Postharvest Stage Research Articles

A review of machine learning applications in Cacao Post-harvest management

Cacao beans play a crucial role in chocolate production, making them a highly relevant crop. The post-harvesting stage of cacao beans, encompassing classification, quality assessment, and fermentation, holds significant importance. With the increasing demand for marketable cacao beans, the need for reliable, accurate, and fast technologies has emerged. This study provides a comprehensive review of machine learning techniques in the post-harvesting stage of cacao beans from 2016 to the present. Analyzing 36 studies, it focuses on classification, quality assessment, and fermentation. The proposed framework includes the application domain, learning algorithms, performance metrics, and reported impacts. Notably, it explores various machine learning applications like classification, quality assessment, and fermentation, highlighting commonly used algorithms like ANN, CNN, and SVM. In terms of performance metrics, GLCM achieved the highest accuracy (99.61%) in cacao classification, ANFIS excelled in quality assessment (99.715%), and k-NN emerged as the most accurate for fermentation. This review serves as a valuable resource for researchers in the cacao bean sector, offering insights into machine learning advancements.

The Effect of Rhizospheric Fungal Species of Tomato (Solanum lycopersicum L.), on In-Vitro Growth of the Tomato Early Blight Pathogen

Tomato (Solanum lycopersicum L.) is a globally consumed crop, susceptible to various biotic and abiotic stresses. Among biotic stresses, plant diseases, particularly Early Blight caused by Alternaria spp. leads to heavy losses in the field and post-harvest stages. The conventional use of synthetic agrochemicals to control these diseases poses environmental risks, underscoring the need for sustainable alternatives. Hence, this study aimed to assess the potential of rhizospheric fungi in controlling Alternaria spp. Infected tomato leaves, stem parts, and fruits were collected from commercial cultivations in four agro-ecological regions in Sri Lanka (two from mid-country in the wet zone, and two from the intermediate zone). All samples were washed using running tap water, and 1cm2 sections, including the edges of lesions, were cut, surface sterilized, placed on potato dextrose agar (PDA), and incubated at room temperature until colonies appeared. Fungal colonies that emerged from lesions, were sub-cultured onto fresh PDA, and pure cultures were obtained using the hyphal-tip purification method. Alternaria isolates were identified morphologically and confirmed the pathogenicity by Koch’s postulate method. Species-level identification involved genomic DNA extraction and sequencing ITS regions. The soil dilution plate technique was used to isolate rhizospheric fungi from two agroecological regions. Composite samples (10 g) of soil attached to the roots of 5 uprooted healthy plants, from each field were used. Soil suspensions were inoculated onto PDA using the spread-plate method and incubated at room temperature for 5 days. A total of 27 isolates were obtained and morphologically identified up to the genus level after preparing pure cultures. The dual-culture plate technique was used to assay percentage inhibition, and according to Tukey’s pairwise comparison, Trichoderma sp. and Purpureocillium lilacinum exhibited significantly high (p≤0.05) inhibition of Alternaria colony growth, (68.25±1.18% and 64.35±3.31% respectively). Microscopic observations of inhibition zones between Alternaria and antagonistic rhizospheric fungal colonies, including Trichoderma sp. and P. lilacinum showed the presence of mycoparasitism-related structures, such as haustoria, coils, loops, and knobs. Qualitative assay for fungal chitinase enzyme production demonstrated high activities in P. lilacinum, Trichoderma sp. and Acremonium sp., whereas in a quantitative assay for fungal glucanase enzyme, testing the ability of fungal culture filtrates to release 1µg of glucose per minute, from Beta-glucanase solution, P. lilacinum, Trichoderma sp., and Paecilomyces sp. showed significantly high (p≤0.05) activities (105.14± 3.62, 100.11±4.09 and 99.83 ±6.44 μg glucose/L respectively). In conclusion, this study highlights the potential of rhizospheric fungi like P. lilacinum and Trichoderma sp. as effective biocontrol agents against Alternaria spp. and these findings lay the groundwork for future applications in enhancing tomato crop resilience against pathogens and promoting sustainable and eco-friendly agricultural practices.
 
