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A mixed mode dispersive solid phase extraction was introduced for the extraction of multi – class pesticides in mango samples. In the following, the extracted analytes were more concentrated by dispersive liquid – liquid microextraction. By the use of advantages of both sample preparation methods, the proposed analytical method was sensitive with high enrichment factors and less matrix effect. Some biopolymers including chitosan, agarose, and cellulose were employed as the sorbent in dispersive solid phase extraction due to their compatibility with the trends of green chemistry. The best composition of the biopolymers was obtained by a simplex centroid design and the data illustrated that the weight ratio of 4:1:1 (w/w/w) was the best composition of chitosan: agarose: cellulose for extraction of the pesticides, respectively. After optimisation of effective factors, the figures of merit were calculated. The validation data showed that the limit of detection were from 0.13 to 0.32 ng g−1. All of the calibration curves were linear in the range of 1.07–1000 ng g−1. The introduced method was successfully utilised for the extraction of the pesticides in mango samples. Fortunately, all studied samples were free of the analytes. [ABSTRACT FROM AUTHOR]

Aiming at the problems of long motion path planning time and low picking efficiency of picking robots in unstructured orchard environments, a heuristic dynamic Rapidly-exploring Random Tree Connect motion planning algorithm (HDRRT-Connect) for picking robots for fast mango harvesting path planning was proposed in this study. The algorithm was obtained by introducing adaptive target gravitation strategy and heuristic dynamic step strategy based on RRT-Connect algorithm. It adjusts the step-size according to the information of the orchard environment as well as the path searching situation, so as to avoid falling into the local optimum of the path. The prototype based on the algorithm was used to carry out picking experiments in the natural orchard environment. The prototype picking test under the natural environment of the orchard is carried out, and the test results showed that the average path cost of the HDRRT-Connect algorithm was 95.7739, the average planning time was 0.448 s, and the success rate was 90%. Compared with the RRT, RRT-Connect and Probabilistic Roadmaps (PRM) algorithms, the HDRRT-Connect planning speed was improved by 95%, 24% and 59%, respectively, and the path cost was reduced by 35%, 13% and 18%, respectively. The results of the experiment verified the feasibility and efficiency of the improved algorithm. The HDRRT-Connect algorithm proposed in this study could effectively shorten the planning time, reduce the search path cost and improve the planning success rate. The research provides technical support for the fast-harvesting operation of mango picking robot. • Built a mango picking robot platform. • Aims to obtain a collision-free path for the mango picking robot. • Adaptive target gravity and heuristic dynamic stepping strategies. • Proposed robotic arm path planning algorithm for unstructured orchards. • Harvesting trials in laboratory and field environments. [ABSTRACT FROM AUTHOR]

Pakistan is one of the biggest mango producing country in the world. Post-harvest losses of mango occur due to lack of storage facilities. Mango can be converted into concentrate to utilize it for longer period. In the current study, the physicochemical profile and storage stability of mango concentrate was investigated to evidence the opportunity of preservation method. Three different concentrations (0.1%, 0.2%, and 0.5%) of citric acid, sodium benzoate and potassium sorbate were applied. All chemical preservatives significantly (p ˂ 0.05) increased viscosity, total soluble solids (TS), reducing sugar (RS), non-reducing sugar (NRS), total soluble solids (TSS), and titratable acidity (TA), while the moisture content, pH, DPPH antioxidant activity, TPC (total phenolic content), TFC (total flavonoid content) and the level of texture acceptance decreased during the storage. The moisture content was decreased from 43.4% to 34.9% during storage. Phytochemical analysis showed that mango concentrate is a potential source of antioxidant compounds and has higher DPPH radical scavenging activity. Regarding preservation solution, it is suggested that sodium benzoate and citric acid might be utilized for industrial applications. [ABSTRACT FROM AUTHOR]

Summary: The quality of processed products can be adversely affected by uncontrollable batches of mangoes, which exhibit heterogeneous characteristics. This study aimed to establish predictive models for sugar and organic acid contents (dependent variables) in processed products using the initial compositions of fresh mangoes. Three mango cultivars (cv. 'Kent', cv. 'Keo Romeat', and cv. 'Keo Chen') were classified as low‐density and high‐density groups. Each group of mangoes at the green‐mature, mid‐ripe, and ripe stages was processed into pasteurised purees, dried slices, and mango chips. Prediction models were established using a mix of simple linear regression (SLR) based on the initial content and Analysis of Variance (ANOVA) to identify the impact of qualitative variables (ripening stage, cultivar‐density, and processing technique). In processed mangoes, 13% sucrose content was estimated to accumulate with the three qualitative variables, whereas glucose and fructose contents decreased from their initial levels by 10% and 7%, respectively. Processing techniques can predict the ratio of sugars/acids (S/A) in processed products, regardless of the ripening stage or cultivar‐density. Similar to S/A, citric acid and malic acid contents in mango products were significantly increased by processing techniques. The initial content and processes were insufficient to predict the final contents of the same parameters in processed mangoes; therefore, some models need to include the effects of ripening stage and cultivar‐density to improve the prediction. These relevant explanatory variables contributed significantly to the development of the models, resulting the accuracy of predictive models with normalised root mean square errors (NRMSEs) lower than 10%, except for malic acid (14.04%). In conclusion, it is feasible to estimate the sugar and acidity levels in processed mangoes, offering promising possibilities for ensuring consistent quality of mango‐based products. [ABSTRACT FROM AUTHOR]

A study of the energy potential from agro-industrial waste of Mangifera indica L. in the city of Zamora, Michoacán is presented, considering its use through solid biofuels. This research is composed of three stages: (a) the qualitative and quantitative diagnosis of the waste disposal of M. indica, spatiotemporally (b) the physicochemical characterization of the waste collected from 14 processing companies using characterization techniques, as well as proximal analysis of the moisture content, ash, volatiles, fixed carbon, and calorific value, and (c) estimation of the energy potential to spatially and temporally define the final energy disposition and possible use of the analyzed waste. The results show the ash content of mango residues below 3.5%, while the volatile material was 82.9%, the fixed carbon content was below 17%, and the polymeric compounds showed 27.24% cellulose, 10.46% for hemicellulose, and for lignin 5.78%. The presence of carbon was also identified in the order of 44.61%, hydrogen in 6.53%, oxygen in 48.11%, nitrogen of 0.74%, and the sulfur recorded was below the range of 0.01%. The calorific value was estimated from 17.5 to 19.28 MJ/kg; the available energy potential on the order of 0.5 TJ/day for 4 months. This proposal not only shows a case study of the bioenergy potential available, but it can also encourage addressing future research related to the use and valuation of agro-industrial waste, which, like in the Zamora region, there are many more in Mexico, and they are so diverse and productive that the energy potential is relevant. [ABSTRACT FROM AUTHOR]

Preharvest sun-exposure can improve the tolerance of fruit during postharvest handling conditions and thus we examined the postharvest responses of mangos. Sun-exposed and shaded fruit of 'Keitt' and 'Reynal' mango were harvested and assessed for external and internal damage following postharvest hot water (HW 55°C/50min) and hot air (HA 47°C/20min; 49°C/90min) treatments used for fruit fly disinfestation. Heat shock proteins and antioxidant systems were examined as possible biochemical strategies for stress protection of fruit tissues. With maximum air temperatures <37°C, fruit exposed to direct sunlight reached temperatures up to 47°C. Following HW, sun-exposed 'Reynal' fruit had less external damage than shaded fruit, with damage mainly on the exposed surfaces. In contrast, sun-exposed and shaded 'Keitt' fruit had similar levels of damage following HW. For both cultivars, HA treatments of either sun-exposed or shaded fruit did not cause any significant external damage, but internal damage was observed. Both cultivars exhibited biochemical stress responses. Hsp17.4 in the flesh of sun-exposed 'Reynal' and 'Keitt' fruit were 2 and 6 times higher than in shaded fruit, respectively. Total polyphenols and anthocyanins were higher in tissues of sun-exposed than shaded fruit. Results are discussed in terms of the different biochemical defence strategies among these cultivars. [ABSTRACT FROM AUTHOR]

