Determination of fruit maturity and its prediction model based on the pericarp index of absorbance difference (IAD) for peaches

Effect of Potassium Permanganate, Ultraviolet Radiation and Titanium Oxide as Ethylene Scavengers on Preservation of Postharvest Quality and Sensory Attributes of Broccoli Stored with Tomatoes

This study introduces an effective solution to enhance the postharvest preservation of broccoli, a vegetable highly sensitive to ethylene, a hormone produced by climacteric fruits such as tomatoes. The proposed method involves a triple combination of ethylene elimination techniques: potassium permanganate (KMnO₄) filters combined with ultraviolet radiation (UV-C) and titanium oxide (TiO₂), along with a continuous airflow to facilitate contact between ethylene and these oxidizing agents. The effectiveness of this approach was evaluated using various analytical techniques, including measurements of weight, soluble solids content, total acidity, maturity index, color, chlorophyll, total phenolic compounds, and sensory analysis conducted by experts. The results demonstrated a significant improvement in the physicochemical quality of postharvest broccoli when treated with the complete system. Notably, broccoli subjected to this innovative method exhibited enhanced organoleptic quality, with heightened flavors and aromas associated with fresh green produce. The implementation of this novel technique holds great potential for the food industry as it reduces postharvest losses, extends the shelf life of broccoli, and ultimately enhances product quality while minimizing waste. The successful development and implementation of this new technique can significantly improve the sustainability of the food industry while ensuring the provision of high-quality food to consumers.

Effects of Harvest Maturity on the Fruit Quality of Different Flesh-Type Peach Stored at Near-Freezing Point Temperature

To investigate the peach fruit flesh types (soft-melting, hard-melting, stonyhard and non-melting) and harvest maturity level suitable for near-freezing temperature storage (NFTS), eight peach cultivars that had four flesh types were used as test materials. Changes in fruit respiration intensity and ethylene release rates, as well as the differences in quality indexes, such as soluble solids content (SSC), firmness, color difference, pigment content, soluble sugar and organic acid component content, of three fruit maturity levels (70%, 80% and 90% maturity) under NFTS conditions were analyzed and compared. The fruit quality indexes of peach having different maturity levels and flesh types changed little during NFTS. The SSC and total sugar content of hard-melting and stonyhard peach fruit were higher than those of other flesh types during NFTS. Those fruit maintained greater firmness at the end of the storage period. The differences in respiration intensity and ethylene release rate were small, but for fruit coloring, hard-melting fruit performed better than stonyhard fruit. The 80%, compared with the 90%, maturity stage maintained more fruit moisture, had less fruit mass loss and maintained a greater edible firmness. It effectively impeded the fruit senescence process and was the most suitable maturity for NFTS. Thus, the hard-melting peach maintained the highest commercial value and desirable storage characteristics under NFTS conditions, and its 80% maturity level was the most suitable for NFTS.

A Fruit Colour Development Index (CDI) to Support Harvest Time Decisions in Peach and Nectarine Orchards

Fruit skin colour is one of the most important visual fruit quality parameters driving consumer preferences. Proximal sensors such as machine vision cameras can be used to detect skin colour in fruit visible in collected images, but their accuracy in variable orchard light conditions remains a practical challenge. This work aimed to derive a new fruit skin colour attribute—namely a Colour Development Index (CDI), ranging from 0 to 1, that intuitively increases as fruit becomes redder—to assess colour development in peach and nectarine fruit skin. CDI measurements were generated from high-resolution images collected on both east and west sides of the canopies of three peach and one nectarine cultivars using the commercial mobile platform Cartographer (Green Atlas). Fruit colour (RGB values) was extracted from the central pixels of detected fruit and converted into a CDI. The repeatability of CDI measurements under different light environments was tested by scanning orchards at different times of the day. The effects of cultivar and canopy side on CDI were also determined. CDI data was related to the index of absorbance difference (IAD)—an index of chlorophyll degradation that was correlated with ethylene emission—and its response to time from harvest was modelled. The CDI was only significantly altered when measurements were taken in the middle of the morning or in the middle of the afternoon, when the presence of the sun in the image caused significant alteration of the image brightness. The CDI was tightly related to IAD, and CDI values plateaued (0.833 ± 0.009) at IAD ≤ 1.20 (climacteric onset) in ‘Majestic Pearl’ nectarine, suggesting that CDI thresholds show potential to be used for harvest time decisions and to support logistics. In order to obtain comparable CDI datasets to study colour development or forecast harvest time, it is recommended to scan peach and nectarine orchards at night, in the early morning, solar noon, or late afternoon. This study found that the CDI can serve as a standardised and objective skin colour index for peaches and nectarines.

