Stages Of Fruit Growth Research Articles

Temperature and Precipitation Synergistically Affect Yield, Harvesting Time and Post-Processing Quality of Tropical Macadamia Nuts

In response to climate change challenges and to ensure stable macadamia nut production, this study analyzed empirical data on macadamia nut yield, climate factors, harvesting time, and post-processing quality from 2020 to 2022. Key findings include: (1) During the flowering to fruit growth stage, 2020 had the highest average temperature, followed by 2021, and then 2022. Conversely, 2022 had the highest precipitation, followed by 2021, and then 2020. (2) Lower temperatures and higher precipitation during the flowering to fruit growth stage contributed to a significant increase in macadamia nut yield, which indirectly extended the harvesting time. In 2022, the average yield of the eight macadamia growers was 8.04 t ha−1, significantly higher than the yields of 6.60 t ha−1 and 6.16 t ha−1 in 2021 and 2020, respectively. Furthermore, the average harvesting time for the eight macadamia growers in 2022 was 8.88 days longer than that in 2021, and 12.50 days longer than that in 2020. (3) Temperature and precipitation had a significant impact on the post-processing quality of macadamia nuts. Lower temperature and higher precipitation during the flowering to fruit growth stage significantly increased the proportion of first-grade fruit, as well as the incidence of mildewed and insect-infested fruits. In conclusion, although a lower temperature and higher precipitation can improve macadamia nut yield, they also lead to delayed harvesting and decreased post-processing quality. Given the observed yield sensitivity to temperature and precipitation, targeted water supplementation strategies during peak heat periods emerge as vital. This approach should be integrated with broader climate resilience planning, including the timing of pest control and disease management, to safeguard macadamia nut production against the multifaceted challenges posed by climate change.

Seasonal Dynamic of NO3− and K+ in a Citrus Crop Irrigated by Different Water Qualities

This study evaluated the effect of (i) irrigation water source: transfer (TW) and reclaimed water (RW), and (ii) crop phenological stage: winter rest (WR), flowering-sprouting (FS), and fruit growth (FG), on NO3− and K+ dynamics in soil and leaf of a citrus crop. The experiment was carried out during the 2018 and 2019 growing seasons on adult ‘Star Ruby’ grapefruit trees (Citrus paradisi Macf.). The concentration of both nutrients was periodically measured in soil and leaf samples and continuously monitored in the soil soluble fraction with nutrient sensors. Moreover, soil NO3− leaching was indirectly estimated by the periodic measurement of the leaf enrichment in 15N isotope (15Nleaf). The two water sources showed a different nutrient loading. Thus, NO3− and K+, were approximately 5 and 7 times higher, respectively, in the RW. Furthermore, the average contents of NO3− and K+ in the soil samples from the RW treatment were 10.1 and 19.7%, respectively, higher than in TW, with the highest soil NO3− leaching observed in RW treatment. In line with this, the mean contents of NO3− and K+ in the leaves from the RW treatment were 106.9 and 30.4% higher than the TW ones. As for the different phenological stages, in the FG stage, the lowest concentrations of NO3− in the soil samples and the highest in the leaf tissue were observed after a high soil leaching event. In this study the nutrient sensors measurements varied according to the dynamic of NO3− and K+ in the soil samples. The use of RW promoted an accumulation of NO3− and K+ in the soil and leaves of grapefruit trees, but also enhanced soil NO3− leaching, indicating that the proper management of this water source is necessary to avoid soil contamination. The mobilization of NO3− and K+ from soil to leaf was the highest in the FG stage, to ensure fruit development and vegetative growth.

Metabolites of blueberry roots at different developmental stages strongly shape microbial community structure and intra-kingdom interactions at the root-soil interface