Despite considerable research globally on postharvest diseases of mango, virtually no work has been done to determine the occurrence of these diseases and their causal agents in Fiji. This study is the first major field and market survey of postharvest diseases of mango in Fiji. For the field survey, fruits from five local mango cultivars were harvested at each of five locations. Fruits from five imported cultivars were also harvested from one location in Nadi. For the market survey, vendors were selected at five municipal markets for fruit collection, along with ten roadside stalls. For field and market surveys, fruits were incubated at 23°C and assessed for postharvest disease (incidence and severity of body rots and stem end rots) when ripe. Isolations were made from disease lesions and fungal cultures were identified using multilocus sequence typing. High incidences of body and stem end rots were recorded across all surveys. In the field survey of local cultivars, 'Salusalu' fruits were found to have the lowest severity of body rot and stem end rot on average, while for imported cultivars, 'Nam Doc Mai' had the lowest average severity of these diseases. The market survey showed that 'Salusalu' had a lower incidence of anthracnose on the body of fruit compared to all other cultivars, although it did have a surprisingly high incidence of stem end rot at some localities. Fungal isolates from anthracnose lesions in the field and market surveys were identified as Colletotrichum asianum, C. simmondsii and C. fructicola. C. asianum was the predominant species associated with anthracnose symptoms, accounting for 97% of isolations. Lasiodiplodia theobromae and Neofusicoccum parvum were the predominant species found in association with mango stem end rot symptoms. Other species isolated from mango stem end rot in lesser numbers included L. brasiliensis, N. umdonicola and N. kwambonambiense. All of these fungi represent new reports for Fiji. [ABSTRACT FROM AUTHOR]

This study examines the impact of both natural and ethylene-induced ripening methods on the aroma and taste of popular mango cultivars using Electronic Nose (E-nose) and Electronic Tongue (E-tongue). Five Indian mango varieties Badami, Banganapalli, Malgoa, Totapuri, and Mallika were selected for this study. Physicochemical parameters showed a decrease in acidity during ripening, accompanied by increase in pH and total soluble solids (TSS). Color changes from greenish to reddish-yellow were indicated by a reduction in L* values and an increase in both a* and b* values. E-tongue data revealed a reduction in sourness, corresponding with measured acidity. Principal component analysis (PCA) accounted for over 90% of the variance in taste and aroma across different ripening stages and varieties. Major aromatic compounds identified were limonene, β-ocimene, myrcene, β-pinene, β-caryophyllene, methyl acetate, ethyl acetate, ethyl butanoate, and γ-terpinene. Variable Importance in Projection (VIP) scores highlighted metabolic differences among ripening stages and mango varieties. Cross-validation tests confirmed significant differences in the composition and intensity of aroma compounds during ripening. Partial least squares discriminant analysis (PLS-DA) demonstrated good fitness (R² > 0.95) of model in analysing aroma compounds. Ethylene-induced ripening accelerated the production of aromatic compounds but resulted in flavor loss during storage. Natural ripening was identified as the optimal method for preserving the aroma and taste of mangoes. [ABSTRACT FROM AUTHOR]

The effect of salt stress was evaluated on putative mutant seedlings of three polyembryonic mango genotypes viz., Bappakkai, Nekkare, and Kurukkan. Imposition of salinity stress resulted in a decrease in chlorophyll content, relative water content, and gas exchange parameters while enhancing the levels of stress markers like Na+/K+ ratio, total phenols, and proline. In total, thirteen phenolic acid compounds were identified including eight hydroxybenzoic acids and five hydroxycinnamic acids wherein hydroxybenzoic acid (majorly gallic acid) comprised more than 99% of total phenolic acids. In all the three genotypes, the concentration of protocatechuic acid, 2, 4-Dihydroxy benzoic acid, gallic acid, chlorogenic acid, and t-cinnamic acid increased with increasing level of salt stress indicating their potential role in mango salt tolerance. Bappakkai recorded higher K+, highest fold increase in proline content (+ 7.27 fold), highest percent increase in chlorogenic acid (+ 510%), protocatechuic acid (+ 750%), and ferulic acid along with lower Na+/K+ ratio and lower reduction in the levels of caffeic and sinapic acid at higher level of salt stress suggesting that putative mutants of Bappakkai were better at tolerating salt stress as compared to the other two genotypes. Exogenous application of ferulic acid (FA) to Nekkare putative mutants increased the activity of enzymatic antioxidants, superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX). Further, quantitative real-time PCR analysis also revealed higher expression levels of SOD, CAT, and APX in FA-treated Nekkare mutants under salinity stress. The results of this study besides identifying distinct phenolic acid signatures in response to stresses like gamma irradiation and salinity, also confirm the potential of physical mutagenesis in breeding salt-tolerant rootstocks in mango. [ABSTRACT FROM AUTHOR]

Sapota fruit tree biomass cannot be estimated using general forest tree allometric equations involving measurement of diameter at breast height (DBH) as grafted sapota tree branches below this height. Therefore grafted sapota trees of commercial orchards require an independent allometric equation for nondestructive estimation of tree biomass. Sapota allometric equations were hence developed with a destructive sampling of grafted sapota trees using parameters other than DBH and compared with other equations developed for grafted mangoes. The selected allometric parameters were significantly related to the age of the trees. The root-to-shoot ratio also differed from those reported for forest trees. The biomass expansion factor by and large attained stability beyond 16 years of tree age. The equations so developed generally fitted the data well, and in most cases, more than 50% of the observed variation in biomass was explained by primary branch girth x number of primary branches. There was a good agreement between the observed and the predicted biomass using both multiple linear regression and power model equations. Further, our purpose was to see if the grafted mango tree equation can predict sapota tree biomass. The results of this study confirmed that the mango equation equally predicts sapota tree biomass and hence the mango tree allometric equation can also be used for estimating sapota tree biomass efficiently. [ABSTRACT FROM AUTHOR]

Lupeol, a naturally occurring lupane-type pentacyclic triterpenoid, is widely distributed in various edible vegetables, fruits, and medicinal plants. Notably, it is found in high concentrations in plants like Tamarindus indica , Allanblackia monticola , and Emblica officinalis , among others. Quantitative studies have highlighted its presence in Elm bark, Olive fruit, Aloe leaf, Ginseng oil, Mango pulp, and Japanese Pear bark. This compound is synthesized from squalene through the mevalonate pathway and can also be synthetically produced in the lab, addressing challenges in natural product synthesis. Over the past four decades, extensive research has demonstrated lupeol's multifaceted pharmacological properties, including anti-inflammatory, antioxidant, anticancer, and antibacterial effects. Despite its significant therapeutic potential, clinical applications of lupeol have been limited by its poor water solubility and bioavailability. Recent advancements have focused on nano-based delivery systems to enhance its bioavailability, and the development of various lupeol derivatives has further amplified its bioactivity. This review provides a comprehensive overview of the latest advancements in understanding the pharmacological benefits of lupeol. It also discusses innovative strategies to improve its bioavailability, thereby enhancing its clinical efficacy. The aim is to consolidate current knowledge and stimulate further research into the therapeutic potential of lupeol and its derivatives. [ABSTRACT FROM AUTHOR]

ABSTRACT To control mango postharvest deterioration, an edible coating based on pectin, glycerol, and oregano essential oil (OEO) was developed using a three‐step process involving optimization, validation, and comparison with a commercial fungicide. An extreme vertices mixture design approach was initially used to optimize the pectin, glycerol, and OEO concentrations in the coating formulation. We evaluated the impact of the coating components on the respiration rate, quality parameters, and anthracnose disease of mangoes. The optimal coating composition was 3.91% (w/v) pectin, 0.57% (w/v) glycerol, and 0.52% (w/v) OEO, with a desirability value of 0.8998. Model validation demonstrated that the measured values for all parameters fit the prediction interval of 95%, and the relative error varied between 0.88% and 12.28%. Validation experiments of the optimal coating compared to untreated mango and mango treated with a commercial fungicide showed that the optimal coating delayed ripening and effectively controlled the incidence of anthracnose for 18 days at 14°C and 85% relative humidity. [ABSTRACT FROM AUTHOR]