 Keywords: Rhizospheric fungi, Mycoparasitism, ITS region, Chitinase enzyme, Glucanase enzyme

Tissue-specific proteome profile analysis reveals regulatory and stress responsive networks in passion fruit during storage

Passiflora edulis, commonly known as passion fruit, is a crop with a fragrant aroma and refreshingly tropical flavor that is a valuable source of antioxidants. It offers a unique opportunity for growers because of its adaptability to tropical and subtropical climates. Passion fruit can be sold in the fresh market or used in value-added products, but its postharvest shelf life has not been well-researched, nor have superior cultivars been well-developed. Understanding the proteins expressed at the tissue level during the postharvest stage can help improve fruit quality and extend shelf life. In this study, we carried out comparative proteomics analysis on four passion fruit tissues, the epicarp, mesocarp, endocarp, and pulp, using multiplexed isobaric tandem mass tag (TMT) labeling quantitation. A total of 3352 proteins were identified, including 295 differentially expressed proteins (DEPs). Of these DEPs, 213 showed a fold increase greater than 1.45 (50 proteins) or a fold decrease less than 0.45 (163 proteins) with different patterns among tissue types. Among the DEPs, there were proteins expressed with functions in oxygen scavenging, lipid peroxidation, response to heat stress, and pathogen resistance. Thirty-six proteins were designated as hypothetical proteins were characterized for potential functions in immunity, cell structure, homeostasis, stress response, protein metabolism and miraculin biosynthesis. This research provides insight into tissue-specific pathways that can be further studied within fruit physiology and postharvest shelf life to aid in implementing effective plant breeding programs. Knowing the tissue-specific function of fruit is essential for improving fruit quality, developing new varieties, identifying health benefits, and optimizing processing techniques.

The Influence of Long-Term Storage on the Epiphytic Microbiome of Postharvest Apples and on Penicillium expansum Occurrence and Patulin Accumulation.

Patulin is a secondary metabolite primarily synthesized by the fungus Penicillium expansum, which is responsible for blue mold disease on apples. The latter are highly susceptible to fungal infection in the postharvest stages. Apples destined to produce compotes are processed throughout the year, which implies that long periods of storage are required under controlled atmospheres. P. expansum is capable of infecting apples throughout the whole process, and patulin can be detected in the end-product. In the present study, 455 apples (organically and conventionally grown), destined to produce compotes, of the variety "Golden Delicious" were sampled at multiple postharvest steps. The apple samples were analyzed for their patulin content and P. expansum was quantified using real-time PCR. The patulin results showed no significant differences between the two cultivation techniques; however, two critical control points were identified: the long-term storage and the deck storage of apples at ambient temperature before transport. Additionally, alterations in the epiphytic microbiota of both fungi and bacteria throughout various steps were investigated through the application of a metabarcoding approach. The alpha and beta diversity analysis highlighted the effect of long-term storage, causing an increase in the bacterial and fungal diversity on apples, and showed significant differences in the microbial communities during the different postharvest steps. The different network analyses demonstrated intra-species relationships. Multiple pairs of fungal and bacterial competitive relationships were observed. Positive interactions were also observed between P. expansum and multiple fungal and bacterial species. These network analyses provide a basis for further fungal and bacterial interaction analyses for fruit disease biocontrol.

Biosensor in smart food traceability system for food safety and security

ABSTRACT The burden of food contamination and food wastage has significantly contributed to the increased prevalence of foodborne disease and food insecurity all over the world. Due to this, there is an urgent need to develop a smarter food traceability system. Recent advancements in biosensors that are easy-to-use, rapid yet selective, sensitive, and cost-effective have shown great promise to meet the critical demand for onsite and immediate diagnosis and treatment of food safety and quality control (i.e. point-of-care technology). This review article focuses on the recent development of different biosensors for food safety and quality monitoring. In general, the application of biosensors in agriculture (i.e. pre-harvest stage) for early detection and routine control of plant infections or stress is discussed. Afterward, a more detailed advancement of biosensors in the past five years within the food supply chain (i.e. post-harvest stage) to detect different types of food contaminants and smart food packaging is highlighted. A section that discusses perspectives for the development of biosensors in the future is also mentioned.

Identification and application of an exocarp-preferential promoter for genetic engineering of tomato fruit.