The rhizosphere microorganisms of blueberry plants have long coexisted with their hosts under distinctively acidic soil conditions, exerting a profound influence on host performance through mutualistic symbiotic interactions. Meanwhile, plants can regulate rhizosphere microorganisms by exerting host effects to meet the functional requirements of plant growth and development. However, it remains unknown how the developmental stages of blueberry plants affect the structure, function, and interactions of the rhizosphere microbial communities. Here, we examined bacterial communities and root metabolites at three developmental stages (flower and leaf bud development stage, fruit growth and development stage, and fruit maturation stage) of blueberry plants. The results revealed that the Shannon and Chao 1 indices as well as community composition varied significantly across all three developmental stages. The relative abundance of Actinobacteria significantly increased by 10 % (p < 0.05) from stage 1 to stage 2, whereas that of Proteobacteria decreased significantly. The co-occurrence network analysis revealed a relatively complex network with 1179 edges and 365 nodes in the stage 2. Niche breadth was highest at stage 2, while niche overlap tended to increase as the plant developed. Furthermore, the untargeted metabolome analysis revealed that the number of differential metabolites of vitamins, nucleic acids, steroids, and lipids increased between stage 1 to stage2 and stage 2 to stage 3, while those for differential metabolites of carbohydrates and peptides decreased. Significant changes in expression levels of levan, L-glutamic acid, indoleacrylic acid, oleoside 11-methyl ester, threo-syringoylglycerol, gingerglycolipid B, and bovinic acid were highly correlated with the bacterial community structure. Collectively, our study reveals that significant alterations in dominant bacterial taxa are strongly correlated with the dynamics of root metabolites. These findings lay the groundwork for developing prebiotic products to enhance the beneficial effects of root microorganisms and boosting blueberry productivity via a sustainable approach.

Interacting effects of phytohormones and fruit pruning on the morpho-physiological and biochemical attributes of bell pepper

Several factors, such as pruning and phytohormones, have demonstrated an influence on both the quantity and quality in the bell pepper. A factorial experiment using a completely randomized design was conducted on the Lumos yellow bell in a greenhouse. Treatments were the fruit pruning (0, 10, and 30%) and foliar application of phytohormones auxin (AUX) and gibberellic acid (GA3) at concentrations of 10 µM AUX, 10 µM GA3, 10 µM AUX + 10 µM GA3+, and 20 µM AUX + 10 µM GA3 along with controls. The plants were sprayed with phytohormones in four growth stages (1: flowering stage when 50% of the flowers were on the plant, 2: fruiting stage when 50% of the fruits were the size of peas, 3: fruit growth stage when 50% of the fruits had reached 50% of their growth, and 4: ripening stage when 50% of the fruits were at color break). The results of the present investigation showed that pruning rate of 30% yielded the highest flesh thickness and vitamin C content, decreased seed count and hastened fruit ripening. The use of GA3 along with AUX has been observed to augment diverse fruit quality characteristics. According to the results, the application of 10% pruning in combination with 20 µM AUX and 10 µM GA3 demonstrated the most significant levels of carotenoids, chlorophyll, and fruit length. The experimental group subjected to the combined treatment of 30% pruning and 10 µM AUX + 10 µM GA3 showed the most noteworthy levels of vitamin C, fruit weight, and fruit thickness. The groups that received the 10 µM GA3 and 20 µM AUX + 10 µM GA3 treatments exhibited the most favorable fruit flavor. According to the research results, the implementation of hormonal treatments 10 µM AUX and 10 µM AUX + 10 µM GA3 in combination with a 30% pruning strategy resulted in the most advantageous yield of bell peppers.

Regulated Deficit Irrigation Perspectives for Water Efficiency in Apricot Cultivation: A Review

Addressing agricultural water scarcity poses a current challenge of growing concern, exacerbated by climate change. This is particularly relevant for stone fruit trees, such as apricot, cultivated in semi-arid zones, where regulated deficit irrigation (RDI) strategies are gaining attention to tackle the challenge. The RDI method involves optimizing various factors based on how the plant responds physiologically to indicators of its water needs. Among these indicators, water potential is considered the most reliable and influential measure. For numerous apricot varieties and diverse geographic locations, research consistently shows that implementing water reduction strategies during non-critical developmental stages of floral bud development or fruit growth does not significantly impact crop yield. However, it does lead to reduced vegetative growth, which could offer additional benefits in crop management. Furthermore, the implementation of RDI strategies leads to advantageous improvements in fruit quality, particularly storage capacity and morphometric and chemical fruit characteristics, such as total soluble solids content. This scoping review study suggests that RDI is a feasible strategy to address water scarcity in apricot cultivation; however, further studies focused on continuous water monitoring alternatives are necessary to optimize RDI techniques. Future research should prioritize optimizing RDI for different growth stages, exploring advanced technologies for precise implementation, and assessing environmental impacts, while addressing research gaps including the influence of climate variability and the interaction with other agronomic practices, to refine RDI strategies and enhance apricot orchard sustainability and productivity.