The document outlines the EPPO Standard PM 3/96 (1) on official controls of passenger luggage at airport points of entry, providing guidance to National Plant Protection Organizations on conducting checks for plants or plant products in passenger luggage. It emphasizes the importance of awareness campaigns to educate travelers on plant health regulations and outlines procedures for inspections, sampling, and identifying pest symptoms in various types of plant products. Non-compliant items may be seized and destroyed if they do not meet regulations, with a focus on preventing the spread of infections through proper hygiene measures. Inspections are conducted according to regulations, and non-compliant goods are safely destroyed to prevent the escape of pests. [Extracted from the article]

Manual measurement on mango fruit dimensions is often confined to the time inefficiency and low accuracy. Specifically, the human judgment and simplified definitions of fruit shape can impact the morphology classification and subsequent packaging. Consequently, it is highly required for the dedicated platform to determine the morphological indicators for the accurate identification of mango fruit shapes. Such a platform can be expected to streamline the sizing process for the shape identification. Advanced techniques, such as three-dimensional (3D) scanning, have been successfully applied into the morphological analysis of other fruit types, demonstrating their potential to the high accuracy. Additionally, machine learning can also be integrated to significantly improve the classification of fruit shapes, in order to effectively mitigate the errors associated with human assessment. In this study, a 3D scanning platform was implemented to rapidly capture the geometric data of mango fruits. An accurate 3D model was constructed to facilitate the measurement on the morphological indices and shape identification. 75 mango varieties were selected with three replicates for each variety. 10 quantitative parameters were then measured, including volume, longitudinal and transverse diameters, as well as fruit shape indices using 3D scanning. A comparison was then made on the scanning and manual measurement. The results indicated that the precision of scanning was surpassed the manual ones, indicating the superiority of the former. Subsequently, eigenvalue, principal component, correlation and cluster analysis were conducted to categorize the mango varieties, according to their distinct fruit shapes. There were the rich genetic diversity and variability in the mango germplasm resources. Notably, the fruit shape index was taken as the critical indicators, together with longitudinal and transverse diameter. The comprehensive evaluation of fruit morphology was performed for the subsequent application of machine learning. The input parameters were then optimized to predict the modeling. A back-propagation (BP) neural network model was developed to classify the fruit shape, according to the SPSSPRO online data analysis platform. The architecture of model consisted of 100 hidden layers, with a learning rate set at 0.1 and a total of 1000 iterations. Furthermore, an success rate was achieved in the 94.12% accuracy, when testing on 68 samples and training with 157 samples. Moreover, the training set exhibited a precision and recall rate of 0.941, with a remarkably rapid recognition time of only 0.451 s. In conclusion, 3D point cloud data was utilized to provide the rapid, precise, and lossless morphological information for mango fruits. 3D point cloud maps were generated to further enhance the overall accuracy, such as fruit color information. Compared with the conventional, this approach can offer numerous advantages: rapid sampling, high accuracy, reduced susceptibility to external factors, and a non-contact measurement. A significant framework can also advance the field of fruit morphology analysis for future application in fruit classification and assessment. [ABSTRACT FROM AUTHOR]

Tree- and block-level prediction of mango yield is important for farm operations, but current manual methods are inefficient. Previous research has identified the accuracies of mango yield forecasting using very-high-resolution (VHR) satellite imagery and an '18-tree' stratified sampling method. However, this approach still requires infield sampling to calibrate canopy reflectance and the derived block-level algorithms are unable to translate to other orchards due to the influences of abiotic and biotic conditions. To better appreciate these influences, individual tree yields and corresponding canopy reflectance properties were collected from 2015 to 2021 for 1958 individual mango trees from 55 orchard blocks across 14 farms located in three mango growing regions of Australia. A linear regression analysis of the block-level data revealed the non-existence of a universal relationship between the 24 vegetation indices (VIs) derived from VHR satellite data and fruit count per tree, an outcome likely due to the influence of location, season, management and cultivar. The tree-level fruit count predicted using a random forest (RF) model trained on all calibration data produced a percentage root mean squared error (PRMSE) of 26.5% and a mean absolute error (MAE) of 48 fruits/tree. The lowest PRMSEs produced from RF-based models developed from location, season and cultivar subsets at the individual tree level ranged from 19.3% to 32.6%. At the block level, the PRMSE for the combined model was 10.1% and the lowest values for the location, seasonal and cultivar subset models varied between 7.2% and 10.0% upon validation. Generally, the block-level predictions outperformed the individual tree-level models. Maps were produced to provide mango growers with a visual representation of yield variability across orchards. This enables better identification and management of the influence of abiotic and biotic constraints on production. Future research could investigate the causes of spatial yield variability in mango orchards. [ABSTRACT FROM AUTHOR]

The regulation of gibberellic acid 2-oxidase (GA2ox) gene expression represents a critical mechanism in the modulation of endogenous gibberellic acids (GAs) levels, thereby exerting an influence on plant height. In this context, we conducted a comprehensive genome-wide analysis of the GA2ox gene family in mango (Mangifera indica L.), a species of significant economic importance, with the aim of identifying potential candidate genes for mango dwarf breeding. Our findings delineated the presence of at least 14 members within the MiGA2ox gene family in the mango genome, which were further categorized into three subfamilies: C19-GA2ox-I, C19-GA2ox-II, and C20-GA2ox-I. Notably, MiGA2ox12, a member of the C19-GA2ox-II subfamily, exhibited substantial expression across various tissues, including roots, bark, leaves, and flowers. Through overexpression of the MiGA2ox12 gene in tobacco, a distinct dwarf phenotype was observed alongside reduced levels of GA1 and GA4, while the knockout line exhibited contrasting traits. This provides evidence suggesting that MiGA2ox12 may exert control over plant height by modulating GA content. Consequently, the MiGA2ox12 gene emerges as a promising candidate for facilitating advancements in mango dwarfing techniques. [ABSTRACT FROM AUTHOR]

A microwave-hot air belt dryer (MHABD) showed high specific energy consumption (SEC) due to its limited material processing capacity and extended drying time. Thus, this research presents the development and performance evaluation of an industrial microwave-hot air belt dryer (IMHABD) for drying Namdokmai Sithong mango slices. The IMHABD system, optimized using the COMSOL Multiphysics program, features a 0.9 m × 4.08 m × 0.5 m chamber with 36 magnetrons having a maximum microwave power of 28,800 W (each magnetron produces 800 W) at a frequency of 2,450 MHz. Two drying methods were studied, step-down microwave power drying (IMHABD-S) and constant microwave power drying (IMHABD-C). IMHABD-S, with a power range of 150–350 W combined with hot air at 65 °C, outperformed IMHABD-C, delivering enhanced drying rates, improved color attributes, and reduced shrinkage, along with decreased hardness and toughness values. All dried slices had a water activity lower than 0.6. An IMHABD-S operated at 350 W for 1.5 h showed the lowest SEC. Economic analysis revealed strong support for the IMHABD process, with a net present value (NPV) of 13,647 USD, an internal rate of return (IRR) of 15%, and a 4.95-year payback with a 10-year service life, highlighting its technical efficacy and economic viability for mango drying applications. [ABSTRACT FROM AUTHOR]

