Search Results (188)

Mango is highly sensitive to heat stress, which directly affects the yield and quality. The extreme heat waves of 2024, with temperatures reaching 41–47 °C over 25 days, caused significant impacts on sensitive cultivars. The impact of heat waves on ten commercial cultivars from subtropical regions viz.,‘Dashehari’, ‘Langra’, ‘Chausa’, ‘Bombay Green’, ‘Himsagar’, ‘Amrapali’, ‘Mallika’, ‘Sharda Bhog’, ‘Kesar’, and ‘Rataul’, and thirteen selected elite hybrids H-4208, H-3680, H-4505, H-3833, H-4504, H-1739, H-3623, H-1084, H-4264, HS-01, H-949, H-4065, and H-2805, is reported. The predominant effects that were observed include the following: burning symptoms or blackened tips, surrounded by a yellow halo, with premature ripening in affected parts and, in severe cases, tissue mummification. Among commercial cultivars, viz., ‘Amrapali’ (25%), ‘Mallika’ (30%), ‘Langra’ (30%), ‘Dashehari’ (50%), and ‘Himsagar’ and ‘Bombay Green’ had severe impacts, with ~80% of fruits being affected, followed by ‘Sharda Bhog’. In contrast, mid-maturing cultivars like ‘Kesar’, ‘Rataul’, and late-maturing elite hybrids, which were immature during the stress period, showed no symptoms, indicating they are tolerant. Biochemical analyses revealed significantly elevated total soluble solids (TSS > 25 °B) in affected areas of sensitive genotypes compared to non-affected tissues and tolerant genotypes. Aroma profiling indicated variations in compounds such as caryophyllene and humulene between affected and unaffected parts. The study envisages that the phenological maturity scales are indicators for the selection of climate-resilient mango varieties/hybrids and shows potential for future breeding programs. Full article

Mango, as an important economic crop in tropical and subtropical regions, suffers from chilling injuries caused by postharvest low-temperature storage, which seriously affect its quality and economic benefits. Traditional detection methods have limitations such as low efficiency and strong destructiveness. This study designs and implements a flexible visible light spectral sensing system based on visible light spectral sensing technology and low-cost environmentally friendly flexible circuit technology. The system is structured based on a perception-analysis-warning-processing framework, utilizing laser-induced graphene electroplated copper integrated with laser etching technology for hardware fabrication, and developing corresponding data acquisition and processing functionalities. Taking Yunnan Yumang as the research object, a three-level chilling injury label dataset was established. After Z-Score standardization processing, the prediction accuracy of the SVM (Support Vector Machine) model reached 95.5%. The system has a power consumption of 230 mW at 4.5 V power supply, a battery life of more than 130 days, stable signal transmission, and a monitoring interface integrating multiple functions, which can provide real-time warning and intervention, thus offering an efficient and intelligent solution for chilling injury monitoring in mango cold chain storage. Full article

Agriculture in India supports millions of livelihoods and is a major force behind economic expansion. Challenges in modern agriculture depend on environmental factors (such as soil quality and climate variability) and biotic factors (such as pests and diseases). These challenges can be addressed by advancements in technology (such as sensors, internet of things, communication, etc.) and data-driven approaches (such as machine learning (ML) and deep learning (DL)), which can help with crop yield and sustainability in agriculture. This study introduces an innovative deep neural network (DNN) approach for identifying leaf diseases in paddy crops at an early stage. The proposed neural network is a hybrid DL model comprising feature extraction, channel attention, inception with residual, and classification blocks. Channel attention and inception with residual help extract comprehensive information about the crops and potential diseases. The classification module uses softmax to obtain the score for different classes. The importance of each block is analyzed via an ablation study. To understand the feature extraction ability of the modules, extracted features at different stages are fed to the SVM classifier to obtain the classification accuracy. This technique was experimented on eight classes with 7857 paddy crop images, which were obtained from local paddy fields and freely available open sources. The classification performance of the proposed technique is evaluated according to accuracy, sensitivity, specificity, F1 score, MCC, area under curve (AUC), and receiver operating characteristic (ROC). The model was fine-tuned by setting the hyperparameters (such as batch size, learning rate, optimizer, epoch, and train and test ratio). Training, validation, and testing accuracies of 99.91%, 99.87%, and 99.49%, respectively, were obtained for 20 epochs with a learning rate of 0.001 and sgdm optimizer. The proposed network robustness was studied via an ablation study and with noisy data. The model’s classification performance was evaluated for other agricultural data (such as mango, maize, and wheat diseases). These research outcomes can empower farmers with smarter agricultural practices and contribute to economic growth. Full article