Production and economic viability of ‘Kent’ mango subjected to regulated deficit irrigation in the semi-arid

Mango (Mangifera indica L.) production has great importance for Brazilian agriculture, being concentrated in the states of Bahia and Pernambuco. Although mango is a drought-tolerant crop, inadequate irrigation management reduces its yield. Thus, the objective was to evaluate production parameters and economic viability of ‘Kent’ mango subjected to controlled water deficit in the phenological stages of flowering, fruit growth and maturation. The experiment was conducted in the municipality of Petrolina/PE, semi-arid region of the São Francisco Valley, in a ultisol. The experimental design was randomized blocks, in a triple factorial scheme, with application of four irrigation depths (40, 60, 80 and 100% of crop evapotranspiration - ETc), three phenological stages (F1 - flowering, F2 - fruit growth, F3 - fruit maturation) and two production cycles (2018 and 2019 seasons), with four replicates, each of which consisting of four plants. The irrigation with 40% ETc in the flowering stage and 80% of the ETc in the growing and ripening of fruits phases promoted higher yield, water use efficiency and benefit/cost ratio in the cultivation of ‘Kent’ mango in the Brazilian semi-arid region.

Analytical strategies to identify multicomponent quality markers for commercial Hua-ju-hong using multidimensional chemical analysis.

Hua-ju-hong (HJH) is a Chinese medicinal material obtained from Citrus grandis 'Tomentosa' (CGT) and Citrus grandis (L.) Osbeck (CG) with various commercial specifications. It is known for relieving cough and dispelling phlegm. To reveal the quality marker for distinguishing the various HJH, 215 batches of commercial HJH were studied systematically using multidimensional chemical analysis. Ten major components were identified by high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry and quantified via high-performance liquid chromatography coupled with diode array detection. In this study, a rapid, efficient, and low-cost chromatographic method was established. Total coumarin-hemiterpene and total coumarin-monoterpene were first classified and analyzed in HJH. The result indicated that the main component, naringin, was not the quality marker for differentiating CGT from CG. For reflecting the unique medicinal and food value of HJH, coumarins should be the more potential quality markers. Flavonoids were the possible quality markers for distinguishing two growth stages of fruit-exocarp and young fruit. For the first time, two chemotypes of HJH were identified in CG. This study provides a convenient yet reliant chromatographic method and novel yet systematic strategies for overall quality control of commercial HJH.

Enhancing precision of root-zone soil moisture content prediction in a kiwifruit orchard using UAV multi-spectral image features and ensemble learning

Accurate and real-time monitoring of soil moisture content (SMC) is of utmost importance for effective field irrigation and maximizing crop water productivity. However, a comprehensive investigation into the inversion study for determining suitable combinations of unmanned aerial vehicle (UAV) image features and enhancing the precision of SMC model prediction has yet to be fully validated within a kiwifruit orchard setting. This study addresses this gap by employing a pre-processing method and an optimal band combination algorithm to assess the impact of various combinations of kiwifruit canopy reflectance and fraction vegetation coverage (FVC) features on the sensitivity of root-zone SMC. Furthermore, an optimal ensemble learning (EL) framework was developed to monitor SMC at various root-zone depths (0–10 cm [SMC10], 0–20 cm [SMC20], 0–30 cm [SMC30], 0–40 cm [SMC40], 0–50 cm [SMC50], 0–60 cm [SMC60]). The key findings of this research highlight the successful derivation of 10 wavebands and FVC features, exhibiting a strong correlation with SMC at different root depths. The gradient boosting (GBDT) model demonstrated the exceptional accuracy in estimating SMC10, with an impressive R2 value of 0.963 ± 0.030 and low RMSE values of 0.238 ± 0.111. Similarly, the eXtreme Gradient Boosting (XGBoost) model outperformed in estimating SMC20 to SMC60, with R2 and RMSE values of 0.963 ± 0.024 and 0.117 ± 0.053, respectively. Additionally, the utilization of the optimal EL model allows for digital mapping of SMC at different depths across fruit growth stages, showcasing superior adaptability for SMC30 to SMC60 (with R2 and RMSE of 0.782 ± 0.090 and 0.037 ± 0.011) compared to SMC10 and SMC20 (with R2 and RMSE of 0.765 ± 0.097 and 0.056 ± 0.024). These results underscore the potential of the EL estimation framework in characterizing the spatial distribution of root-zone SMC at the individual kiwifruit plant level.