Tomato (Solanum lycopersicum) is a globally cultivated crop with great economic value. The exocarp determines the appearance of tomato fruit and protects it from various biotic and abiotic challenges at both pre-harvest and post-harvest stages. However, no tomato exocarp-specific promoter is currently available, which hinders exocarp-based genetic engineering. Here, we identified by RNA sequencing and reverse transcription-quantitative PCR analyses that the tomato gene SlPR10 (PATHOGENESIS RELATED 10) was abundantly and predominantly expressed in the exocarp. A fluorescent reporter expressed by a 2087-bp SlPR10 promoter (pSlPR10) was mainly detected in the exocarp of transgenic tomato plants of both Ailsa Craig and Micro-Tom cultivars. This promoter was further utilized for transgenic expression of SlANT1 and SlMYB31 in tomato, which are master regulators of anthocyanin and cuticular wax biosynthesis, respectively. pSlPR10-driven SlANT1 expression resulted in anthocyanin accumulation in the exocarp, conferring gray mold resistance and extended shelf life to the fruit, while SlMYB31 expression led to waxy thickening in the fruit skin, delaying water loss and also extending fruit shelf life. Intriguingly, pSlPR10 and two other weaker tomato exocarp-preferential promoters exhibited coincided expression specificities in the gynophore of transgenic Arabidopsis (Arabidopsis thaliana) plants, providing not only an inkling of evolutionary homology between tomato exocarp and Arabidopsis gynophore but also useful promoters for studying gynophore biology in Arabidopsis. Collectively, this work reports a desirable promoter enabling targeted gene expression in tomato exocarp and Arabidopsis gynophore and demonstrates its usefulness in genetic improvement of tomato fruit quality.

Integrating meta-analysis with a quantitative microbial risk assessment model to investigate Campylobacter contamination of broiler carcasses

This study investigated the prevalence and associated risk factors of Campylobacter in South Korean broilers using a random-effects meta-analysis. Subsequently, to facilitate the design of preventive measures, the prevalence estimate from the meta-analysis was incorporated into a stochastic risk assessment model to quantify the Campylobacter contamination levels on broiler carcasses. The baseline model was developed based on the most common practices along the South Korean broiler processing line, with no interventions. Meta-analysis results revealed Campylobacter prevalence across the chicken supply chain in the following order: farms (60.6 % [57.3–63.4]), retail markets (43.90 % [24.81–64.99]), slaughterhouses (27.71 % [18.56–39.21]), and processing plants (14.50 % [3.96–41.09]). The model estimated a 52 % (36.1–70.8) Campylobacter prevalence at the end of chilling, with an average contamination level of 4.62 (2.50–6.74) log CFU/carcass. Sensitivity analysis indicated that Campylobacter fecal shedding (r = 0.95) and the amount of feces on bird exteriors (r = 0.17) at pre-harvest were the main factors for carcass contamination, while soft scalding (r = -0.22) and air chilling (r = -0.12) can serve as critical control points (CCPs) at harvest. Scenario analysis indicated that a combination of hard scalding, inside-outside bird washing, spray washing, and chlorinated water immersion chilling can offer a 30.9 % reduction in prevalence and a reduction of 2.23 log CFU/carcass in contamination levels compared to the baseline model. Apart from disinfection and sanitation interventions carried out during meat processing, the implementation of robust control measures is indispensable to mitigate Campylobacter prevalence and concentration at broiler farms, thereby enhancing meat safety and public health. Furthermore, given the high Campylobacter prevalence in the retail markets, future studies should explore the potential risk of cross-contamination at post-harvest stage.

Non-destructive detection of fusarium head blight in wheat kernels and flour using visible near-infrared and mid-infrared spectroscopy

Fusarium head blight (FHB) is one of the most severe fungal diseases that reduces yield of cereal crops and degrades kernel quality with mycotoxins, which are harmful to human and animal health. The majority of FHB identification at post-harvest stage is through lab-based analysis, whilst effective it is a time consuming, expensive, and laborious process. Hence, a non-destructive, rapid, accurate, and robust method is required for FHB detection at post-harvest. This study explores the potential of visible near-infrared (vis-NIR) in the wavelength range from 400 to 1700 nm and the mid-infrared (MIR) in the wavenumber range from 4000 to 650 cm−1 to predict FHB infection of wheat kernels and flour. A total of 143 ear samples (93 infected, and 50 healthy) were collected from an inoculated trial covering several winter wheat varieties. The collected spectral data was analysed with two different machine learning algorithms, namely, random forest (RF) and linear discriminant analysis (LDA). Both models produced a higher test accuracy of 96.6 % and 100 %, respectively, for the flour samples than that (e.g., 93.1 %) for the kernels, using the MIR spectroscopy. Recursive feature elimination (RFE) demonstrated notable improvements in accuracy of the vis-NIR for the kernels, with LDA model providing 100 % classification accuracy. While RFE failed to improve the accuracy of MIR-LDA models. The results highlight the effectiveness of vis-NIR and MIR spectroscopy with RFE and machine learning for classifying FHB in wheat kernel and flour samples.