In order to solve the problems of low drying efficiency and poor drying quality existing in the current closed heat pump drying system (CHPD), a closed carbon dioxide heat pump drying system (CHPRD) with the function of combining rotor dehumidification was designed. This study investigates the drying kinetics and quality characteristics of CHPRD in low-temperature drying processes using mango as the drying material through experimental studies and theoretical analysis. The experimental results showed that the drying rate of CHPRD increased by 29% and 17.8%, the moisture removal rate per unit energy (SMER) by 14.2% and 12.5%, and the coefficient of performance (COP) by 17.3% and 12.0%, respectively, compared with that of CHPD in the low-temperature drying process with loading amounts of 400 and 450 g, respectively. In terms of drying quality, the rehydration factor (Rf) of CHPRD-dried mango slices increased by 6.0% and 5.0%, the ascorbic acid content increased by 15.0% and 14.4%, and the color difference (ΔE) was lower by 11.0% and 5.6%, respectively. These improvements indicate that CHPRD provides better drying kinetics and higher quality of dried material. Based on the experimental data, simulation fitting was conducted, revealing that the two-term model is the best mathematical model to simulate the drying characteristics of CHPRD for mango. [ABSTRACT FROM AUTHOR]

Summary Chromosomal inversions can preserve combinations of favorable alleles by suppressing recombination. Simultaneously, they reduce the effectiveness of purifying selection enabling deleterious alleles to accumulate. This study explores how areas of low recombination, including centromeric regions and chromosomal inversions, contribute to the accumulation of deleterious and favorable loci in 225 Mangifera indica genomes from the Australian Mango Breeding Program. Here, we identify 17 chromosomal inversions that cover 7.7% (29.7 Mb) of the M. indica genome: eight pericentric (inversion includes the centromere) and nine paracentric (inversion is on one arm of the chromosome). Our results show that these large pericentric inversions are accumulating deleterious loci, while the paracentric inversions show deleterious levels above and below the genome wide average. We find that despite their deleterious load, chromosomal inversions contain small effect loci linked to variation in crucial breeding traits. These results indicate that chromosomal inversions have likely facilitated the evolution of key mango breeding traits. Our study has important implications for selective breeding of favorable combinations of alleles in regions of low recombination. [ABSTRACT FROM AUTHOR]

So far, the metabolic differences between tree-ripened and postharvest-ripened mangoes have largely remained unexplored. The aim of this study was to evaluate the chemical composition of nutrient substances in mangoes subjected to different ripening methods. An untargeted metabolomic approach based on ultra performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was carried out to investigate the differences between artificially ripened and naturally ripened mangoes. The principal component analysis results indicate a clear separation between the different treatment groups. Variance analysis, fold change, and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to find potential markers. In total, 69 metabolites were identified, with significant variations in the abundance of organic acids, vitamins, carbohydrates, and polyphenols closely related to the ripening methods of mangoes. These results contribute to a better understanding of the metabolic changes in mangoes due to different ripening methods, which could be used to assist in evaluating the quality of mango fruit. [ABSTRACT FROM AUTHOR]

Mango, often regarded as the "king of fruits," holds a significant position in Bangladesh's agricultural landscape due to its popularity among the general population. However, identifying different types of mangoes, especially from mango leaves, poses a challenge for most people. While some studies have focused on mango type identification using fruit images, limited work has been done on classifying mango types based on leaf images. Early identification of mango types through leaf analysis is crucial for taking proactive steps in the cultivation process. This research introduces a novel multi-layer perceptron model called WaveVisionNet, designed to address this challenge using mango leaf datasets collected from five regions in Bangladesh. The MangoFolioBD dataset, comprising 16,646 annotated high-resolution images of mango leaves, has been curated and augmented to enhance robustness in real-world conditions. To validate the model, WaveVisionNet is evaluated on both the publicly available dataset and the MangoFolioBD dataset, achieving accuracy rates of 96.11% and 95.21%, respectively, outperforming state-of-the-art models such as Vision Transformer and transfer learning models. The model effectively combines the strengths of lightweight Convolutional Neural Networks and noise-resistant techniques, allowing for accurate analysis of mango leaf images while minimizing the impact of noise and environmental factors. The application of the WaveVisionNet model for automated mango leaf identification offers significant benefits to farmers, agricultural experts, agri-tech companies, government agencies, and consumers by enabling precise diagnosis of plant health, enhancing agricultural practices, and ultimately improving crop yields and quality. [ABSTRACT FROM AUTHOR]

A convolutional neural network (CNN) can be expected to grade the mango appearance quality for high accuracy. However, it is still challenging to implement CNN on low-cost and performance-constrained edge devices, due to the computation- and storage-intensive CNN algorithm. This has greatly limited the application and promotion of CNN for mango appearance quality grading. In this study, a low-cost grading device was proposed to balance the grading accuracy, speed, power consumption, and detection cost of mango appearance quality using FPGA-accelerated CNN. Firstly, a lightweight network called “ Compact MobileNet” (CMNet) was designed with a simple and efficient structure. The parameter and computational complexity of CMNet were significantly reduced to compress the network structure suitable for the deployment of edge devices with acceptable accuracy. Secondly, Batch normalization (BN) layer fusion and model quantization were used to further reduce the storage requirements and computational complexity of the model, in order to accelerate the execution speed of CMNet on cost- and performance-constrained edge devices. Meanwhile, an FPGA-based hardware accelerator was designed for CMNet. Since the basic function of the accelerator was achieved, the high-level synthesis (HLS) optimization, including “ unrolling the for-loop”, “ pipelining the for-loop”, and “ array partitioning”, were used to optimize the parallelism of the hardware accelerator. Finally, a grading device was developed for the appearance quality of mangoes using an FPGA development board, specifically the “ ZYNQ Z7 Lite 7020” model. An OV5640 camera module, the CMNet network acceleration circuit, and an HDMI interface were integrated to enable the mango image collection, real-time detection, and display of appearance quality. A series of experiments were conducted in a laboratory environment, in order to verify the performance of CMNet and the grading device. The Dosehri mango dataset downloaded from the internet was used to train and validate CMNet. The mango appearance quality was classified into three grades, according to China's agricultural industry standard for mango (NY/T 492-2002). The model comparison demonstrated that the CMNet shared a very lightweight model scale, only with 0.015M parameters and 7.2MFlops computations, with a high grading accuracy of 96.4%. Therefore, the CMNet was suitable for deployment on a resource-limited FPGA terminal. The assessment experiments on the FPGA-based accelerator of CMNet demonstrated that the accelerator significantly expedited the quality grading, with a speed of 0.072 s per frame. The accelerator was capable of detecting the mango appearance quality in real time. The performance comparison among various computing devices revealed that the power consumption of the FPGA-based grading device was 2.6 W, which was the lowest among the tested devices. The FPGA-based detection device offered substantial advantages, in terms of power consumption and portability, compared with the CPUs and GPUs. The FPGA excelled in the best unit cost performance, compared with the portable Raspberry Pi devices and Android smartphones. In summary, all experimental results indicate that a low-cost, low-power, high-accuracy, and high-speed grading device was suitable for assessing mango appearance quality. This device can also be effectively utilized for the real-time grading of mango quality in the field. Furthermore, this finding can provide a strong reference for similar agricultural applications, where artificial intelligence can be employed to rapidly extract information from video data. [ABSTRACT FROM AUTHOR]

Positioning of mango picking points is a crucial technology for the realisation of automated robotic mango harvesting. Herein, this study reported a visualised end-to-end system for mango picking point positioning using improved YOLOv8 architecture with object detection and instance segmentation, as well as an algorithm of picking point positioning. At first, the improved YOLOv8n model, incorporating the BiFPN structure and the SPD-Conv module, was utilised to enhance the detection performance of mango fruits and stems. This model achieved a detection precision of 98.9% in fruits and 97.1% in stems, with recall of 99.5% and 94.6% respectively. Then, the YOLOv8n-seg model was used for segment the stem ROI (Region of interest), leading to 81.85% in MIoU and 88.69% in mPA. Finally, a skeleton line of the stem region was obtained on the basis of the segmentation image, and a picking point positioning algorithm was developed to determine the coordinates of the optimal picking point. Subsequently, the positioning success rate of coordinates, absolute errors, and relative errors were calculated by comparing the automatic positioned coordinates with the manually positioned stem region. Experimental results indicated that this study achieved an average positioning success rate of 92.01%, with an average absolute error of 4.93 pixels and an average relative error of 13.11%. Additionally, the average processing time for processing 640 images using the picking point positioning system is 72.75 ms. This study demonstrates the reliability and effectiveness of positioning mango picking points, laying the technological basis for the automated harvesting of mango fruits. • Simultaneous detection of mango fruits and fruiting stems. • A picking point positioning algorithm is proposed based on instance segmentation. • Development of an end-to-end mango picking point positioning system. [ABSTRACT FROM AUTHOR]

