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Near-infrared spectroscopy (NIRS) can be a faster and more economical alternative to traditional methods for screening varietal mixtures of nursery plants during the propagation process to ensure varietal purity and to avoid errors in the dispatch batches. The global objective of this work was to develop and optimize a NIR spectral collection method for construction of robust multivariate discrimination models. Three different varieties of Prunus dulcis (Avijor , Guara , and Pentacebas) of agricultural interest were used for this study. Sources of variation were investigated, including the position of the leaves on the trees, differences among trees of the same variety, and differences at the varietal level. Three types of processed samples were investigated. Fresh leaves, dried leaves, and dried leaves in powder form were included in each analysis. A study of spectral pre-treatment methods was also performed, and multivariate methods were applied to analyze the influence of different factors on classification. These included principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and ANOVA simultaneous component analysis (ASCA). The results indicated that variety was the most important factor for classification. The spectral pre-treatment that provided the best results was a combination of standard normal variate (SNV), Savitzky-Golay first derivative, and mean-centering methods. With regard to the type of processed sample, the highest percentages of correct classifications were obtained with fresh and dried powdered leaves at both the training set and test set validation levels. This study represents the first step towards the consolidation of NIRS as a method to identify Prunus dulcis varieties. Image 1 • NIRS was used for discriminating between three Prunus dulcis varieties. • Several spectral pre-treatment strategies were investigated. • A combination of SNV, SG first derivative, and mean centering methods was optimal. • Tree variety and leaf age were the most important classification factors for PLS-DA. • NIRS is a rapid and economical method for nursery plant classification. [ABSTRACT FROM AUTHOR]

Highlights • Improvement in the cultivation of the species of Justicia to produce herbal medicines. • First report on morphological and anatomical changes in the leaves and stems of the three species of Justicia caused by the cultivation. • Histochemical localization of compounds and verification of the antioxidant activity of these substances. • Report on the chemical composition of Justicia brandegeeana. • Presence of coumarin in Justicia gendarussa. Abstract Morphoanatomical and chemical changes can occur because of biotic and abiotic factors, naturally present in the environment. These changes can result in modifications in the concentrations of secondary metabolites of medicinal species, an essential aspect to produce herbal medicines. Justicia species are used for analgesic and anti-inflammatory purposes and widely used in social programs in the Northeast of Brazil. Therefore, this study aimed to evaluate how different growth conditions (greenhouse and field) affect morphoanatomical features, chemical composition and AA of the aerial organs of three economically important species of Justicia (J. brandegeeana , J. gendarussa , and J. pectoralis). The results of morphological evaluations indicate that plants grown in the field developed better than those grown in the greenhouse, which underwent etiolation. Plants grown in the greenhouse had a greater leaf area and reduced mesophyll thickness. In contrast, plants that were grown in the field had greater cuticle and mesophyll thickness, as well as increased collenchyma cell wall thickness of stems and petioles. Plants grown in the field also had a higher stomatal density than plants grown in the greenhouse. Mass spectrometric data revealed a higher overall concentration of phenols and flavonoids, as well as higher AA, in the extracts of the plants grown in the field. Thus, the different growth conditions resulted in anatomical alterations, and changes in the concentrations of some chemical components. The results help to improve the cultivation of these species, as these changes imply in the quality of the final product and the treatment. [ABSTRACT FROM AUTHOR]

The feasability of using reclaimed water (RW) to irrigate nectarines in Apulia, to reduce sea-water intrusion, has been studied in an orchard for 3-years. While the primary water quality parameters were significantly higher in RW than in fresh water (FW), concentrations were below the phytotoxic threshold that would cause significant yield losses under good management practices. In general, fruit quality parameters of nectarines, total phenolics and antioxidant compounds were higher in fruits irrigated with RW than FW, because of higher nutrients and salinity in the RW treatment. Lower firmness values were observed in RW-treated fruits implying early ripening. Overall, no yield differences were found between FW and RW-treated trees during the three year study. However, the RW treatment significanly reduced the number of fruits but this reduction was compensated by a larger individual fruit weight. While this 3yr-study has demonstrated that reclaimed water is a feasable alternative to freshwater in areas in southern Italy, further long-term studies are still needed to show the beneficial effects of RW on nectarine fruit yield and quality. [ABSTRACT FROM AUTHOR]