Characteristics of famoxadone-resistant mutants of Phytophthora litchii and their effect on lychee fruit quality

Lychee downy blight (LDB), a common disease caused by the oomycete Phytophthora litchii, poses a significant threat to both pre- and post-harvest stages, leading to substantial economic losses. Famoxadone, a quinone outside inhibitor fungicide, was registered for controlling LDB in China in 2002. However, limited information is available regarding the risk, mechanism, and impact on lychee fruit quality associated with famoxadone resistance. In this study, we determined the sensitivity of 133 P. litchii isolates to famoxadone, yielding a mean EC50 value of 0.46 ± 0.21 μg/mL. Through fungicide adaption, we derived resistant mutants with M124I and Y131C substitutions in PlCyt b (Cytochrome b in P. litchii) from wild-type isolates. In vitro assessments revealed that the fitness of the resistant mutants was significantly lower compared to the parental isolates. These laboratory findings demonstrate a moderate resistance risk of P. litchii to famoxadone. Molecular docking analyses indicated that the M124I and Y131C alterations disrupted hydrogen bonds and weakened the binding energy between famoxadone and PlCyt b. This indicates that the M124I and Y131C changes do indeed confer famoxadone resistance in P. litchii. Infection caused by famoxadone-resistant mutants exhibited a decreased or comparable impact on the characteristic traits of lychee fruit compared to the sensitive isolate. For future detection of famoxadone-resistant strains, AS-PCR primers were designed based on the M124I substitution.

Effects of temperature and water activity on 25 de novo strains of pathogenic plant fungi in Al-Baha and Baljurashi cities in Saudi Arabia

Fungi inflict a great deal of damage to crops in fields and in storage facilities, causing issues such as leaf spot, wilt, rust, dieback and rot, as well as releasing mycotoxins that taint vegetation. In the current study, 25 de novo fungal isolates were taken from infected plant tissue (leaf, root and fruit), at pre- and post-harvest stages. Isolates were identified using molecular markers; 8 genera and 15 species were determined. The most common species was Penicillium spp. (40%), Aspergillus spp. (20%), Fusarium spp. (16%) and Alternaria alternata species (8%). The remaining 16% was comprised of various types of fungi, including Geotrichum candidum, Neofusicoccum parvum, Rhizopus stolonifera and Mucor fragilis. Many of these genera are known to cause significant crop damage and are notorious mycotoxin producers. An evaluation of the optimal growth temperature revealed the ideal temperatures were 30 °C for 56% of isolates, 25 °C for 28% of isolates and 20 °C for 16% of isolates. An assessment of water activity showed that 60% of isolates belonged to Penicillium and Aspergillus spp. and were mesophilic and xerophilic. Another 28% of isolates were Fusarium spp., Geotrichum candidum, Neofusicoccum parvum and Mucor fragilis, and hydrophilic. The remaining 12%, representing Alternaria alternata and Rhizopus stolonifera, were mesophilic. The current study provides accurate eco-physiological response data and molecular information for each isolate. The findings can assist the development of novel approaches to control the expansion of invasive fungal infections and minimise their deleterious consequences.

The interaction between CmPIF8 and CmACO1 under postharvest red light treatment might affect fruit ripening and sucrose accumulation in oriental melon fruit

Light and plant hormones are involved in regulating the growth, development and fruit quality formation. However, it remains unclear whether light regulates the fruit quality of oriental melon by affecting hormones. Sucrose is mainly accumulated in mature oriental melon fruit, and the accumulation of sucrose is closely related to ethylene. Here, the climacteric melon fruit ‘HS’ were treated with red and blue light at ethylene release initial stage (30 d after anthesis, DAA), and the results showed that the red light treatment enhanced the production of ethylene and the activity of 1-aminocyclopropane-1-carboxylate oxidase (ACO), as well as CmACO1 expression in melon fruit at postharvest stage. Red light also up-regulated the sucrose accumulation and the activity of sucrose phosphate synthetase (SPS) and CmSPS1 expression in postharvest melon fruit. Moreover, we found that PHYTOCHROME INTERACTING FACTOR 8 (PIF8), as a negative regulator of ethylene biosynthesis by directly binding to CmACO1 promoter. In summary, red light treatment at postharvest stage suppressed the expression of CmPIF8, and released the inhibitory effect of CmPIF8 on CmACO1, thereby promoting the ethylene production and fruit ripening, which indirectly increased the sucrose content in melon fruit.

