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BackgroundFungal pathogens significantly impact the quality of fruits and vegetables at different stages of the supply chain, leading to substantial food losses. Understanding how these persistent fungal infections occur and progress in postharvest conditions is essential to developing effective control strategies.ResultsIn this study, we developed a reliable and consistent inoculation protocol to simulate disease spread from infected fruits to adjacent healthy fruits during postharvest storage. We tested different combinations of relevant fruit commodities, including oranges, tomatoes, and apples, against impactful postharvest pathogens such as Penicillium digitatum, Penicillium italicum, Botrytis cinerea, and Penicillium expansum. We assessed the efficacy of this protocol using fruits treated with various postharvest methods and multiple isolates for each pathogen. We optimized the source of infected tissue and incubation conditions for each fruit-pathogen combination. Disease incidence and severity were quantitatively evaluated to study infection success and progression. At the final evaluation point, 80% or higher disease incidence rates were observed in all trials except for the fungicide-treated oranges inoculated with fungicide-susceptible Penicillium spp. isolates. Although disease incidence was lower in that particular scenario, it is noteworthy that the pathogen was still able to establish itself under unfavorable conditions, indicating the robustness of our methodology. Finally, we used multispectral imaging to detect early P. digitatum infections in oranges before the disease became visible to the naked eye but after the pathogen was established.ConclusionsWe developed a non-invasive inoculation strategy that can be used to recreate infections caused by contact or nesting in postharvest. The observed high disease incidence and severity values across fruit commodities and fungal pathogens demonstrate the robustness, efficacy, and reproducibility of the developed methodology. The protocol has the potential to be tailored for other pathosystems. Additionally, this approach can facilitate the study of fruit-pathogen interactions and the assessment of innovative control strategies.

Postharvest fungal pathogens benefit from the increased host susceptibility that occurs during fruit ripening. In unripe fruit, pathogens often remain quiescent and unable to cause disease until ripening begins, emerging at this point into destructive necrotrophic lifestyles that quickly result in fruit decay. Here, we demonstrate that one such pathogen, Botrytis cinerea, actively induces ripening processes to facilitate infections and promote disease in tomato (Solanum lycopersicum). Assessments of ripening progression revealed that B. cinerea accelerated external coloration, ethylene production, and softening in unripe fruit, while mRNA sequencing of inoculated unripe fruit confirmed the corresponding upregulation of host genes involved in ripening processes, such as ethylene biosynthesis and cell wall degradation. Furthermore, an enzyme-linked immunosorbent assay (ELISA)-based glycomics technique used to assess fruit cell wall polysaccharides revealed remarkable similarities in the cell wall polysaccharide changes caused by both infections of unripe fruit and ripening of healthy fruit, particularly in the increased accessibility of pectic polysaccharides. Virulence and additional ripening assessment experiments with B. cinerea knockout mutants showed that induction of ripening depends on the ability to infect the host and break down pectin. The B. cinerea double knockout Δbc polygalacturonase1 Δbc polygalacturonase2 lacking two critical pectin degrading enzymes was incapable of emerging from quiescence even long after the fruit had ripened at its own pace, suggesting that the failure to accelerate ripening severely inhibits fungal survival on unripe fruit. These findings demonstrate that active induction of ripening in unripe tomato fruit is an important infection strategy for B. cinerea.

Agricultural science necessarily involves a commitment to some form of humanitarian and environmental ethics. For the past century, agricultural science has been based on a productivist ethic of maximizing agricultural production in pursuit or support of food security. Recognition of the ethical and political disposition of contemporary agricultural science can help scientists reorient their work to better address the urgent problems of the upcoming century: environmental degradation, climate change, and social inequality. A commitment to solving these problems is well within the scope of modern agricultural science. Supporting and furthering multidimensional food systems should replace productivism as an explicit goal of agricultural development and scientific innovation.