Background: Acute visceral pain is among the most common symptoms of patients seeking in-hospital treatment and is related to various thoracic, abdominal, and pelvic diseases. It is characterized by distinguishable sensory qualities and can be described on a sensory-discriminative and affective-motivational level. These sensory qualities correlate with the activation of cerebral areas involved in the neuronal processing of visceral pain and can be visualized using functional neuroimaging. Methods: An ALE (activation likelihood estimation) meta-analysis of a total of 21 studies investigating different balloon distention paradigms during either PET or fMRI was performed to demonstrate the neuroanatomical correlates of visceral pain. The ALE meta-analysis was performed using the GingerAle software version 3.0.2 and was displayed with the Mango software 4.1 on an anatomical MNI template. Results: Summarizing studies investigating the functional neuroanatomy of visceral pain, bihemispheric activation of the insula, the thalamus, and clusters involving the right inferior parietal lobe/postcentral gyrus as well as the left postcentral gyrus/parietal inferior lobe were observed. Conclusions: This ALE meta-analysis substantiates the concept of two distinguishable neuroanatomical pathways of visceral pain which are related to either the sensory-discriminative or the affective-motivational dimension of pain processing. Full article

The SWEET gene family is a group of genes with important functions in plants that is mainly involved in the transport and metabolism of carbohydrate substances. In this study, 32 mango (Mangifera indica L.) SWEET genes were screened and identified at the whole-genome level through bioinformatics methods. A systematic predictive analysis was conducted on their physicochemical properties, homology relationships, phylogenetic relationships, chromosomal locations, genomic structures, promoter cis-acting elements, and transcription factor regulatory networks. Meanwhile, the transcription levels of mango SWEET genes in different varieties and at different fruit development stages were also analyzed to obtain information about their functions. These results showed that 32 mango SWEET genes were unevenly distributed on 12 chromosomes. Phylogenetic analysis divided the SWEET proteins of mango, Arabidopsis thaliana (L.) Heynh., and Oryza sativa L. into four clades; in each clade, the mango SWEET proteins were more closely related to those of Arabidopsis. Four types of cis-acting elements were also found in the promoter regions of mango SWEET genes, including light-responsive elements, development-related elements, plant hormone-responsive elements, and stress-responsive elements. Interestingly, we found that the Misweet3 and Misweet10 genes showed strong expression in different mango varieties and at different fruit development stages, and they both belonged to the fourth Clade IV (G4) in the phylogenetic tree, indicating that they play a key role in the sugar accumulation process of mango. In this study, the upstream transcription factors of Misweet3, Misweet8, Misweet9, Misweet10, Misweet17, Misweet18, Misweet19, Misweet21, Misweet23, Misweet25, Misweet27, and Misweet31, those that had high expression levels in the transcriptome data, were predicted, and transcription factors such as ERF, NAC, WRKY, MYB, and C₂H₂ were screened. The results of this study provide a new way to further study the regulation of mango SWEET family genes on sugar accumulation, highlight their potential role in fruit quality improvement, and lay an important foundation for further study of mango SWEET function and enhance mango competitiveness in fruit market. Full article

During the flowering period of mango trees, pests often hide in the inflorescences to suck sap, affecting fruit formation. By accurately detecting the number and location of mango inflorescences in the early stages, it can help target-specific spraying equipment to perform precise pesticide application. This study focuses on mango panicles and addresses challenges such as high crop planting density, poor image quality, and complex backgrounds. A series of improvements were made to the YOLOv8 model to enhance performance for this type of detection task. Firstly, a mango panicle dataset was constructed by selecting, augmenting, and correcting samples based on actual agricultural conditions. Second, the backbone network of YOLOv8 was replaced with FasterNet. Although this led to a slight decrease in accuracy, it significantly improved inference speed and reduced model parameters, demonstrating that FasterNet effectively reduced computational complexity while optimizing accuracy. Further, the GAM (Global Attention Module) attention mechanism was introduced as an attention module in the backbone network to enhance feature extraction capabilities. Experimental results indicated that the addition of GAM improved the average precision by 2.2 percentage points, outperforming other attention mechanisms such as SE, CA, and CBAM. Finally, the model’s bounding box localization ability was enhanced by replacing the loss function with WIoU, which also accelerated model convergence and improved the mAP@.5 metric by 1.1 percentage points. Our approach demonstrates a discrepancy of less than 10% compared to manual counted results. Full article