Fruit Morphological and Biochemical Characterization of Three Saudi Arabian Date Palm (Phoenix dactylifera L.) Cultivars Grown in District Khairpur, Pakistan

In the present study fruit morphological and biochemical characterization of three Saudi Arabian date palm cvs. (Ajwa, Safawi and Ruthana) were carried out, which were cultivated in the district Khairpur, Pakistan. Fruits were collected at four different fruit growth stages (kimri, khalal, rutab and tamar) from fifteen years old trees for morphological (fruit colour, fruit length, fruit diameter, fruit weight, pulp ratio, seed length, seed diameter, seed weight) and biochemical analyses (moisture content, pH, total soluble solids, total sugars, reducing sugars, non-reducing sugars). Results of fruits physical characters showed that significantly highest fruit length (5.5 cm at rutab stage), fruit weight (20.2 g at khalal stage) was observed in cv. Safawi, whereas at khalal stage significantly lowest fruit length (3.4 cm) was observed in cv. Ajwa and fruit weight (13.2 g) was observed in cv. Ruthana. Fruits showed significant variations in colour and weight from kimri to tamar stage. Biochemical analyses of fruits revealed that highest moisture content (86.2%) was observed in fruits of cv. Ruthana at kimri stage. Total soluble solids (TSS) increased from 8.7% (at kimri stage) to 20.5% (at tamar stage) in cv. Ruthana. pH of the fruits at kimri stage was 3.2 in cv. Ajwa, whereas pH increased to 5.2 in cv. Ruthana at tamar stage. Total sugars (reducing and non-reducing) increased from 7.56% in cv. Ajwa at kimri stage to 69.7% in cv. Safawi at tamar stage as significantly highest values. Findings obtained in the present study described morphological attributes and biochemical constituents of the fruits of three exotic cultivars introduced in climatic conditions of the district Khairpur, Pakistan will open the route and interest of the farmers to introduce other elite date cultivars grown in the world.

Physical, Chemical and Enzymatic Changes in Amla (Emblica officinalis) Fruit during Growth and Maturation.

Amla (Emblica officinalis) is one of the most prominent fruits in terms of nutritional and medicinal properties and is utilized for the preparation of many traditional processed foods and in Ayurvedic formulations. This study aims to investigate the enzyme activity and physical and chemical quality parameters during the growth and development stages of amla fruit for the determination of proper harvesting time to get optimum nutrient contents of fruit. The amla fruits of the chakaiya variety were harvested at 135 to 270 days after fruit set (DAFS) in 2021 and 2022 to study the various physical, chemical and enzymatic changes during growth and maturation. The geometrical and gravimetric attributes of the fruit, viz. diameter, height, weight, volume, surface area, sphericity, aspect ratio, and radius of curvature increased. However, density decreased with the growth and maturation of the fruit. Furthermore, the rolling resistance, yellowness index and firmness of the fruit increased during the entire harvesting period of 135 to 270 DAFS. Total soluble solids and titratable acidity of the fruits increased only up to 195 DAFS and after that, continuously decreased. In contrast, ascorbic acid concentration grew in the entire growth and development period. Tannic, phenolic compounds and naringin content of the fruit steadily dropped until the final stage of harvest. Pectin Methyl Esterase (PME) activity was detected very low, 0.009 unit/ml at 135 DAFS, but as the fruit grew and matured, activity increased to 0.307 unit/ml at 270 DAFS. Polygalactouronase (PG) activity was not detected until 210 DAFS and, thereforesignificantly increased with maturity. Considering the optimal value of all studied physical, chemical and enzymatic attributes of the fruit during the entire harvesting period of 135 to 270 DAFS, the optimal harvesting time of the fruit was 210 DAFS.