ContextThe COVID-19 pandemic caused significant shocks to U.S. food systems at multiple scales. While disturbances to long-distance supply chains received substantial attention in national media, local supply chains experienced mixed impacts. As broad closures of schools, restaurants, and other businesses sourcing from local farmers removed key marketing channels for many direct market farmers, consumer interest in Community Supported Agriculture (CSA), farmers markets, and on-farm and online direct farm sales increased.ObjectiveIn this paper, we examine the resilience and vulnerability of farmers during the March 2020 through December 2020 period of the COVID-19 pandemic. We focus on California farmers and ranchers engaged in direct market sales.MethodsThrough a widely disseminated survey, we collected responses from 364 farmers and used these data to answer the following questions about direct market farmers in California: 1) What were direct market farmers' experiences of the pandemic from March 2020 through December 2020? 2) Which factors (e.g., relationships, institutions, market channels) did farmers report enhanced their resilience during the pandemic? 3) Which individual and operational factors were significantly associated with resilience during the pandemic? And finally, 4) how do the farmer-reported factors compare to the statistically significant factors associated with resilience? We created three dependent variables-ability to respond to the pandemic, concern about pandemic impacts, and change in profitability-to operationalize several aspects of resilience and examine their association with individual and operational characteristics through a series of ordered logistic regression models.Results and conclusionsAcross both the quantitative models and the farmer reported factors, we found that farmers who increased their use of online sales and marketing during the first year of the pandemic, had larger-scale farms, and had more on-farm crop and livestock diversity were more resilient to the shocks of the pandemic. We also found that greater use of non-direct-to-consumer market channels was associated with less resilience. The characteristics of the farming operations played a relatively larger role in predicting resilience compared to the individual characteristics of the farmers surveyed.SignificanceThis study gives a detailed picture of how California direct market farmers fared during the pandemic and the characteristics associated with greater resilience. As short and long-term disruptions become increasingly common in agriculture, policies and programs can leverage support to direct market farmers, particularly direct-to-consumer farmers, as a strategy to strengthen farmer resilience.

Background and purposeClinical outcomes of multiple sclerosis (MS) patients affected by coronavirus disease 2019 (COVID-19) have been thoroughly investigated, but a further analysis on main signs and symptoms and their risk factors still needs attention. The objective of this study was to group together and describe based on similarity the most common signs and symptoms of COVID-19 in MS patients and identify all factors associated with their manifestation.MethodLogistic and linear regression models were run to recognize factors associated with each pooled group of symptoms and their total number.ResultsFrom March 2020 to November 2021, data were collected from 1354 MS patients with confirmed infection of COVID-19. Ageusia and anosmia was less frequent in older people (odds ratio [OR] 0.98; p = 0.005) and more in smoker patients (OR 1.39; p = 0.049). Smoke was also associated with an incremental number of symptoms (OR 1.24; p = 0.031), substance abuse (drugs or alcohol), conjunctivitis and rash (OR 5.20; p = 0.042) and the presence of at least one comorbidity with shortness of breath, tachycardia or chest pain (OR 1.24; p = 0.008). Some disease-modifying therapies were associated with greater frequencies of certain COVID-19 symptoms (association between anti-CD20 therapies and increment in the number of concomitant symptoms: OR 1.29; p = 0.05). Differences in frequencies between the three waves were found for flu-like symptoms (G1, p = 0.024), joint or muscle pain (G2, p = 0.013) and ageusia and anosmia (G5, p

This research examines the extent to which a Farm-to-Table restaurant prompted social and ecological changes in the food system. Chefs and restaurants are uniquely positioned to both generate consumer interest in certain foods and motivate farmers to grow such products. Despite their central role in Alternative Food Networks (AFNs), the influence of restaurants on farming practices and the re-localization of food sourcing is under-explored. In this research, we used archival document review, interviews, surveys, and social network mapping to understand the mechanisms by which direct market connections between farmers and the Chez Panisse restaurant grew over time and influenced farmers’ growing practices. Founded in Berkeley by Alice Waters in 1971, Chez Panisse is frequently credited with pioneering the Farm-to-Table model and spurring the slow, local, and organic food movements. Our study suggests that Chez Panisse inspired farmers toward more sustainable agriculture practices, but the restaurant was not the only influential actor in the network. We found that local food hub managers and the restaurant’s “foragers” were key intermediaries. Our findings demonstrate that social embeddedness in AFNs is pertinent to fostering sustainable agriculture, the long-term survival of network actors, and network growth. Acronyms: AFN: Alternative Food Network; DTC: Direct-to-consumer; CSA: Community-Supported Agriculture.