In a preliminary in vitro study, leaves of Acacia nilotica, Prosopis juliflora, Cajanus cajan, Leucaena leucocephala and seed kernel of Mangifera indica were identified as potential candidates in mitigating ruminal methane (CH4) production. The objective of the current study was to investigate the combination efficiency of these unconventional feeds with concentrate mix (CM) or Chloris gayana grass in CH4 reduction. Two feed combinations in different proportions were incubated in vitro with buffered rumen fluid at Hohenheim Gas test. In combination 1, C. gayana and CM were included as basal substrates, while in combination 2, A. nilotica, P. juliflora, C. cajan, L. leucocephala or M. indica seed kernel were included as CH4 reducing supplements at different proportions. The CH4 reducing potentials of feed combinations were presented as the ratio of CH4 to net gas production and expressed as percentage (pCH4). The pCH4 for CM and C. gayana was 16.7% and 16.9%, respectively, while it ranged from 3.18% in A. nilotica to 13.1% in C. cajan. The pCH4 was reduced (p < 0.05) from 14.6% to 9.39% when A. nilotica was combined with CM. In combination of L. leucocephala or C. cajan with CM, the pCH4 (p < 0.05) was reduced from 16.5% and 16.6% with the lowest proportion to 15.1% and 15.2% with the highest inclusion rate respectively. The combination of C. gayana with L. leucocephala or C. cajan reduced (p < 0.05) the pCH4 from 16.3% and 16.4% to 15.1% and 14.9% respectively. The pCH4 was reduced (p < 0.05) from 13.4% to 7.60% when A. nilotica was combined with C. gayana. Estimated digestible organic matter (dOM) and metabolizable energy (ME) increased (p < 0.05) with increasing proportions of M. indica seed kernel with CM or C. gayana. In conclusion, the combination of the basal substrates with unconventional supplements resulted in CH4 reduction without affecting the dOM and ME at lower inclusion rates. Animal‐based experiments await to validate in vitro findings. [ABSTRACT FROM AUTHOR]

Alternative pre-treatment strategies before drying offer the prospect to minimize drying time, replacing the use of chemicals, and preserving quality of dried fresh products. This study explored the application of low-pressure atmospheric cold plasma (CP) for 5- and 10 min (CP5 and CP10) as pre-treatments prior to processing and hot air drying (60 °C) of 'Heidi' mango, while non-treated samples served as control. Changes in tissue microstructure and physicochemical properties, bioactive compounds, and microbial load were evaluated, and seven thin layer drying models were applied. Scanned electron microscope images showed that CP pre-treatments altered the tissue microstructure of dried mango slices compared to control. 'Heidi' mango slices with the initial moisture content of 80 ± 0.2% on a wet basis was reduced by 81% and 76% in dried CP5 and CP10 samples, respectively. Drying time was reduced by 20% for CP pre-treated samples in comparison to control samples, and the drying behavior of 'Heidi' mango slices was best described by the Logarithmic model (R2, 0.9999 and RMSE, 0.0122). Colour attributes were best retained by sodium metabisulphite (SMB) pre-treated samples, followed by CP5 pre-treated, which performed better than CP10 and control (p ≤ 0.05). Highest total flavanols (15.0 ± 0.4 mg CE 100 g−1) and higher total phenolics (1528.2 ± 23.6 mg GA 100 g−1) were found in CP5 pre-treated samples compared to the control (p ≤ 0.05). Lowest antioxidant activities were found in CP10 pre-treated samples compared to the control (p ≤ 0.05). CP-pretreatment and drying resulted in ≥ 2 Log reduction in microbial load on mango slices. These results demonstrate to the role players in mango value addition chain, the potential of low-pressure CP pretreatment in enhancing/maintaining the bioactive compounds, reducing drying time and microbial load. [ABSTRACT FROM AUTHOR]

BACKGROUND: Mango fruits undergo numerous postharvest quality losses during storage. Hence, the present study aimed to increase the shelf life of mango fruits by applying hexanal‐based enhanced freshness formulations (EFF) in combination with hot water treatment (HWT). RESULTS: The findings revealed that, among all the tested applications, the combination of EFF 1.0% + HWT reduced the weight loss, decay incidence, and activity of cell wall degrading enzymes of mango fruits. Also, the combined treatment was effective in maintaining the fruit quality parameters such as soluble solid contents, titratable acidity, ascorbic acid and activity of antioxidant compounds. CONCLUSION: The present study concludes that the postharvest application of EEF 1.0% in combination with HWT can be used in extending the shelf life of mango cv. 'Langra,' fruits stored at 12° C and 85–90% relative humidity for 35 days. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Cetoniidae (Coleoptera), known as flower and fruit beetles, form a diverse group, feed on nectar, pollen, plant exudates, and are highly attracted to fermented fruits. To evaluate their diversity in natural and agricultural areas, traps baited with fermented fruits are used. The objective of this study was to compare the effectiveness of various types of fruit used as bait, with or without the addition of sugarcane juice to accelerate fruit fermentation, on the assessment of Cetoniidae diversity in the Brazilian Cerrado. The study was conducted in two conservation units in Brasília (DF, Brazil). Two experiments were conducted, the first aiming to select the most attractive fruits (banana, pineapple, mango, grape, or cagaita), and the second to verify whether there is interference of sugarcane juice in the fruit fermentation process and, consequently, in the attractiveness to Cetoniidae. The chemical profiles of the types of bait were evaluated by identifying and quantifying the main volatile organic compounds released by the fruit traps. Insect collections were conducted weekly using fruit‐baited traps for 1 month, without interruption. We found that the diversity estimate of Cetoniidae was higher for banana‐based baits relative to grape and cagaita fruit, but not relative to pineapple, mango, and sugarcane juice. Additionally, no increase in attractiveness was observed with the addition of sugarcane juice to banana, pineapple, and mango bait. Most compounds in the fruit extracts belong to alcohol, ester, and terpene functional groups. Our results suggest that banana, pineapple, mango, and sugarcane juice, used alone, may be used for Cetoniidae diversity studies, and that banana bait seems to be the most suitable for Cetoniidae collection in the Cerrado, because it enables the collection of a high diversity of species and also of species considered rare. [ABSTRACT FROM AUTHOR]

The food and agriculture sector is one of the world's most critical and essential industries, as it provides the necessities of life for a growing global population. Food assessment, especially fruit, is an essential mechanism for producers and industries that can affect fruit quality assessment and export markets. However, the food industry still practices manual fruit classification and quality assessment during post-harvest handling and is prone to human error. This research aims to implement a computer-assisted and non-destructive method to classify and determine fruit quality based on colour, odour, and shape characteristics to improve the efficiency of the post-harvest handling process. Six thousand samples of mango, honeydew, chilli and tomato went through the system with data processing techniques (image and odour) and the predictive model using multimodal deep learning algorithms such as convolutional neural network (CNN), CNN-LSTM, and CNN-SVM. The predictive model extracted and concatenated odour and image features using the feature fusion level method. As a result, multimodal CNN-LSTM achieved the highest accuracy rate, such as 93.50% in fruit classification and 96.08% in fruit quality assessment. The experiments demonstrate the feasibility of the proposed multimodal deep learning method in fruit classification and quality assessment. Finally, this fruit assessment intends to provide good food quality to the customers and maintain the food quality consistently. [ABSTRACT FROM AUTHOR]