Phenotyping Brown Rot Susceptibility in Stone Fruit: A Literature Review with Emphasis on Peach

Plant disease phenotyping methodologies can vary considerably among testers and often suffer from shortcomings in their procedures and applications. This has been an important challenge in resistance breeding to brown rot, one of the most severe pre-and postharvest stone fruit diseases caused by Monilinia spp. Literature about methodologies for evaluating stone fruit susceptibility to brown rot is abundant but displays significant variations across the described approaches, limiting the ability to compare results from different studies. This is despite the fact that authors largely agree on the main factors influencing brown rot development, such as Monilinia inocula, environmental conditions, cultivars, fruit stage, and management practices. The present review first discusses ways to control or at least account for major factors affecting brown rot phenotyping studies. The second section describes in detail the different steps of fruit infection assays, comparing different protocols available in the literature with the objective of highlighting best practices and further improvement of phenotyping for brown rot susceptibility. Finally, experimental results from multi-year evaluation trials are also reported, highlighting year-to-year variability and exploring correlations of evaluation outcomes among years and assay types, suggesting that choice of phenotyping methodology must be carefully considered in breeding programs.

Site-directed mutagenesis identified the key active site residues of alcohol acyltransferase PpAAT1 responsible for aroma biosynthesis in peach fruits

The aroma of peach fruit is predominantly determined by the accumulation of γ-decalactone and ester compounds. A previous study showed that the biosynthesis of these aroma compounds in peach fruit is catalyzed by PpAAT1, an alcohol acyltransferase. In this work, we investigated the key active site residues responsible for γ-decalactone and ester biosynthesis. A total of 14 candidate amino acid residues possibly involved in internal esterification and 9 candidate amino acid residues possibly involved in esterification of PpAAT1 were assessed via site-directed mutagenesis. Analyses of the in vitro enzyme activities of PpAAT1 and its site-directed mutant proteins (PpAAT1-SMs) with different amino acid residue mutations as well as the contents of γ-decalactone in transgenic tobacco leaves and peach fruits transiently expressing PpAAT1 and PpAAT1-SMs revealed that site-directed mutation of H165 in the conserved HxxxD motif led to lost enzymatic activity of PpAAT1 in both internal esterification and its reactions, whereas mutation of the key amino acid residue D376 led to the total loss of γ-decalactone biosynthesis activity of PpAAT1. Mutations of 9 and 7 other amino acid residues also dramatically affected the enzymatic activity of PpAAT1 in the internal esterification and esterification reactions, respectively. Our findings provide a biochemical foundation for the mechanical biosynthesis of γ-decalactone and ester compounds catalyzed by PpAAT1 in peach fruits, which could be used to guide the molecular breeding of new peach species with more favorable aromas for consumers.