Revealing the structural changes of lignin in Chinese quince (Chaenomeles sinensis) fruit as it matures

Chinese quince fruits (Chaenomeles sinensis) contain substantial amounts of lignin; however, the exact structure of lignin remains to be investigated. In this study, milled wood lignins (Milled wood lignin (MWL)-1, MWL-2, MWL-3, MWL-4, MWL-5, and MWL-6) were extracted from fruits harvested once a month from May to October 2019 to investigate their structural evolution during fruit growth. The samples were characterized via High-performance anion exchange chromatography (HPAEC), Fourier transform–infrared spectroscopy (FT-IR), gel permeation chromatography (GPC), thermogravimetric (TGA), pyrolysis–gas chromatography/mass spectrometry (Py–GC/MS) and NMR (2D-heteronuclear single quantum coherence (HSQC) and 31P). The MWL samples in all fruit growth stages were GS-type lignin and lignin core undergoing minimal alterations during fruit development. The predominant linkage in the lignin structure was β-O-4′, followed by β-β' and β-5′. Galactose and glucose were the main monosaccharides associated with MWL. In MWL-6, the lignin exhibited the highest homogeneity and thermal stability. As the fruit matured, a gradual increase in the β-O-4′ proportion and the ratio of S/G was observed. The results provide comprehensive characterization of the cell wall lignin of quince fruit as it matures. This study could inspire innovative applications of quince fruit lignin and provide the optimal harvest time for lignin utilization.

Influence of plant growth regulators on fruit drop, fruit retention and fruit yield of mango (Mangifera indica l.) cv. Amrapali under west central table land zone of Odisha

Farmers in the western region of Odisha are grappling with issues related to low fruit set, fruit drop, and erratic yield in mango cultivation. Plant growth regulators (PGRs) play a pivotal role in addressing fruit drop at different developmental stages by modulating the nutritional and hormonal status of the plant. This study aims to investigate the impact of specific PGRs on fruit drop, fruit retention, and overall yield of Mango (Mangifera indica L.) cv. Amrapali in the West Central Table Land zone of Odisha. The experimental setup was implemented at the research plot of the College of Horticulture, Chiplima, Sambalpur, following a randomized block design with ten treatments, each replicated three times. The treatments involved various concentrations of three PGRs: NAA, GA3, and 2,4-D, applied during the pea and marble stages of fruit growth. The outcomes indicated that the application of 30 ppm GA3 significantly mitigated fruit drop, with comparable efficacy observed for 30 ppm 2,4-D. GA3 positively influenced fruit retention, particularly Treatment T7 (30 ppm GA3), exhibiting the highest retention percentages at 30, 60, and 90 days post-spraying. Furthermore, GA3 at 30 ppm resulted in the maximum average fruit weight and volume. The highest number of harvested fruits per plant and maximum yield per plant were recorded in Treatment T7. These findings underscore the potential of GA3 in alleviating fruit drop, enhancing fruit retention, and improving overall yield in mango cultivation, specifically for the Amrapali variety in the West Central Table Land Zone of Odisha.

Vegetative and Reproductive Responses Induced by Organo-Mineral Fertilizers on Young Trees of Almond cv. Tuono Grown in a Medium-High Density Plantation

Field experiments were conducted in three successive seasons (2019–2021) to evaluate the effects of four commercial organo-mineral fertilizers with biostimulating action (Hendophyt®, Ergostim®, and Radicon®) on the vegetative and productive performance of young almond trees (Prunus dulcis, cv. Tuono) grown in a semiarid climate in Southern Italy. Foliar treatments were applied three times during each season (at the swollen bud, beginning of flowering, and fruit set-beginning of fruit growth stages). Both 2020 and 2021 were adversely affected by late frosts, resulting in damage to the flowers and small fruits without any positive effect of the biostimulant applications. In contrast, the results obtained during the normal climate year (2019) indicated that the growth of trunk diameter and shoot length of trees tended to increase in biostimulant treatments compared to those of the control. The number of buds and flowers per unit length of the branch revealed no significant differences among years and all compared treatments. However, in 2019, the fruit set percentage, number, and weight of kernels per tree were significantly higher in the biostimulant treatments compared to those of the control. To this regard, the use of biofertilizers is suitable for maintaining soil fertility and improving crop productivity This information holds significance for almond tree growers.

Testing effects of vapor pressure deficit on fruit growth: a comparative approach using peach, mango, olive, orange, and loquat.