This study employs machine learning techniques to forecast horticultural production in Indramayu Regency, Indonesia, utilizing data from the Indramayu Regency Statistics Agency from 2009 to 2017. The variables under observation encompass mango fruit production volume, harvest area, rainfall, and the number of rainy days. Mango fruit production volume is the target variable, while the remaining data serves as features. Regression models comprise Linear Regression, Random Forest Regression, Gradient Boosting Regression, and Decision Tree Regression. The research unveils three key findings. Firstly, it underscores the significance of data preprocessing to eliminate noise or outliers, thereby enhancing the performance of regression models, as evidenced by amplified R2 and reduced RMSE values alongside diminished MAPE. Elevated RMSE values highlight the presence of noise or outliers in unprocessed data. Secondly, it emphasizes the necessity of a representative test data proportion for precise prediction outcomes, as indicated by escalating MAPE and RMSE with increased test data proportions. Lastly, it shows the strong correlation between harvest area and mango production volume, culminating in commendable evaluation metrics. Among the regression models, Random Forest Regression emerges as the most robust, boasting the highest R2 value and lowest RMSE, affirming its efficacy in this study. [ABSTRACT FROM AUTHOR]

Mango (Mangifera indica), a nutritionally rich tropical fruit, is significantly impacted by UV-B radiation, which induces oxidative stress and disrupts physiological processes. This study aimed to investigate mango pulp's molecular and biochemical responses to UV-B stress (96 kJ/mol) from the unripe to mature stages over three consecutive years, with samples collected at 10-day intervals. UV-B stress affected both non-enzymatic parameters, such as maturity index, reactive oxygen species (ROS) levels, membrane permeability, and key enzymatic components of the ascorbate-glutathione (AsA-GSH) cycle. These enzymes included glutathione reductase (GR), gamma-glutamyl transferase (GGT), glutathione S-transferases (GST), glutathione peroxidase (GPX), glucose-6-phosphate dehydrogenase (G6PDH), galactono-1,4-lactone dehydrogenase (GalLDH), ascorbate peroxidase (APX), ascorbate oxidase (AAO), and monodehydroascorbate reductase (MDHAR). Transcriptomic analysis revealed 18 differentially expressed genes (DEGs) related to the AsA-GSH cycle, including MiGR, MiGGT1, MiGGT2, MiGPX1, MiGPX2, MiGST1, MiGST2, MiGST3, MiG6PDH1, MiG6PDH2, MiGalLDH, MiAPX1, MiAPX2, MiAAO1, MiAAO2, MiAAO3, MiAAO4, and MiMDHAR, validated through qRT-PCR. The findings suggest that UV-B stress activates a complex regulatory network in mango pulp to optimize ROS detoxification and conserve antioxidants, offering insights for enhancing the resilience of tropical fruit trees to environmental stressors. [ABSTRACT FROM AUTHOR]

Mango, a tropical fruit celebrated for its delightful fragrance and high nutritional value, generates significant waste during processing, with approximately 35–60% of the fruit being discarded. However, this waste contains valuable components, such as fibre, carotenoids, polyphenols, and other bioactive compounds. In an effort to repurpose mango peel, this study dehydrated it to create mango peel powder (MPP), which was then incorporated into sourdough bread to produce functional breads with enhanced nutritional value. Semolina was replaced with MPP at levels of 5% (MPP-5) and 10% (MPP-10) (w/w). After dehydration, the mango peel had a yield of 22%, and the procedure used did not cause any organoleptic changes. The bread fermentation process was conducted at 30 °C for 8 h. During dough fermentation, the pH was monitored, showing a value of 4.14 ± 0.02 in the MPP-10 dough. Overall, the MPP-10 bread received a higher score (6.51) than the control (CTR) bread (5.6) and the MPP-5 bread (6.11). The total phenolic content of the fortified breads ranged from 44.760 to 98.931 mg gallic acid equivalents (GAE)/g, and the antiradical activity ranged from 15.213 to 29.461 mmol trolox equivalent antioxidant activity (TEAC)/100 g, depending on the percentage of enrichment. [ABSTRACT FROM AUTHOR]

Climate change is an emerging threat to global food and nutritional security. The tropical fruits such as mango, bananas, passionfruit, custard apples, and papaya are highly sensitive to weather changes especially; changes of monsoon onset and elevated temperature are influencing crop growth and production. There is a need for more specific studies concerning individual crops and regional variations. Long-term effects and interactions of weather parameters and increased concentration of greenhouse gases, especially carbon dioxide, with phenological stages of the plant, pests, and diseases remain understudied, while adaptation strategies require further exploration for comprehensive understanding and effective mitigation. Few researchers have addressed the issues on the effect of climate change on tropical fruits. This paper focuses on the impact of abiotic (temperature, rainfall, humidity, wind speed, evaporation, carbon dioxide concentration) and biotic (pest and pathogens dynamics) factors affecting the fruit crop ecosystem. These factors influence flowering, pollination, fruit set, fruit yield and quality. This review paper will help develop adaptive strategies, policy interventions and technological innovations aimed at mitigating the adverse effects of climate change on tropical fruit production and safeguarding global food and nutritional security. [ABSTRACT FROM AUTHOR]

Mango fruit is a rich source of bioactive compounds such as carotenoids, phenolics, and ascorbic acid. This research aimed at predicting the content of these bioactive compounds in 'Tommy Atkins' mangoes using optical properties, i.e., the absorption coefficients related to chlorophylls (µa630, µa650, µa670, µa690) and carotenoids (µa540), and the scattering parameters (Mie's A and b), measured during the shelf-life period at 20 °C by time-resolved reflectance spectroscopy. The µa540 and Mie's b increased during shelf-life, while µa670 and Mie's A decreased. Ascorbic acid (AA) and the total antioxidant capacity decreased during shelf-life, while the total carotenoids increased, and the total phenols (TPC) did not significantly change. The major constituent of the nonsaponified extracts, (all-E)-β-carotene, increased during the shelf-life period. A similar trend was observed for the total (all-E)-violaxanthin esters, the total (9Z)-violaxanthin esters and the total neoxanthin esters. Carotenoids are responsible for the yellow-orange color of mangoes: (all-E)-β-carotene was mainly related to a* and h° pulp color while the total (all-E)-violaxanthin esters were mainly linked to b*, C*, and the yellowness index. Using multiple regression analysis, good prediction models were achieved for the total carotenoids (R2adj = 83.1%), the total xanthophylls (R2adj = 78%), (all-E)-β-carotene (R2adj = 77%) and the total (all-E)-violaxanthin esters (R2adj = 74%), while less satisfactory predictions were obtained for AA and TPC. [ABSTRACT FROM AUTHOR]

This study focuses on four species of Lasiodiplodia (L. euphorbiaceicola, L. mahajangana, L. theobromae, and L. pseudotheobromae), which are associated with avocado stem end rot (SER) in Hainan, China. The factors affecting the growth of Lasiodiplodia, pathogenicity to avocado and other tropical fruits, and sensitivity to 12 fungicides, were tested. All Lasiodiplodia spp. isolates were grown between 10 °C and 40 °C, with optimal growth temperature ranging from 28 to 30 °C; the lethal temperature ranged from 51 to 53 °C for 10 min. Optimal growth pH ranged from 5 to 6. The most suitable medium was PDA, the preferred carbon sources were D–fructose and soluble starch, and the preferred nitrogen sources were yeast and beef extract. All Lasiodiplodia spp. isolates were highly pathogenic to avocado fruit. In addition, their pathogenicity to six tropical fruits (banana guava, mango, papaya, pitaya, and soursop) was evaluated, and the results reveal that all four species of Lasiodiplodia are able to infect these fruits to various degrees of severity. The pathogenicity of both L. theobromae and L. pseudotheobromae was the highest among all the species tested. All Lasiodiplodia spp. isolates were highly susceptible to the fungicides fludioxonil, carbendazim, thiophanate–methyl, tetramycin, iprodione, tebuconazole, prochloraz, and imazalil, which are good candidates for controlling avocado SER. The results of the present study provide important information on the biological characteristics of these four species of Lasiodiplodia and provide a basis for the management of SER in avocado. [ABSTRACT FROM AUTHOR]