Plant-Nitrogen is a vital element that significantly influences plant growth, fruit quality, and yield. However, excessive Nitrogen (N) fertilizer application can have adverse effects on both plant health and environment. Traditional methods of plant-N analysis face numerous challenges like time-consuming procedures, hazardous chemicals, low precision, and limited throughput, hindering efficient and accurate analysis in laboratories. In recent years, Near-Infrared Spectroscopy (NIRS) has emerged as an innovative and rapid method for plant-N analysis, offering non-destructive, cost-effective, and real-time measurements with high accuracy and throughput. This research aimed to explore the potential of utilizing miniaturized handheld Near-Infrared (NIR) sensors in conjunction with machine learning (ML) and chemometrics to assess the N status of tomato plants leaves in the field. Through this study, A comprehensive analysis involving 18 models utilizing different regression and spectral preprocessing methods was conducted. The findings indicate that combining the first- or second-order SG derivatives with the MSC is the optimal spectral data preprocessing method, and that incorporating wavelengths selection techniques, such as GA-PLS and GA-SVM, improves the predictive accuracy of the models by reducing the number of wavelengths considered. The best model's performance was assessed using R2, RMSE, and RPD, yielding values of 81.0–82.8, 7.4–7.8, and 2.3–2.4, respectively. Overall, this study demonstrates that combining NIRS with ML and chemometrics enables effective evaluation of plant-N status using leaves total N content as a proxy variable and emphasizes the significance of integrating spectral preprocessing, modeling, and wavelengths selection techniques to enhance data quality and mitigate the influence of environmental factors that may impact the accuracy of NIRS-based evaluations. • Rapid and efficient method for assessing plant nutritional status was introduced. • Machine learning and chemometrics have unleashed the power of NIR spectroscopy in the analysis of nutrients in fresh leaves. • Leaf diagnosis was a good proxy for evaluating plants nutritional status. • Leaf tissue analysis offered crucial information about the plant status. • Meta-Modeling made it possible to develop powerful calibrations. [ABSTRACT FROM AUTHOR]

In the present paper, an expert system for automatic recognition of different plant species through their leaf images is investigated by employing the ant colony optimization (ACO) as a feature decision-making algorithm. The ACO algorithm is employed to investigate inside the feature search space in order to obtain the best discriminant features for the recognition of individual species. In order to establish a feature search space, a set of feasible characteristics such as shape, morphology, texture and color are extracted from the leaf images. The selected features are used by support vector machine (SVM) to classify the species. The efficiency of the system was tested on around 2050 leaf images collected from two different plant databases, FCA and Flavia. The results of the study achieved an average accuracy of 95.53% from the ACO-based approach, confirming the potentials of using the proposed system for an automatic classification of various plant species. [ABSTRACT FROM AUTHOR]

The aim of the present investigation was to evaluate the effects of annual application of three rates of compost on nutrient concentration and accumulation in tree organs, after 11 years of continuous application of a municipal solid waste (MSW) compost in a commercial nectarine orchard. Trees were subjected, since their plantation (2001), to the following MSW compost rate: 0, 5 and 10 t dw ha −1 yr −1 , split in May (60%) and September (40%). In 2011/2012 biomass of pruned wood, thinned fruits, fruit pulp and stones at harvest, and abscised leaves were weighted and analyzed for macro (N, P, K, Ca, Mg) and micro (Fe, Mn, Cu, and Zn) nutrients concentration. In addition, leaves and fruit pulp at harvest were analyzed for heavy metal (Cd, Cr, Hg and Pb) concentration. Plant part biomass (with the exception of thinned fruits) was linearly related to compost application rate. The highest rate of compost increased N and decreased Ca and Mg concentration in leaves sampled in summer, whereas no differences among treatments were observed for the other nutrients. At the end of the season leaf N, K and Zn were remobilized to storage plant part, while P, Ca, Mg, Fe and Mn reached the highest values in abscised leaves. Nitrogen, K, Mg, Cu, Mn and Zn accumulation in the plant part analyzed increased as a consequence of the application of compost at 10 t ha −1 when compared with compost at 5 t ha −1 and control. Phosphorous accumulation was increased by compost at the highest rate compared with control; no differences were observed for Ca and Fe accumulation. Nitrogen and P were mainly accumulated in fruit, abscised leaves and pruned wood; K was allocated mainly into fruits, while Ca and Mg were found highest in abscised leaves. Concentration of heavy metals in leaves and fruits were not affected by treatments. [ABSTRACT FROM AUTHOR]

Abstract: Background: Cissampelos sympodialis Eichl. (Menispermaceae) is used in folk medicine for the treatment of respiratory conditions such as bronchitis and asthma. The aqueous fraction of the hydroalcoholic extract of its leaves has shown immunomodulatory, bronchodilator and anti-inflammatory activities. However, there is no data available on the pharmacognostic quality control of its leaves. Objective: The aim of the present study was to characterize the drug material obtained from the leaves of C. sympodialis, with the determination of WHO recommended assays, histochemistry of leaf sections and HPLC determination of its main bioactive alkaloid, warifteine. Materials and methods: Three batches of leaves were collected and histochemical and phytochemical analyses were performed to screen for alkaloids, phenolics, terpenoids, lipids, polysacharides and saponins. Pharmacopeial assays for the plant material were also conducted and the bisbenzylisoquinoline alkaloid warifteine was quantified by HPLC analysis. Results: The histochemistry of leaf sections from C. sympodialis revealed the presence of lipids, polysaccharides, phenolic compounds and alkaloids, mainly as part of idioblast secretions. These results were confirmed by general phytochemical screening reactions conducted with the leaf hydroalcoholic extract (presence of alkaloids, steroids, tannins, flavonoids and saponins). General pharmacopeial tests conducted with the leaves were within accepted standards. The warifteine content was similar for the three batches tested (0.004–0.006%). Conclusion: The physicochemical parameters and the morphological results presented in this paper can be used as basis for the preparation of a monograph on C. sympodialis leaves. [Copyright &y& Elsevier]