Background and purposeSome studies have shown that air pollution, often assessed by thin particulate matter with diameter below 2.5 µg/m3 (PM2.5), may contribute to severe COVID-19 courses, as well as play a role in the onset and evolution of multiple sclerosis (MS). However, the impact of air pollution on COVID-19 has never been explored specifically amongst patients with MS (PwMS). This retrospective observational study aims to explore associations between PM2.5 and COVID-19 severity amongst PwMS.MethodsData were retrieved from an Italian web-based platform (MuSC-19) which includes PwMS with COVID-19. PM2.5 2016-2018 average concentrations were provided by the Copernicus Atmospheric Monitoring Service. Italian patients inserted in the platform from 15 January 2020 to 9 April 2021 with a COVID-19 positive test were included. Ordered logistic regression models were used to study associations between PM2.5 and COVID-19 severity.ResultsIn all, 1087 patients, of whom 13% required hospitalization and 2% were admitted to an intensive care unit or died, were included. Based on the multivariate analysis, higher concentrations of PM2.5 increased the risk of worse COVID-19 course (odds ratio 1.90; p = 0.009).ConclusionsEven if several other factors explain the unfavourable course of COVID-19 in PwMS, the role of air pollutants must be considered and further investigated.

Gray mold, a disease of strawberry (Fragaria × ananassa) caused by the ubiquitous necrotroph Botrytis cinerea, renders fruit unmarketable and causes economic losses in the postharvest supply chain. To explore the feasibility of selecting for increased resistance to gray mold, we undertook genetic and genomic prediction studies in strawberry populations segregating for fruit quality and shelf life traits hypothesized to pleiotropically affect susceptibility. As predicted, resistance to gray mold was heritable but quantitative and genetically complex. While every individual was susceptible, the speed of symptom progression and severity differed. Narrow-sense heritability ranged from 0.38 to 0.71 for lesion diameter (LD) and 0.39 to 0.44 for speed of emergence of external mycelium (EM). Even though significant additive genetic variation was observed for LD and EM, the phenotypic ranges were comparatively narrow and genome-wide analyses did not identify any large-effect loci. Genomic selection (GS) accuracy ranged from 0.28 to 0.59 for LD and 0.37 to 0.47 for EM. Additive genetic correlations between fruit quality and gray mold resistance traits were consistent with prevailing hypotheses: LD decreased as titratable acidity increased, whereas EM increased as soluble solid content decreased and firmness increased. We concluded that phenotypic and GS could be effective for reducing LD and increasing EM, especially in long shelf life populations, but that a significant fraction of the genetic variation for resistance to gray mold was caused by the pleiotropic effects of fruit quality traits that differ among market and shelf life classes.

Local food systems are growing, and little is known about how the constellation of farms and markets change over time. We trace the evolution of two local food systems (Baltimore County, Maryland and Chester County, Pennsylvania) over six years, including a dataset of over 2690 market connections (edges) between 1520 locations (nodes). Longitudinal social network analysis reveals how the architecture, actor network centrality, magnitude, and spatiality of these supply chains shifted during the 2012-2018 time period. Our findings demonstrate that, despite growth in the number of farmers' markets, grocery stores, farms and restaurants in both counties, each local food system also experienced high turnover rates. Over 80% of the market connections changed during the study period. Farms, farmers' markets, and grocery stores showed a 40-50% 'survival' rate, indicating their role in sustaining local food systems over longer time periods. Other actors, such as restaurants, had a much higher turnover rate within the network. Both food systems became more close-knit and consolidated as the center of gravity for both local food systems pulled away from urban areas toward rural farmland. Evidence of both growth and decay within local food systems provides a new understanding of the social networks behind local food markets.

ObjectiveThis study was undertaken to assess the impact of immunosuppressive and immunomodulatory therapies on the severity of coronavirus disease 2019 (COVID-19) in people with multiple sclerosis (PwMS).MethodsWe retrospectively collected data of PwMS with suspected or confirmed COVID-19. All the patients had complete follow-up to death or recovery. Severe COVID-19 was defined by a 3-level variable: mild disease not requiring hospitalization versus pneumonia or hospitalization versus intensive care unit (ICU) admission or death. We evaluated baseline characteristics and MS therapies associated with severe COVID-19 by multivariate and propensity score (PS)-weighted ordinal logistic models. Sensitivity analyses were run to confirm the results.ResultsOf 844 PwMS with suspected (n = 565) or confirmed (n = 279) COVID-19, 13 (1.54%) died; 11 of them were in a progressive MS phase, and 8 were without any therapy. Thirty-eight (4.5%) were admitted to an ICU; 99 (11.7%) had radiologically documented pneumonia; 96 (11.4%) were hospitalized. After adjusting for region, age, sex, progressive MS course, Expanded Disability Status Scale, disease duration, body mass index, comorbidities, and recent methylprednisolone use, therapy with an anti-CD20 agent (ocrelizumab or rituximab) was significantly associated (odds ratio [OR] = 2.37, 95% confidence interval [CI] = 1.18-4.74, p = 0.015) with increased risk of severe COVID-19. Recent use (