In recent years, the market has seen a growing demand for healthy and convenient food options, such as fruit and cereal bars, driven by shifts in eating habits. These changes are primarily attributed to time constraints in meal preparation and the need for ready-to-eat foods. Consequently, this has promoted interest in creating a nutritious, high-quality snack combining oats and mango. This study employed a response surface analysis of extreme vertex mixtures, incorporating constraints and three components: oats, mango peel, and dehydrated mango pulp. This resulted in ten different mixtures, each with unique combinations and proportions of the three components. It evaluated the microbiological quality, proximal composition, total phenolic content, tannins, Aw, color, texture, and chemical properties during storage at room temperature. The optimal blend, which demonstrated the best quality characteristics, consisted of 44.38% oats, 5.36% mango peel, and 29.24% mango pulp. This formulation yielded a protein content of 7.1 g, dietary fiber of 20.3 g per 100 g, total phenols of 3.4 mg gallic acid per g, and no pathogenic microorganisms. According to the obtained data, Aw > 0.3, the estimated shelf life could be 12 months at room temperature. Developing a stable oat-mango snack with excellent nutritional, nutraceutical, chemical quality, and microbiological properties is technologically feasible. [ABSTRACT FROM AUTHOR]

In many European countries the consumption of tropical fruit is constantly growing, and people are increasingly turning to diets rich in fruit and vegetables. In this context, mango is considered a super-food for its nutritional medium-high energy value. Produced mainly in developing countries, tropical fruits animate an interesting international market. Production in Mediterranean countries is also growing and is increasingly requested in European markets. The aim of this work is to investigate the factors that drive the inclination to purchase fresh mango and mango food and drinks in Italy and Brazil in order to observe consumer preferences in the two countries. The personal experiences, motivations and choices of consumers regarding fresh mango and mango-based products were taken into consideration. Through an online survey, a semi-structured questionnaire was administered in Italy and Brazil which led to a total sample of 453 participants. The data were statistically analyzed, and a PLS-SEM model was used to empirically examine the factors influencing the consumption of fresh mango and mango food and drinks. The research hypotheses are all supported. For a comparison between the two countries, a multigroup analysis (PLS-MGA) was performed. In Italy, consumers are attentive to the quality and safety of the fruit; they choose the point of sale where they buy fresh mango or mango foods because they trust the seller to guarantee the fruit's origin and transformation. In Brazil, new consumer trends are emerging especially in gastronomy; since they are local foods, they are considered safe, sustainable and healthy by consumers. The study addresses a little-explored topic and aims to enrich the debate on consumer orientations, preferences and reasons for buying mango and mango products. [ABSTRACT FROM AUTHOR]

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This study aimed to evaluate the nutritional requirements of Saccharomyces cerevisiae to improve low ethanol production in some fruit wines. The growth kinetics, ethanol production and nutrient requirements of S. cerevisiae were analyzed in chemically defined media. The results revealed that Ca2+, Fe2+, Co2+, Mo2+, Cu2+ and BO33− were predominantly utilized during the late lag phase, whereas free amino acids, nicotinic acid, calcium pantothenate, Na+ and Mg2+ were mainly consumed during the logarithmic phase. Compared with the control medium, supplementation with threonine, inositol, calcium pantothenate, thiamine hydrochloride, riboflavin, biotin, MgSO4 or KH2PO4 significantly increased the ethanol content by 1.10-fold (p < 0.05). Furthermore, adding key nutrients to noni-, guava- and mango juice significantly shortened the fermentation time and increased the final alcohol content of the fruit wines (p < 0.05). This study provides scientific insights and effective methods for shortening fermentation time and increasing alcohol content with S. cerevisiae in some fruit wines. [ABSTRACT FROM AUTHOR]

Ultraviolet shortwave (UV-C) is a technology for postharvest fruit disinfection. This study aimed to use computational fluid dynamics (CFD) based on the discrete ordinate (DO) radiation model to analyze the distribution of UV-C intensity on whole and minimally processed mangoes within a disinfection chamber and to predict treatments against foodborne pathogens. The mango spears were oriented both parallel and perpendicular to the lamp and positioned at varying distances from the radiation source (50, 75, and 100 mm for spears and 100 mm for whole fruit). CFD simulations integrated with in vitro kinetic parameters enabled predictions of the time and doses needed to inactivate one to three logarithmic units of pathogens on the fruit surface. The highest average radiation intensity values were recorded for the whole mango oriented parallel to the lamp at 100 mm and the spears oriented normally to the lamp at 50 mm. The estimated times to achieve inactivation of one to three logarithmic units of microorganisms ranged from approximately 15 to 6540 s, while the doses necessary for this inactivation were, on average, 1.854, 5.291, and 10.656 kJ/m2, respectively. CFD simulations are valuable for optimizing UV-C treatments in large-scale designing from both microbicide and sustainable perspectives. [ABSTRACT FROM AUTHOR]

Change in land‐use patterns affects a landscape by changing the composition of local flora and fauna. The lateritic plateaus in Konkan are one such example of this rapid land‐use change. Although these plateaus are rich in endemic flora and fauna, they are considered as "wastelands" due to lack of woody vegetation and thus, are subjected to various land‐uses. Mango cultivation in this region has become a major source of income due to its Alphonso variety of mangoes. Hence, over the last few decades, many plateaus have been converted into mango orchards. However, how the conversion of plateaus to mango orchards has affected species composition of different groups of organisms remains unclear. In the present study, we sampled the lateritic plateaus and plateaus converted into mango orchards in Ratnagiri, Maharashtra, to investigate the response of the reptile communities. We observed more species heterogeneity in the orchards compared to the unaltered sites. Moreover, it appeared that there was a species turnover when the plateaus were converted into orchards. The generalist and widespread species such as agamids and skinks and very few specialist species were comparatively more abundant in the orchards. On the contrary, the plateaus without orchards harbored more specialist species such as Hemidactylus albofasciatus (n = 62, in unaltered sites vs. n = 5 in the orchards), Echis carinatus (n = 15 in unaltered sites and none in the orchards) and Ophisops jerdonii (n = 45 in unaltered site vs. n = 12 in the orchards) compared to the generalist species. [ABSTRACT FROM AUTHOR]

Current treatments for severe acne include combinations of synthetic anti-inflammatory and antibacterial drugs, which possess numerous side effects. Therefore, this study developed microemulsion-based hydrogel containing lemongrass leaf essential oil (Cymbopogon citratus (DC.) Stapf) and mango seed kernel extract (Mangifera indica Linn) as a potential natural therapy for inflammatory acne. To this end, the microemulsions were first prepared using pseudo-ternary phase diagrams with soybean oil and coconut oil, cremophor RH40, and PEG 400. The optimal formula could load 1% lemongrass oil and 10% mango extract, possessed a spherical droplet size of ~18.98 nm, a zeta potential of -5.56 mV, and a thermodynamic stability. Secondly, the microemulsion-based hydrogel was developed by simple mixing the optimal microemulsion in carbopol-940 hydrogel (3.5% w/w). The product showed a viscosity of ~3728 cPs, a pH of 5.4-6.2, a spreadability of ~24 cm, an in-vitro Franz-cell cumulative release rate of ~80% for polyphenol content and ~60% for citral within 12 h, and a good physicochemical stability of > 3 months. Thirdly, the skin compatibility/irritability of the microemulsion-based hydrogel was determined by the HET-CAM assay, which showed non-irritation level. Finally, the anti-inflammatory activities of the hydrogel, using heat-induced BSA denaturation assay and LPS-stimulated RAW 264.7 NO inhibition assay, was 4-times higher than that of the reference drug Klenzit-C® (adapalene and clindamycin gel). Moreover, the hydrogel possessed strong anti-biofilm activity in Cutibacterium acnes, comparable with Klenzit-C®. Conclusively, the microemulsion-based hydrogel containing lemongrass oil and mango seed extract demonstrated much potentials to be a promising natural drug for acne treatment. [ABSTRACT FROM AUTHOR]