Order assignment and two-stage integrated scheduling in fruit and vegetable supply chains

Fruit and vegetable supply chains require tight integration due to freshness-keeping requirements during the post-harvest, production, and distribution stages. This paper addresses the scheduling problem of a two-stage flow shop in the fruit and vegetable supply chain involving procurement, production, distribution, and order assignment. The supply chain consists of contract growers, processors, and demand points. Growers and processors maintain limited capacity. Growers have processing lines to sort and grade fruits and vegetables, which are then shipped to processors for further processing. The first stage of the problem involves determining the production and distribution schedules of growers to processors. The second stage concerns assigning demand points to processors, scheduling production at processors, and distributing from processors to demand points. This paper considers its two sub-problems and proposes a mixed-integer linear programming problem: growers’ and processors’ production and distribution scheduling with order assignment. Also, we present two respective strongly polynomial algorithms for solving the two sub-problems. Besides, we develop a two-phase heuristic algorithm for the integrated problem by solving sub-problems together. We conduct computational experiments to justify the proposed algorithms and integration value. Computational results reveal that the proposed algorithms outperform the CPLEX on large-scale problem instances. Finally, we analyze the impacts of waste reduction, unit processing time and cost, and inbound and outbound shipping rates on supply chain performance, along with managerial insights.

An Overview of Different Fruit Crop Models in the last 40 Years to Date with Their Main Uses

Horticulture is a versatile field which encompasses a plethora of day to day strategic decisions like varietal selection, optimisation of resources, understanding the mechanisms of the phenology, identification of plant invaders both in the micro and macro level, wise and judicious use of plant protectants, yield prediction & assessment, post harvesting & handling, strategic way of understanding the pulse of consumer’s popular demands and efficient way of marketing. Fruit trees are perennial unlike annual vegetable and cereal crops where there is a high prerequisite for efficient modelling of canopy architecture, photosynthesis, nutrient uptake, pest forecasting etc where the ill-effects of climate change are bringing out huge losses in the existing germplasm, annual turnover of the farmers and emergence of unheard pests and diseases. An invincible foresight or preparedness against such vagaries can be brought out by efficient modelling mechanisms combining the physiology, phenology and vital requirements of fruit trees with the interacting ecosystem of the land where it is present. Extrapolating such models from the local level to a general situations always gives fruitful results and it further aids in strengthening the present protocols. With the advancement of machine learning and deep learning in precision agriculture, problems of farmers and orchardists are being solved at a faster pace with the help of sensors in identification of problems and its alleviation using fast and error-free processing at pre-harvesting, harvesting and post-harvesting stages of fruit crops. In fact it is also one of the major concerns among people regarding the complete replacement of human power in the crucial decision support systems for agriculture and farming.

A Life Cycle Cost Analysis—Relevant Method Supporting the Decision to Establish an Apple Orchard in an Organic System

The life-cycle cost analysis is a method used to assess long-term economic efficiency among equivalent competing processes or products. The purpose of this paper is to investigate the nature and level of costs for an organic orchard located in Southern Romania, using a complex approach covering the entire chain of production, through its life span. The research results, based on a dynamic analysis and an integrated evaluation of the orchard’s performance, were ranked on investment and operational costs and broken down into three categories (establishment, production, post-harvest, transport costs). The highest costs, representing 151,726 EUR/ha/20 years, about 52.72% of the total operational costs and 50.4% of the total farm costs/ha/20 years, were recorded in the exploitation stage. The scenarios for the sensitivity analysis considered different levels of average yields (40 and 60 tons/ha, respectively) with different rates of sold productions (85%, optimistic scenario; 70%, pessimistic scenario). The hot points identified at the production stage were the use of agricultural machinery, several pesticides, the costs of seedlings, anti-hail nets, plastic boxes, and labor costs, while at the post-harvest stage, there were those related to labor and energy consumption. The transport stage had important costs with respect to tractor operations and the track.