Determining the influence of vapor pressure deficit (VPD) on fruit growth is a key issue under a changing climate scenario. Using a comparative approach across different fruit tree species may provide solid indications of common or contrasting plant responses to environmental factors. Knowing fruit growth responses to VPD may also be useful to optimize horticultural management practices under specific atmospheric conditions. Climate data to calculate VPD and fruit relative growth rates (RGR) by fruit gauges were monitored in peach at cell division, pit hardening and cell expansion stages; in two mango cultivars at cell division, cell expansion and maturation stages; in two olive cultivars, either full irrigated or rainfed, at early and late cell expansion stages; in 'Valencia' orange at early and late cell division stage, before and after mature fruit harvest; in loquat at cell expansion and maturation stages. At the fruit cell division stage, sensitivity of fruit growth to VPD seems to vary with species, time, and probably soil and atmospheric water deficit. 'Keitt' mango and 'Valencia' orange fruit growth responded to VPD in opposite ways, and this could be due to very different time of the year and VPD levels in the monitoring periods of the two species. At pit hardening stage of peach fruit growth, a relatively weak relationship was observed between VPD and RGR, and this is not surprising as fruit growth in size at this stage slows down significantly. A consistent and marked negative relationship between VPD and RGR was observed at cell expansion stage, when fruit growth is directly depending on water intake driving cell turgor. Another behavior common to all observed species was the gradual loss of relationship between VPD and RGR at the onset of fruit maturation, when fruit growth in size is generally programmed to stop. Finally, regardless of fruit type, VPD may have a significant effect on fruit growth and could be a useful parameter to be monitored for tree water management mainly when the cell expansion process prevails during fruit growth.

Development of Tomato Fruit Stage Index (TFSI) to characterise different fruit growth stages of tomato using multivariate techniques

Development of Tomato Fruit Stage Index (TFSI) to characterise different fruit growth stages of tomato using multivariate techniques

Effect of deficit irrigation and mulching on the agronomic and physiological response of mandarin trees as strategies to cope with water scarcity in a semi-arid climate

In order to increase the crop water productivity (WPc) of the agricultural systems, and to support farmers in minimizing uncertainty of water availability, we conducted a three-years experiment in a commercial adult mandarin orchard to quantify the effect of sustained and severe deficit irrigation in combination with the use of geotextile mulch on the agronomic and physiological response of the crop. For this purpose, five treatments were tested: (i) a control (CTL) irrigated at 100% of the crop evapotranspiration (ETc) during the entire season; ii) sustained deficit irrigation (SDI), irrigated at ∼70% of CTL; (iii) regulated deficit irrigation (RDI), irrigated as SDI, except during the initial period of the second fruit growth stage, when trees were irrigated at 35% of the CTL, maintaining a moderate water stress level of around –1.5 MPa of stem water potential (Ψs), until fruits reached 70% of their final size. In addition, two geotextile mulch treatments were established, using the same irrigation criteria as the SDI and RDI treatments. The available irrigation water supplied about 66% of the crop evapotranspiration, but if it is managed under a SDI regime with the incorporation of mulching it is possible to increase the crop sustainability and reduce the pressure over the water resources. Since SDI did not reduce the yield with respect to the CTL treatment, it increased WPc by 35% and the incorporation of mulch significantly increased the water status of the soil and the crop, thus reducing the intensity of water stress by 18% on average, which was expressed in a higher leaf gas exchange rate and was also a factor that significantly increased crop production variables and WPc.

Transcriptome Insights into Candidate Genes of the SWEET Family and Carotenoid Biosynthesis during Fruit Growth and Development in Prunus salicina 'Huangguan'.

The Chinese plum (Prunus salicina L.) is a fruit tree belonging to the Rosaceae family, native to south-eastern China and widely cultivated throughout the world. Fruit sugar metabolism and color change is an important physiological behavior that directly determines flavor and aroma. Our study analyzed six stages of fruit growth and development using RNA-seq, yielding a total of 14,973 DEGs, and further evaluation of key DEGs revealed a focus on sugar metabolism, flavonoid biosynthesis, carotenoid biosynthesis, and photosynthesis. Using GO and KEGG to enrich differential genes in the pathway, we selected 107 differential genes and obtained 49 significant differential genes related to glucose metabolism. The results of the correlation analyses indicated that two genes of the SWEET family, evm.TU.Chr1.3663 (PsSWEET9) and evm.TU.Chr4.676 (PsSWEET2), could be closely related to the composition of soluble sugars, which was also confirmed in the ethylene treatment experiments. In addition, analysis of the TOP 20 pathways between different growth stages and the green stage, as well as transient overexpression in chili, suggested that capsanthin/capsorubin synthase (PsCCS) of the carotenoid biosynthetic pathway contributed to the color change of plum fruit. These findings provide an insight into the molecular mechanisms involved in the ripening and color change of plum fruit.