Background: Mango is a tropical fruit with high economic value. The selection of suitable dwarf mango varieties is an important aspect of mango breeding. However, the mechanisms that regulate mango dwarfing remain unclear. Results: In this study, we compared the transcriptomes and metabolomes of mango varieties Guiqi (a dwarfed variety) and Jinhuang (an arborized variety). A total of 4,954 differentially expressed genes and 317 differentially abundant metabolites were identified between the two varieties, revealing the molecular mechanism of the gibberellin 3β-hydroxylase gene GA3ox in regulating dwarfing traits in mangoes using joint transcriptome and metabolome analyses. The results showed that differentially expressed genes were enriched in the diterpenoid biosynthesis pathway and that differentially abundant metabolites were annotated to their upstream pathway, the terpenoid backbone biosynthesis. A gene regulation network based on these two pathways was constructed, indicating the upregulation of the GA3ox gene and the accumulation of gibberellin in dwarfed mangoes. We then transferred the GA3ox gene to tobacco plants following the application of gibberellin, and the morphology and height of the transgenic tobacco plants largely recovered the phenotype. Conclusions: These results demonstrated that GA3ox plays a role in the regulation of dwarf traits. Our study provides an important theoretical basis for studying the regulatory mechanisms underlying mango dwarfism to facilitate mango breeding. [ABSTRACT FROM AUTHOR]

Mango fruit undergoes various physiochemical changes after its harvest that affect consumer acceptability. The present research work was carried out to evaluate the preservation effect of sodium nitroprusside (SNP) treatments on the postharvest quality of mango cv. Langra fruits at 12 ± 1°C for 35 days. The results revealed that SNP 1.0 mM treated fruits exhibited reduced weight loss (6.94%), decay incidence (8.05%), and activities of cell wall degrading enzymes like polygalacturonase and pectin methyl esterase in comparison to uncoated fruits on the last day of storage. Furthermore, the treatment maintained higher fruit firmness (56.77 N) along with fruit quality parameters like soluble solid content (16.24%), titratable acidity (0.20%), starch (4.99%), and, total flavonoid content (12.92 mg/100 g). Overall, SNP 1.0 mM combined with low-temperature storage was proved to be the most effective in extending the shelf life and preserving the quality characteristics of mango fruits. [ABSTRACT FROM AUTHOR]

Mango is a highly diverse tropical fruit with numerous varieties that differ in flavor, texture, and chemical composition. Consequently, identifying fraudulent substitutions of mango varieties poses a significant challenge using traditional techniques. Therefore, there is an increasing need for new methods to discriminate between mango varieties. Hyperspectral imaging coupled with machine learning techniques presents a promising approach for varietal discrimination. In this study, mango samples of eleven varieties were collected from a germplasm bank, with four slices obtained from each sample. Hyperspectral images were acquired in the Vis–NIR and NIR ranges for each slice, and spectral profiles were extracted and pretreated. Three discrimination models, linear discriminant analysis, K-nearest neighbor, and artificial neural networks, were implemented and validated using relevant wavelengths selected through a covering array feature selection algorithm. The performance of these models was evaluated using precision, accuracy, and F-score metrics. The average spectral profiles of the studied varieties exhibited a similar behavior with slight differences, which could be used for classification within the evaluated ranges. The optimal number of variables selected to refine the models was 17 for the UV–Vis–NIR range and 21 for the NIR range, with an accuracy ranging between 0.752 and 0.972. This study concludes that hyperspectral imaging combined with machine learning techniques can effectively discriminate between different varieties of mango. [ABSTRACT FROM AUTHOR]

This study tested whether encouraging prediction enhances prediction in second language (L2) speakers. L2 English speakers listened to English sentences like The woman … will read/buy one of the newspapers while viewing the target (a newspaper) and distractor objects (a rose, a bowl, and a mango) on a screen and clicked on the target as quickly as possible. The target was predictable (read) or unpredictable (buy) from the verb meaning. Participants looked at the target longer and were quicker to move the mouse to it when instructed to predict sentence continuation than when they were merely instructed to comprehend sentences. This result held true both when the target was predictable and unpredictable. Furthermore, only when instructed to predict did the participants make more clicking errors when the target was unpredictable than predictable, which suggested that encouraging prediction can interfere with word recognition accuracy in unpredictable contexts due to reduced cognitive resources or failed predictions. [ABSTRACT FROM AUTHOR]

AbstractUnderstanding the nutritional dynamics before pruning is essential to elucidate how nutrient reserves affect the mango tree’s ability to regenerate tissues. A research project was carried out to determine the adequate range of supply for mango sprout phase (pre-pruning) in two different mango leaves (from the first and second vegetative flushes), and evaluate effect of biochemical activity on mango sprouting and correlate it with fruit yield. Two experiments with ‘Ataulfo’ and ‘Kent’ mangoes were carried out from 2021 to 2023. The experiments were arranged in randomized blocks with treatments distributed in subdivided plots referring to two N sources (NO3-, NH4+) in the plots and N doses (0, 50, 100, 150 and 200% of the recommended dose) in the subplots. The leaf nutrient concentrations, sodium, and α-amylase were evaluated in leaves of the 1st and 2nd vegetative flush, the number of shoots per pruned branch, and fruit yield. The number of shoots per pruned branch, influenced by the nutritional status prior to production pruning, varies with nutrient, and the 2nd vegetative flush after the previous pruning has a greater impact on shoot development in the current cycle. The shoot growth of the ‘Ataulfo’ after production pruning depends on leaf concentrations of phosphorus, potassium, calcium, sulfur, cooper, manganese, zinc and molybdenum, in addition to sodium, while ‘Kent’ depends only on phosphorus, cooper, iron, manganese, and zinc. The highest fruit yield indices are recorded under the average number of sprouts per pruned branch of 2.72 for ‘Ataulfo’ and 2.63 for ‘Kent’. [ABSTRACT FROM AUTHOR]

AbstractThe catalytic effect of climate change on the emergence and prevalence of invasive alien pests along with weak pesticide regulatory frameworks in developing countries calls for a transition towards sustainable pest management. Agro-ecological pest management (APM) offers a nature-based, cost-effective alternative for addressing systemic pest challenges, such as mango fruit fly invasion. We applied a two-part fractional regression to sequentially model APM adoption and intensity decisions among 423 smallholder mango orchard managers from Makueni County, Kenya. Despite APM’s potential, we observed moderate adoption rates (56.7%), with the average adopter implementing only 25% of the APM practices concurrently. Farmers’ socio-psychological attributes significantly influenced both adoption and intensity decisions. While perceptions of technology attributes and institutional and social factors primarily influenced both the adoption and intensity decisions, information constraints, resource endowment, gender and inter-generational factors significantly influenced only the intensity decision. To support the transition from synthetic insecticides to APM measures, policymakers should create more opportunities for awareness creation, training and knowledge co-creation and co-production, particularly through social networks and gender-disaggregated participatory group approaches. [ABSTRACT FROM AUTHOR]

[Objective] To study the effect of chitosan-CMC composite film on the storage quality of Xiaoguifei mango. [Method] Chitosan membrane, CMC membrane, and chitosan-CMC composite membrane were prepared using chitosan and carboxymethylcellulose sodium (CMC) as film-forming agents. The Xiaoguifei mangoes treated with these three types of membranes were divided into groups A, B and C, and the CK group was set. Storage at room temperature (20± 2)℃, the effects of three types of membranes on the storage quality of Xiaoguifei mango were studied by measuring the disease index, decay rate, weight loss rate, acidity, soluble solids and scanning electron microscopy analysis of groups A, B, C and CK. [Result]After 20 days of storage, the disease index, decay rate and weight loss rate of Xiaoguifei mango treated with composite film were the lowest, while the acidity and soluble solids content were the highest. Scanning electron microscopy analysis revealed that the composite film had good cross-linking and a uniform and dense structure. [Conclusion]The CMC film had no preservation effect on the storage of Xiaoguifei mangoes, while chitosan-CMC composite film and chitosan film had a preservation effect on Xiaoguifei mangoes, and the preservation effect of chitosan-CMC composite film was greater than that of chitosan film. [ABSTRACT FROM AUTHOR]