Precision agriculture is an approach that uses information technologies to improve and optimize agricultural production. It is based on the collection and analysis of agricultural data to support decision making in agricultural processes. In recent years, Artificial Neural Networks (ANNs) have demonstrated significant benefits in addressing precision agriculture needs, such as pest detection, disease classification, crop state assessment, and soil quality evaluation. This article aims to perform a systematic literature review on how ANNs with an emphasis on image processing can assess if fruits such as mango, apple, lemon, and coffee are ready for harvest. These specific crops were selected due to their diversity in color and size, providing a representative sample for analyzing the most commonly employed ANN methods in agriculture, especially for fruit ripening, damage, pest detection, and harvest prediction. This review identifies Convolutional Neural Networks (CNNs), including commonly employed architectures such as VGG16 and ResNet50, as highly effective, achieving accuracies ranging between 83% and 99%. Additionally, it discusses the integration of hardware and software, image preprocessing methods, and evaluation metrics commonly employed. The results reveal the notable underuse of vegetation indices and infrared imaging techniques for detailed fruit quality assessment, indicating valuable opportunities for future research. Full article

The sensation of dyspnea is related to various cardiopulmonary and neuromuscular diseases and is characterized by its sensory and affective qualities. Although there is a vast number of studies investigating its pathophysiology, less is known about the neuroanatomy of dyspnea perception. An activation likelihood estimation (ALE) meta-analysis of 13 studies investigating different breathing challenges using either PET or fMRI was performed to demonstrate the neuroanatomical correlates of dyspnea perception. The ALE meta-analysis was performed using the GingerAle software 3.0.2 and was displayed with the Mango software 4.1. Synthesizing the results of all included studies, clusters involving the insula and cingulated cortex in both hemispheres were observed. Subgroup analysis for the restrained breathing condition revealed activation involving the right and left cingulate cortex and left anterior cingulate cortex. For the loaded breathing condition, statistically significant activation was found for the postcentral gyrus, the superior temporal gyrus, and the right thalamus. The combined ALE map for both conditions showed activity patterns in the right cingulate cortex, the right insula, and the right thalamus. This ALE meta-analysis demonstrates that two separate neuronal pathways related to either the affective or intensity domain are involved in the central processing of dyspnea perception. Full article

Inflorescence cutting is a critical cultural practice that enhances yield and fruit quality in mango cultivation. This study evaluated four treatments with the “Tainongyihao” mango: no cutting (CK), 1/3, 1/2, and 2/3 cutting of the central inflorescence axis, classified as light (L), medium (M), and heavy (H) cutting, respectively. Inflorescences were categorized by length, and field experiments were conducted during the growth periods of autumn–winter and winter–spring fruit in under-regulated and conventional harvest systems. The measured indicators include yield efficiency per unit trunk circumference, average fruit weight, reduced sugar content, total soluble solids (TSS), total titratable acids (TA), vitamin C content (Vc), and the TSS/TA ratio. Results indicated that light cutting was optimal for yield efficiency of autumn–winter fruit, while medium and heavy cutting were most effective for winter–spring fruit. Comprehensive fruit quality improved most under heavy cutting across all inflorescences. Long inflorescences benefited from heavy or medium cutting, medium inflorescences benefited from heavy cutting, and short inflorescences benefited from medium cutting. Interactive effects were observed between inflorescence-cutting treatments and inflorescence length, with fruit quality consistently improving under inflorescence-cutting treatments. Heavy cutting is recommended for manual operations, and all the results of this paper provide a foundation for developing artificial intelligence (AI)-based inflorescence-cutting technologies that enable precise and efficient mango cultivation practices. Full article