A Novel Greenhouse-Based System for the Detection and Plumpness Assessment of Strawberry Using an Improved Deep Learning Technique

The automated harvesting of strawberry brings benefits such as reduced labor costs, sustainability, increased productivity, less waste, and improved use of natural resources. The accurate detection of strawberries in a greenhouse can be used to assist in the effective recognition and location of strawberries for the process of strawberry collection. Furthermore, being able to detect and characterize strawberries based on field images is an essential component in the breeding pipeline for the selection of high-yield varieties. The existing manual examination method is error-prone and time-consuming, which makes mechanized harvesting difficult. In this work, we propose a robust architecture, named "improved Faster-RCNN," to detect strawberries in ground-level RGB images captured by a self-developed "Large Scene Camera System." The purpose of this research is to develop a fully automatic detection and plumpness grading system for living plants in field conditions which does not require any prior information about targets. The experimental results show that the proposed method obtained an average fruit extraction accuracy of more than 86%, which is higher than that obtained using three other methods. This demonstrates that image processing combined with the introduced novel deep learning architecture is highly feasible for counting the number of, and identifying the quality of, strawberries from ground-level images. Additionally, this work shows that deep learning techniques can serve as invaluable tools in larger field investigation frameworks, specifically for applications involving plant phenotyping.

Differences in PpAAT1 Activity in High- and Low-Aroma Peach Varieties Affect γ-Decalactone Production

Aroma contributes to the unique flavors of fruits and is important for fruit quality evaluation. Among the many volatiles in peach (Prunus persica) fruits, γ-decalactone has the greatest contribution to the characteristic peach aroma. Some peach cultivars have γ-decalactone contents that are too low to detect. Comparison of the transcriptomes and metabolomes of a high-aroma cultivar, Fenghuayulu, and a low-aroma cultivar, Achutao, suggested that amino acid substitutions in ALCOHOL ACYLTRANSFERASE (PpAAT1) are responsible for the undetectable levels of γ-decalactone in cv Achutao fruit. Modeling and molecular docking analysis of PpAAT1 indicated that the substituted residues might determine substrate recognition or act as control channels to the active site. In vitro enzyme assays on PpAAT1 heterologously expressed and purified from Escherichia coli and in vivo assays using transient PpAAT1 expression in Nicotiana benthamiana or the oleaginous yeast Yarrowia lipolytica indicated that PpAAT1 from high-aroma cultivars was more efficient than PpAAT1 from low-aroma cultivars in catalyzing the conversion of 4-hydroxydecanoyl-coenzyme A into γ-decalactone. Examination of loss-of-function mutations of PpAAT1 generated by CRISPR/Cas9 in cv Fenghuayulu showed that fruits with PpAAT1 mutations had significantly lower γ-decalactone contents. Expression of the version of PpAAT1 from cv Fenghuayulu in cv Achutao restored γ-decalactone levels to those measured in 'Fenghuayulu', confirming the specific contribution of PpAAT1 to the formation of this key aroma compound. These results show how the biosynthesis of the peach aroma compound γ-decalactone is compromised in some low-aroma cultivars and illustrate the physiological role of PpAAT1 in plant lactone biosynthesis.

Expression QTL (eQTLs) Analyses Reveal Candidate Genes Associated With Fruit Flesh Softening Rate in Peach [Prunus persica (L.) Batsch]

Significant differences in softening rate have been reported between melting flesh in peach and nectarine varieties. This trait seems to be controlled by several genes. We aimed to identify candidate genes involved in fruit softening rate by integrating quantitative trait loci (QTL) and expression QTL (eQTL) analyses, comparing siblings with contrasting softening rates. We used a segregating population derived from nectarine cv. 'Venus' selfing, which was phenotyped for softening rate during three seasons. Six siblings with high (HSR) and six with low softening rate (LSR) were sequenced using RNA-Seq. A group of 5,041 differentially expressed genes was identified. Also, we found a QTL with a LOD (logarithm of odds) score of 9.7 on LG4 in all analyzed seasons. Furthermore, we detected 1,062 eQTLs, of which 133 were found co-localizing with the identified QTL. Gene Ontology (GO) analysis showed 'Response to auxin' as one the main over-represented categories. Our findings suggest over-expression of auxin biosynthetic related genes in the HSR group, which implies a higher expression and/or accumulation of auxin, thereby triggering fast softening. Conversely, the LSR phenotype might be explained by an altered auxin-homeostasis associated with low auxin levels. This work will contribute to unraveling the genetic mechanisms responsible for the softening rate in peaches and nectarines and lead to the development of molecular markers.