRM 1567a Wheat Flour from NIST) and the recovery percentages were between 97.7–103%. The results obtained were in good agreement with 95% confidence limit with the certified concentrations, relative standard deviation (RSD) values were lower than 25%. Significant differences (p < 0.05) in the metal content between the two breeding systems have been demonstrated. The daily consumption of eggs from free-range hens (24.3 g/person/day for children, 31.2 g/person/day for adults) contributes to the intake of metals, such as Na (2.7% adults, 2.1% children), Fe (7.4% males, 3.7% females, 4.3% children), Zn (4.4% males, 5.9% females, 4.1% children) and Cu (9.6% adults, 8.3% children). Macroelements and trace elements contribution is lower in home-grown eggs and with higher amounts of toxic metals.

Multivariate Optimization of Conditions for Digestion of Wet Feeds for Dogs and Cats Using a Closed Digester Block and Multielement Determination by ICP-OES

A full 24 factorial design was applied to find the best combination of diluted reagents (HNO3 and H2O2), time, and temperature for the digestion of samples of wet feed for dogs and cats using a closed digestion block. The residual carbon concentration (RCC) was used as the response in the factorial design. All variables and their interactions significantly influenced the digestion of the feed samples, as indicated by the RCC. The conditions established for the digestion of 0.05 g (dry mass) wet feed samples were the addition of 3.0 mol/L HNO3 and 5.0% m/m H2O2 in a final volume of 10 mL, followed by heating in a closed digestion block at a temperature of 170°C for 120 min. Analyses were performed by inductively coupled plasma (ICP) optical emission spectrometry (OES). LOQs ranged from 0.2 μg/g (Mg and Sr) to 51 μg/g (P). Accuracy of the analytical method was confirmed through the analysis of the Standard Reference Materials Tomato Leaves (NIST 1573), Apple Leaves (NIST 1515), and Peach Leaves (NIST 1547). The agreement values achieved ranged from 80.2 ± 0.3% for Ba to 113.8 ± 7.1% for Zn (n = 3). Addition and recovery tests were carried out by adding the analytes to a feed sample at two concentration levels, and the recoveries were between 84 ± 6 and 114 ± 10% for macroelements (Ca, K, Mg, and P; n = 3) and between 88 ± 3 and 113 ± 7% for microelements and trace elements (B, Cu, Fe, Sr, and Zn; n = 3). The precision values achieved for the different elements, expressed as RSDs, were better than 7.3% (Zn; n = 3) except for Cu determination, that was 14.6% (n=3). The optimized analytical method was applied to 10 commercial samples of wet feed for cats and dogs, with the concentrations of Al, B, Ba, Ca, Cu, Fe, K, Mg, Mn, P, Sr, and Zn determined by ICP-OES.

Reliability of graphite furnace atomic absorption spectrometry as alternative method for trace analysis of arsenic in natural medicinal products

Purpose: To evaluate the comparative efficiency of graphite furnace atomic absorption spectrometry (GFAAS) and hydride generation atomic absorption spectrometry (HGAAS) for trace analysis of arsenic (As) in natural herbal products (NHPs). Method: Arsenic analysis in natural herbal products and standard reference material was conducted using atomic absorption spectrometry (AAS), namely, hydride generation ASSAAS (HGAAS) and graphite furnace (GFAAS). The samples were digested with HNO 3 –H 2 O 2 in a ratio of 4:1 using microwave-assisted acid digestion. The methods were validated with the aid of the standard reference material 1515 Apple Leaves (SRM) from NIST Results: Mean recovery of three different samples of NHPs, using HGAAS and GFAAS, ranged from 89.3 - 91.4 %, and 91.7 - 93.0 %, respectively. The difference between the two methods was insignificant. A ( P = 0.5), B ( P =0.4) and C ( P =0.88) Relative standard deviation (RSD) RSD, i.e., precision was 2.5 - 6.5 % and 2.3 - 6.7 % using HGAAS and GFAAS techniques, respectively. Recovery of arsenic in SRM was 98 and 102 % by GFAAS and HGAAS, respectively. Conclusion: GFAAS demonstrates acceptable levels of precision and accuracy. Both techniques possess comparable accuracy and repeatability. Thus, the two methods are recommended as an alternative approach for trace analysis of arsenic in natural herbal products. Keywords: Arsenic, Graphite furnace atomic absorption spectrometer (GFAAS), Hydride generation atomic absorption spectrometer (HGAAS), Natural herbal products

Direct analysis of elemental biodistribution in pea seedlings by LA-ICP-MS, EDX and confocal microscopy: Imaging and quantification