Mango fruits are susceptible to cold stress under prolonged storage. Melatonin (MT) is a phytohormone well known for enhancing the tolerance and overall quality of various tropical and subtropical fruits during cold storage. This study investigated the effects of MT treatment on the postharvest quality of mango fruits during prolonged cold storage. Mangoes were treated with different concentrations of MT (1.0 mM (T1), 1.5 mM (T2), 2.0 mM (T3), and 2.5 mM (T4)) and stored for 45 days under cold conditions (15 °C and 90% relative humidity). Control fruits had no MT treatments. Various physicochemical, phytochemical, antioxidant, and enzymatic activities were monitored every 5 days throughout the storage period. MT treatment significantly reduced the weight loss and decay rates compared to control samples, with T3 and T4 treatments showing superior effectiveness. Due to severe decay in the control samples, the storage period was terminated on day 25, whereas the MT treatment protected the mango fruits and allowed for the completion of all 45 days of storage. The MT treatments effectively maintained color characteristics, reduced respiration rates, and suppressed ethylene production in mango fruits compared to the control samples. Higher MT concentrations preserved firmness and controlled malondialdehyde accumulation (p < 0.05). Chemical properties, including the starch content, total soluble solids, and titratable acidity, were better maintained in MT-treated fruits. The treatments also enhanced the retention of phytochemicals (ascorbic acid, total phenolic, and total flavonoid contents) and improved antioxidant activities against DPPH and ABTS radicals. Furthermore, MT treatment effectively regulated the activities of browning-related enzymes (polyphenol oxidase (PPO) and peroxidase (POD)), cell wall-degrading enzymes (polygalacturonase (PG), pectin methylesterase (PME), and lipoxygenase (LOX)), and antioxidant enzymes (superoxide dismutase (SOD) and ascorbate peroxidase (APX)). The results demonstrate that MT treatment, particularly at higher concentrations (T3 and T4), effectively extends the storage life and maintains the quality of mango fruits during prolonged cold storage. Full article

Lacticaseibacillus rhamnosus is a strain predominantly used for juice production because of its excellent fermentation characteristics and strong acid production capacity. However, the influence of L. rhamnosus on the quality of mango juice has not yet been determined. Therefore, the effects of L. rhamnosus FJG1530 on the physicochemical properties, physiological activity, and volatile and non-volatile compounds of mango juice were extensively examined in this study. The data showed that L. rhamnosus FJG1530 possessed strong adaptability to mango juice, reducing its total sugar and increasing its total flavonoids. L. rhamnosus FJG1530 fermentation enhanced the ability of mango juice to clear the free radicals ABTS and DPPH, as well as improving the inhibition of lipase and α-glucosidase. In addition, L. rhamnosus FJG1530 treatment improved the volatile compounds in mango juice, especially promoting the formation of acids and alcohols. Simultaneously, metabolomic analysis revealed that 592 non-volatile compounds in mango juice were significantly changed by L. rhamnosus FJG1530 fermentation, with 413 dramatically increased and 179 significantly decreased metabolites. This study demonstrates that the fermentation process using L. rhamnosus FJG1530 was beneficial for ameliorating the quality of mango juice. Full article

The growing global population has led to increased food consumption and a significant amount of food waste, including the non-consumed parts of fruits (e.g., stems, rinds, peels, seeds). Despite their nutrient richness, these by-products are often discarded. With the rising interest in nutrient-dense foods for health benefits, fruit by-products have potential as nutritious ingredients. Upcycling, which repurposes waste materials, is one solution. White flour, which is common in food products like bread and pasta, has good functional properties but poor nutritional value. This can be enhanced by blending white flour with fruit by-product flours, creating functional, nutrient-rich mixtures. This review explores using flours from common Brazilian fruit by-products (e.g., jaboticaba, avocado, guava, mango, banana, jackfruit, orange, pineapple, and passion fruit) and their nutritional, physical–chemical properties, quality and safety, and applications. Partially replacing wheat flour with fruit flour improves its nutritional value, increasing the amount of fiber, protein, and carbohydrates present in it. However, higher substitution levels can alter color and flavor, impacting the sensory appeal and acceptability. While studies showed the potential of fruit by-product flours in food formulation, there is limited research on their long-term health impacts. Full article