Disinfection efficiency of chlorine dioxide and peracetic acid against MNV-1 and HAV in simulated soil-rich wash water

Wash water from fresh vegetables and root vegetables is an important vehicle for foodborne virus transmission. However, there is lack of assessing rapid viral inactivation strategies in wash water characterized by a high soil content at the post-harvest stage. Considering the significance of food safety during the washing stage for fresh and root vegetable produce prior to marketing, we assessed the inactivation efficacy by using chlorine dioxide (ClO2) and peracetic acid (PAA) against a surrogate of human norovirus (murine norovirus 1, MNV-1) and hepatitis A virus (HAV), in wash water containing black soil and clay loam. The results indicated that MNV-1 and HAV were reduced to the process limit of detection (PLOD), with reductions ranging from 4.89 to 6.35 log10 PFU, and 4.63 to 4.96 log10 PFU when treated with ClO2 at 2.5 ppm for 10 mins. Comparatively, when treated with 500 ppm of PAA for 10 mins, MNV-1 and HAV were maximum reduced to 1.75 ± 0.23 log10 PFU (4.50 log10 PFU reduction) and 2.13 ± 0.12 log10 PFU (2.72 log10 PFU reduction). This demonstrated the efficacy of ClO2 in eliminating foodborne viruses in soil-rich wash water. When we validated the recovery of the virus from two types of wash water, the pH (9.24 ± 0.33 and 5.95 ± 0.05) had no impact on the recovery of MNV-1, while the recovery of HAV was less than 1 %. By adjusting the pH to a neutral level, recovery of HAV and its RNA levels was increased to 15.94 and 3.89 %. Thus, this study emphasized the critical role of pH in the recovery of HAV from the complex soil-rich aqueous environment, and the efficacy of ClO2 serving as a pivotal reference for the development of control strategies against foodborne viruses in the supply chain of fresh and root vegetables.

Molecular Characterization of Colletotrichum gloeosporioides (Glomerella cingulata) Causing Mango Anthracnose Disease

Mango production in Tamil Nadu is known to be adversely affected by C. gloeosporioides in both field and post harvest stage of crop and drastically reduces market and edible value of fruit. To manage the disease it is essential to learn about the nature of pathogen and its way of interaction with host and its survival ability in environment. Hence a study has been carried out on Isolation of fungal pathogen was done using PDA medium in order to identify the disease's causative agent and its variation in morphology and colony characters. A total of twenty-four C. gloeosporioides isolates were obtained from various Tamil Nadu mango cultiavting areas of Tamil Nadu. The isolates were identified morphologically and molecularly. The microscopic features such as conidia shape and size were used to identify C. gloeosporioides. The CTAB technique was employed to extract the DNA from the isolates of C. gloeosporioides. A total of 24 isolates were subjected to ITS (Inter Transcribed Spacer) of 18s ribosomal RNA amplification; all of these isolates exhibited amplified products with a size range of 560 bp, indicating that they were fungal pathogen. The MkCgF and MkCgR PCR primer combination was unique to the ITS region of C. gloeosporioides species. It has been confirmed that all 24 of the C. gloeosporioides isolates are really C. gloeosporioides by amplifying the predicted size of 380 bp.

Genetic variation of drug target CYP51 conferring resistance to ergosterol biosynthesis inhibitors in Botrytis cinerea, causing lily gray mould

Gray mould caused by Botrytis cinerea poses a threat to Lily (Lilium spp.), an important plant with both medicinal and ornamental value, during pre- and post-harvest stages. Ergosterol biosynthesis inhibitors (EBIs) have been widely registered to control gray mould caused by B. cinerea in various plants over a prolonged period of time, yet no instances of resistance of B. cinerea to EBIs have been detected in the field. In this study, the field B. cinerea EBIs-resistant populations were detected from the diseased lily flowers. The CYP51 protein, which is the target of EBIs, was found to have G461S or R464K substitutions in these resistant strains. To further verify whether the G461S or R464K substitutions of CYP51 confer the resistance to EBIs in B. cinerea, the mutants carrying the G461S or R464K substitutions of CYP51 were generated from EBIs-sensitive wild type strains via site-directed mutagenesis. The G461S or R464K substitutions indeed resulted in decreased sensitivity of B. cinerea to EBIs. Meanwhile, the mutants conferring the S461G or K464R substitutions of CYP51 were generated from the field EBIs-resistant strains, and the significant increase in sensitivity to EBIs were observed in these mutants. Furthermore, the G461S or R464K substitutions suffered to fitness penalty in mycelial growth and virulence, but improved sporulation capability. Molecular docking analysis furtherly demonstrated that the CYP51 protein, carrying the G461S or R464K substitutions, exhibited reduced binding affinity with tebuconazole. To the best of our knowledge, it is the first report that G461S or R464K substitutions in CYP51 leading to field resistance to EBIs in B. cinerea. These findings not only provided valuable insights for managing lily gray mould caused B. cinerea, but also enhance our understanding of molecular mechanism underlying plant pathogen resistance to EBIs.