Determination of Phytochemical Contents in Extracts from Different Growth Stages of Oroxylum indicum Fruits Using HPLC-DAD and QAMS Methods.

Flavones are major compounds found in several parts of Oroxylum indicum (O. indicum). The quantification of multiple components by one marker (QAMS) method and the high-performance liquid chromatography (HPLC) method were developed for the quantitative analysis of extracts from the young fruits, green mature fruits, dry pod coats and seeds of O. indicum. Oroxin A, oroxin B and chrysin-7-O-glucuronide were identified in the O. indicum extracts. Oroxylin A and 5-hydroxymethylfurfural were isolated and structurally identified from the pod coat and young fruit extracts, respectively. From the HPLC analysis of the seven major flavones in the extracts, baicalin was the major compound in all extracts investigated (0.4-11% w/w of the extract). All flavone contents were low in the young fruit extract (<1% w/w of the extract). The green mature fruit and dry pod coat extracts showed similar constituent compositions. They contained small amounts of baicalin and oroxylin A, which were found only in these two extracts. Oroxylin A could be used as a marker to indicate the maturity of O. indicum fruits, while 5-hydroxymethylfurfural could be used as a marker for the young fruits. Baicalin was found to be a suitable single marker to calculate the contents of all flavones in the O. indicum extracts.

Grading of Pomegranate Fruit using CNN

Farmers require an automated system to grade Pomegranate fruits rather than a manual system to increase productivity and quality of Pomegranate fruits. Manual grading of fruits does not produce adequate results and requires additional time for disease identification and gradation, as well as the expertise of an expert, making it ineffective. The suggested system is an efficient module that identifies various pomegranate fruit disorders and determines the stage of sickness. Effective growth stage monitoring and disease detection are critical for maximising pomegranate fruit yield and quality. This paper describes a method for monitoring the growth stages of pomegranate fruit utilising image processing techniques and disease detection approaches based on machine learning algorithms. The suggested method analyses colour, shape, and texture information taken from photos captured at various phases of development to track the growth stages of pomegranate fruit. The obtained data is then utilised to train machine learning models that appropriately distinguish the growth stages. The models are trained on a dataset of annotated photos containing numerous pomegranate fruit illnesses. Farmers and agricultural specialists can use the developed technology to correctly monitor the growing phases of pomegranate fruit and detect problems. The camera in this project catches various pomegranate fruit stages and classifies pomegranate fruits into two classes: infected and non-infected, using a machine learning algorithm and Python tools. This study employs a CNN, K-mean method, and image processing technique to detect illnesses at various phases of fruit development.

Label-free Raman microspectroscopic imaging with chemometrics for cellular investigation of apple ring rot and nondestructive early recognition using near-infrared reflection spectroscopy with machine learning

Apple ring rot caused by Botryosphaeria dothidea can cause fruit decay during the growth and storage stages of apple fruit. Understanding the infection process and cellular defense response at the cellular micro-level holds immense importance in the field of prevention and control. Consequently, there is a pressing need to develop suitable chemical imaging analysis methods. Here we proposed a label-free, high-throughput imaging method for cellular investigation of apple fruit ring rot infected by Botryosphaeria dothidea, based on confocal Raman microspectroscopic imaging technology combined with multivariate curve resolution-alternating least squares algorithm (MCR-ALS). We conducted Raman measurements on every apple fruit and obtain an image cube. This cube was then unfolded into an augmented matrix in a column-wise manner. We proceeded with simultaneous MCR-ALS analysis, resolving the single-substance spectrum and concentration profile from the mixed signals. Lastly, the accurate and pure molecular imaging of low methoxyl pectin, high methoxyl pectin, cellulose, lignin, and phenols were realized by refolding the resolved concentration data to construct the composition image. Thereafter, we realized the study of the spatial-temporal changes distribution of the above substances in the cuticle and cell wall of green and red apples at different stages of infection. The imaging method proposed in this paper is expected to provide a chemical imaging strategy for studying pathogen infection process and fruit defense response at the cellular level. In addition, by utilizing a fiber-optic probe near-infrared reflection spectrometer in conjunction with machine learning, we developed a rapid and non-destructive classification method. This method allows for the timely identification of apples exhibiting early infection by Botryosphaeria dothidea. Notably, both principal component analysis-quadratic discriminant analysis and support vector machine achieved a classification accuracy of 100%.