Highlights: [•] This paper studied the relationships between nutrient concentrations of Satsuma mandarin flowers and leaves. [•] It was put forward that floral analysis could be an earlier nutrient diagnosis method for citrus reticulata. [•] The critical values for Satsuma mandarin floral diagnosis were calculated. [ABSTRACT FROM AUTHOR]

Abstract: Municipal solid waste (MSW) compost is an ‘organic’ amendment and can influence nutrient mineralization and subsequent plant growth. A three-year field experiment evaluated the effects of MSW compost and fertilizer on soil fertility and elemental analysis of squash (Cucurbita maxima cv. Buttercup) grown in a Pugwash sandy loam soil in Nova Scotia, Canada. Three rates of compost (MSW1, MSW2, and MSW3), one rate of chemical fertilizer (NPK), and one mixture of 1/2 MSW1 compost and 1/2 NPK fertilizer (MIXTURE) were applied each year to plots in a three crop rotation. The experimental design was a randomized complete block (RCB) design with four replications. The NPK treatment produced the highest yields in 1996 and numerically the highest yields in 1997 and 1998. In the last year of the study, significant differences were found between soil fertility treatments for K, S, Cu, Zn, B, and Na in Mehlich 3 extracts at the 0–15cm soil depth; however, only leaf Mn, Cd, and Cr were found to be influenced by the treatments. In two of the three years, the highest rates of MSW compost produced the highest levels of leaf S, Cu, and Zn. The study found that MSW compost was a good source of nutrients, however, the relatively low availability of mineralizable nutrients means that high rates of compost and/or supplementary N-P-K in the form of inorganic fertilizer may have to be added in order to enhance nutrient availability to winter squash. [Copyright &y& Elsevier]

Abstract: Correlations between macro and micronutrient concentration of olive leaves and those obtained in floral buds at five development stages, were studied in order to evaluate the utility of floral analysis for the diagnosis of the nutritional status of olive orchards. Olive leaves from ‘Arbequina’, ‘Frantoio’, ‘Hojiblanca’, ‘Bella de España’ and ‘Picual’ cultivars were taken during July of 2002 and 2003. Samples of floral buds were collected at five development stages: closed bud (E), petal fall (G), G+15 days, G+30 days and pit hardening (H). Results showed a lack of signification of the correlation coefficients between leaf and floral analysis for N, P, K, Ca, Mg, B, Zn, Mn, Fe, Cu and Na in both years of the experiment. The few significant correlations obtained were not repeated in both years. Therefore, the results indicate that floral bud mineral analyses cannot substitute the foliar diagnosis to establish the nutritional status of the olive orchards. [Copyright &y& Elsevier]

Abstract: Mature ‘on’ and ‘off’ ‘Manzanillo’ olives trees with three healthy branches of 10–12cm in diameter were selected to determine changes in nitrogen levels in the bearing shoots after foliar application of urea. Each selected branch of each tree received one of the following treatments: (i) control without urea application; (ii) foliar application of urea to all the current-season leaves; and (iii) foliar application of urea to all the one-year-old leaves. Urea was applied in May, four days after full bloom in the ‘on’ year trees. Each treated leaf was immersed in a test tube containing a 4% urea solution and 0.1% Tween 20 for 5s. Bearing shoots, composed of both one-year stems and leaves and current-season stems and leaves, were collected at intervals from the beginning of the experiment until 64 days after urea application. Nitrogen was determined in stems and leaves from each part of the bearing shoot, and in fruits during the ‘on’ year. Nitrogen uptake from the leaves was rapidly mobilized from the older to the current-season leaves of the bearing shoot, and thereafter to other storage organs of the tree or to the fruit, which is the largest nitrogen sink in the bearing shoot. No translocation of nitrogen from the current-season leaves to older leaves was observed. The rapid translocation of nitrogen from the younger leaves to other storage organs of the tree could explain the insensitivity of leaf analysis to detect excess nitrogen, since mature leaves from current-season shoots must be sampled to determine the nutritional status of the tree. The failure of leaf analysis to detect excess nitrogen may be a cause of nitrogen over-fertilization in olive orchards. [Copyright &y& Elsevier]