A Review of the Efficacy of Medicinal Plants as Good Anti-Infection Agents

Fungicides should be used to prevent plants against numerous plant-attacking pathogens in order to support the agriculture sector and raise food production, which often results in the ubiquitous usage of synthetic chemicals. Crops are more vulnerable to diseases when they are in the post-harvest stages. However, these compounds have some major drawbacks, such as harm to human health, bad environmental conditions, disease resistance to fungicides, etc. This results in identifying compounds derived from plants that can be used in managing disease control. Plants have a wide variety of compounds that can be isolated and applied in a variety of ways, one of which is treating damaged plants. These substances are collectively referred to as secondary metabolites because, despite playing an equally significant role, they do not play a part in the growth and development of plants. These secondary metabolites cover a wide range, including glycosides, alkaloids, phenols, flavonoids, terpenoids, tannins, and saponins. Several approaches are present to extract the phytochemicals from plants without disrupting their functional groups or qualities that let them target the pathogens. Plant-based fungicides have long highlighted the variety of plant species that shield the flora from pathogens without harming the plant system. This review paper focuses on how several medicinal plant families proved to be strong anti-infection agents.

Barriers to Minimisation of agri-products wastage through Optimizing logistics in India: An ISM modelling approach

The research work identifies and priorities the factors affecting agri-logistics causing wastage of the agricultural products during its transit from farm to the point of consumption so that logistics mechanism for agriculture sector in India can be optimised by removing the barriers leading to hindrances in safe, timely, economical and good condition delivery of the agri consignment. The field of agri-logistics remains at the crucial nexus of the agricultural and logistics industries and has the potential to improve the nation's system for distributing food. The post-harvest wastage in India has been massive due to inefficiencies agri-logistics management and faulty food distribution mechanism. It is an exploratory study that along the factors (barriers) identified and synthesised from literature review of the concerned area. The identified barriers were reduced and finalised in consultation with the experts using Delphi technique. With the help of ISM questionnaire, a model has been developed reflecting the drivers and dependents out of the barriers considered for the study. The result is further validated through MICMAC analysis. The result of the study has come up with the interpretive structure model depicting hierarchy of the barriers pushing from down to top causing agriculture wastage. The paper holds originality in the sense that it comes up with fresh perspectives on the factors causing hindrances in the efficient logistics operation that certainly helps to minimise wastage of the agri-products in the post-harvest stages. The identification of the barriers and their detriments to the other factors will help to take essential steps on how to overcome the issues and optimize the agri-logistics that would minimise the agri-wastage in India and prove to be a game changer to the agri-trade sector.

Effect of cleaning, milling, and cooking on the reduction of deoxynivalenol in freshly harvested rice

Abstract Fusarium mycotoxins were frequently present in freshly harvested rice samples caused by Fusarium head blight in China recently. Due to the importance of rice and the risks associated with mycotoxins, the fate of Fusarium mycotoxins in rice was evaluated by physical methods. In the present study, a total of 157 freshly harvested rice samples were collected from fields in Jiangsu Province. Mycotoxin analysis showed that only Fusarium mycotoxins were found in these samples, with deoxynivalenol (DON) being the major mycotoxin. Twenty-three freshly harvested rice samples containing concentrations of DON higher than 200 μg/kg were selected for cleaning and milling. Compared with air or gravity separation, the combined air and gravity separation was the most effective cleaning method to decrease the content of DON. After milling, brown and white rice intended for human consumption presented lower level of DON than freshly harvested rice, husks, and bran. Three types of brown and white rice with different contents of DON were chosen for cooking. Compared with other treatments, preboiled was the most effective method to reduce DON in both brown and white rice. The results of this study improve our understanding of the transfer ratios of DON and the development of effective control measures during the postharvest stage.