Nitrogen (N) is vital for mango yield and fruit quality, but finding the optimal amount is crucial to avoid the ‘stay green’ problem, which diminishes both fruit quality and profitability. This study aimed to assess the impact of N levels on the fruit quality and yield of ‘Kensington Pride’ (‘KP’) mangoes and determine the amount of N that triggers the ‘stay green’ effect in fruit. A field trial was conducted in a commercial orchard with N treatments (0, 12.5, 25, and 50 kg ha⁻¹) and four replications during the 2018 and 2019 cropping seasons. Fruit yield was quantified, and post-harvest quality (skin color during ripening, sugar content [°Brix], and texture) as well as ethylene effects were assessed. Fruit yields did not vary among N levels over the two cropping seasons but were significantly lower in 2018 (20.0 t ha⁻¹) compared to 2019 (38.5 t ha⁻¹), illustrating the alternate year-bearing habit of ‘KP’ mangoes. In the 2018 harvest, fruit from trees receiving 25 kg N ha⁻¹ appeared yellow–green compared to those with less N, while fruit from trees with 50 kg N ha⁻¹ exhibited ‘stay green’ skin, indicating that applications of 25 and 50 kg N ha⁻¹ were excessive. There was no ‘stay green’ skin observed in the 2019 harvest, indicating that the environment may also be a contributing factor. The texture of ripe fruit from untreated control trees had the highest flesh resistance. Moreover, ethylene-treated fruit ripened in nine days post-harvest and had significantly lower sugar content than untreated fruit, which ripened in 14 days. This study provides valuable insights into the complex interactions among N application, fruit quality, and yield of ‘KP’ mangoes, highlighting the importance of appropriate N management for a sustainable and environmentally friendly commercial mango production system. Full article

Incorporation of plant residues in soil affects microbial community structure and ecological function, which can improve soil fertility. It is reported that substrate qualities could regulate microbial keystone taxa and their interactions, wielding an important effect on nutrient cycling in ecosystems, such as soil labile phosphorus (P) transformation. However, there is little understanding of the specific microbial mechanisms governing P’s availability in acidic soils following the incorporation of plant residues of various qualities. In this 210-day incubation experiment, two high-quality residues of pumpkin stover and mango branch and one low-quality residue of rice straw, different in terms of their labile carbon (C) content and carbon/phosphorus ratio (C/P), were separately mixed with an acidic soil. The aim was to investigate how the residues affected the community composition, keystone species, and interaction patterns of soil bacteria and fungi, and how these microbial characteristics altered soil P mineralization and immobilization processes, along with P availability. The results showed that adding high-quality pumpkin stover significantly increased the soil’s available P content (AP), microbial biomass P content (MBP), and acid phosphatase activity (ACP), by 63.7%, 86.7%, and 171.7% compared to the control with no plant residue addition, respectively. This was explained by both the high abundance of dominant bacteria (Kribbella) and the positive interactions among fungal keystone species. Adding mango branch and rice straw induced cooperation within fungal communities while resulting in lower bacterial abundances, thereby increasing AP, MBP, and ACP less than the addition of pumpkin stover. Moreover, the labile C of plant residues played a dominant role in soil P transformation and determined the P availability of the acidic soil. Therefore, it may be suitable to incorporate high-quality plant residues with high labile C and low C/P into acidic soils in order to improve microbial communities and enhance P availability. Full article

Commercial mango growers commonly spray potassium nitrate (KNO₃) solution to enhance flowering and fruit quality, yet there is limited information on the uptake efficiency of nitrogen (N) by mango cultivars through leaf cuticles. The study aimed to assess N uptake efficiency (NUpE) from foliar application of KNO₃ solution and compare NUpE among mango varieties. Mango cultivars were ‘Kensington Pride’ (‘KP’), ‘B74’ (‘Calypso^®’), and ‘NMBP 1201’ (‘AhHa!^®’), ‘NMBP 1243’ (‘Yess!^®’), and ‘NMBP 4069’ (‘Now^®’) grafted onto ‘KP’ seedlings. Leaves of six-month-old seedlings were dipped in ¹⁵N-enriched KNO₃ solution and analyzed for total N and ¹⁵N contents. A significant correlation was observed between the leaf area and the amount of solution retained after dipping the leaves in the KNO₃ solution. Moreover, leaves treated with the KNO₃ solution had higher ¹⁵N levels than the natural ¹⁵N abundance, indicating successful N uptake from the KNO₃ solution. The NUpE ranged from 27% to 44% and varied with variety. Cultivar ‘NMBP 4069’ had the highest NUE (44%) which was comparable with that of ‘B74’ (40%). ‘NMBP 1201’ showed the lowest (27%) NUpE which was comparable with that of ‘NMBP 1243’ (30%) and ‘KP’ (33%). These data on ¹⁵N uptake through the mango leaf cuticle demonstrates the effectiveness of foliar application as a method of supplying N to mango trees, highlighting important varietal differences in foliar ¹⁵N uptake efficiency. Considering these differences in NUpE among mango varieties will help in making informed decisions about cultivar selection and N management strategies for sustainable mango production. Full article