Qualitative and quantitative methods were developed for cadmium, lead, cooper and zinc mapping and quantification in root of pea Pisum sativum L. Plants were cultivated hydroponically in a Hoagland medium with the addition of 50μM of: CdCl2, Pb(NO3)2, CuSO4, or ZnSO4. After 48h, parts of roots were cut and analysed. LA-ICP-MS was used for in vivo quantitative imaging of the distribution of metals in thin sections of plant tissues. Calibration curve was obtained using standard addition method NIST SRM 1515 Apple Leaves spiked with standard and application of sulfur isotope as an internal standard. Energy Dispersive X-ray microanalysis Spectroscopy (EDX) was used in order to confirm results obtained by LA-ICP-MS and identify the exact localization of metals deposits in root tissue. In the electron-microscopic photographs we observed deposits of metals in the cell wall, cell membrane, vacuoles, cytoplasm and organelles, such as: mitochondria and peroxisomes. Formation and localization of O2− and H2O2 in cross-sections of root tips was confirmed by confocal microscopy. The presence of metals induced ROS (reactive oxygen species: O2−, H2O2) production in areas corresponding to patterns of metals accumulation.

Dyeing of Wool and Cotton Fabrics with Leaves of Apple (Malus Domestica) Tree

ABSTRACTIn this study, apple leaves were used to dye wool and cotton fabrics. Effects of mordant type and dyeing technique on color yield and fastness properties were investigated. The selected dyed fibre sample surfaces were observed using a scanning electron microscope (SEM). Color strength (K/S) values of the dyed fabrics were between 0.53 and 20.56. Washing and rubbing fastness results of the dyed fabrics were moderate/high. The SEM images of the naturally dyed fabrics demonstrated a smooth surface profile. We have concluded that apple leaf is suitable for the natural dyeing of wool fabrics.

Proteome Analysis of Pathogen-Responsive Proteins from Apple Leaves Induced by the Alternaria Blotch Alternaria alternata.

Understanding the defence mechanisms used by apple leaves against Alternaria alternate pathogen infection is important for breeding purposes. To investigate the ultrastructural differences between leaf tissues of susceptible and resistant seedlings, in vitro inoculation assays and transmission electron microscopy (TEM) analysis were conducted with two different inoculation assays. The results indicated that the resistant leaves may have certain antifungal activity against A. alternate that is lacking in susceptible leaves. To elucidate the two different host responses to A. alternate infection in apples, the proteomes of susceptible and resistant apple leaves that had or had not been infected with pathogen were characterised using two-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption/ionisation time-of-flight tandem mass spectrometry (MALDI-TOF-TOF MS). MS identified 43 differentially expressed proteins in two different inoculation assays. The known proteins were categorised into 5 classes, among these proteins, some pathogenesis-related (PR) proteins, such as beta-1,3-glucanase, ascorbate peroxidase (APX), glutathione peroxidase (GPX) and mal d1, were identified in susceptible and resistant hosts and were associated with disease resistance of the apple host. In addition, the different levels of mal d1 in susceptible and resistant hosts may contribute to the outstanding anti-disease properties of resistant leaves against A. alternate. Taken together, the resistance mechanisms of the apple host against A. alternate may be a result of the PR proteins and other defence-related proteins. Given the complexity of the biology involved in the interaction between apple leaves and the A. alternate pathogen, further investigation will yield more valuable insights into the molecular mechanisms of suppression of the A. alternate pathogen. Overall, we outline several novel insights into the response of apple leaves to pathogen attacks. These findings increase our knowledge of pathogen resistance mechanisms, and the data will also promote further investigation into the regulation of the expression of these target proteins.

Effects of Nitrate:Ammonium Ratios on Vegetative Growth and Mineral Element Composition in Leaves of Apple

Evaluations of vegetative growth and leaf concentrations of nitrogen (N), potassium (K), calcium (Ca), magnesium (Mg), and iron (Fe) were made of apple (Malus domestica Borkh. cvs. Granny Smith, Gala, and Golab) grown with five treatments of NO3−:NH4+ ratios in pot culture. The concentrations of NO3−:NH4+ ratios were 2.5:0.1, 6:0.3, 6:0.5, 6:0.7, and 6: 1 meq L−1. Regression analysis showed that growth parameters of main stems and branches were not affected by increases of NH4+ in the ratios. Granny Smith, Gala, and Golab differed in some of these parameters. Concentrations of N and Fe increased as NH4+ increased, whereas K and Ca decreased and Mg was not affected significantly. Generally, the treatment of 2.5:0.1 produced leaves with lower N but higher K, Ca, and Mg concentrations than the other treatments. This research showed that vegetative growth was not affected by NH4+ concentration whereas elemental composition was affected.