Infections by the fungus Monilinia laxa, the main cause of brown rot in Europe, result in considerable losses of stone fruit. Herein, we present a comprehensive transcriptomic approach to unravel strategies deployed by nectarine fruit and M. laxa during their interaction. We used M. laxa-inoculated immature and mature fruit, which was resistant and susceptible to brown rot, respectively, to perform a dual RNA-Seq analysis. In immature fruit, host responses, pathogen biomass, and pathogen transcriptional activity peaked at 14-24 h post inoculation (hpi), at which point M. laxa appeared to switch its transcriptional response to either quiescence or death. Mature fruit experienced an exponential increase in host and pathogen activity beginning at 6 hpi. Functional analyses in both host and pathogen highlighted differences in stage-dependent strategies. For example, in immature fruit, M. laxa unsuccessfully employed carbohydrate-active enzymes (CAZymes) for penetration, which the fruit was able to combat with tightly regulated hormone responses and an oxidative burst that challenged the pathogen's survival at later time points. In contrast, in mature fruit, M. laxa was more dependent on proteolytic effectors than CAZymes, and was able to invest in filamentous growth early during the interaction. Hormone analyses of mature fruit infected with M. laxa indicated that, while jasmonic acid activity was likely useful for defense, high ethylene activity may have promoted susceptibility through the induction of ripening processes. Lastly, we identified M. laxa genes that were highly induced in both quiescent and active infections and may serve as targets for control of brown rot.

Worldwide, 20-25% of all harvested fruit and vegetables are lost annually in the field and throughout the postharvest supply chain due to rotting by fungal pathogens. Most postharvest pathogens exhibit necrotrophic or saprotrophic lifestyles, resulting in decomposition of the host tissues and loss of marketable commodities. Necrotrophic fungi can readily infect ripe fruit leading to the rapid establishment of disease symptoms. However, these pathogens generally fail to infect unripe fruit or remain quiescent until host conditions stimulate a successful infection. Previous research on infections of fruit has mainly been focused on the host's genetic and physicochemical factors that inhibit or promote disease. Here, we investigated if fruit pathogens can modify their own infection strategies in response to the ripening stage of the host. To test this hypothesis, we profiled global gene expression of three fungal pathogens that display necrotrophic behavior-Botrytis cinerea, Fusarium acuminatum, and Rhizopus stolonifer-during interactions with unripe and ripe tomato fruit. We assembled and functionally annotated the transcriptomes of F. acuminatum and R. stolonifer as no genomic resources were available. Then, we conducted differential gene expression analysis to compare each pathogen during inoculations versus in vitro conditions. Through characterizing patterns of overrepresented pathogenicity and virulence functions (e.g., phytotoxin production, cell wall degradation, and proteolysis) among the differentially expressed genes, we were able to determine shared strategies among the three fungi during infections of compatible (ripe) and incompatible (unripe) fruit tissues. Though each pathogen's strategy differed in the details, interactions with unripe fruit were commonly characterized by an emphasis on the degradation of cell wall components, particularly pectin, while colonization of ripe fruit featured more heavily redox processes, proteolysis, metabolism of simple sugars, and chitin biosynthesis. Furthermore, we determined that the three fungi were unable to infect fruit from the non-ripening (nor) tomato mutant, confirming that to cause disease, these pathogens require the host tissues to undergo specific ripening processes. By enabling a better understanding of fungal necrotrophic infection strategies, we move closer to generating accurate models of fruit diseases and the development of early detection tools and effective management strategies.

Worldwide, 20-25% of all harvested fruit and vegetables are lost annually in the field and throughout the postharvest supply chain due to rotting by fungal pathogens. Most postharvest pathogens exhibit necrotrophic or saprotrophic lifestyles, resulting in decomposition of the host tissues and loss of marketable commodities. Necrotrophic fungi can readily infect ripe fruit leading to the rapid establishment of disease symptoms. However, these pathogens generally fail to infect unripe fruit or remain quiescent until host conditions stimulate a successful infection. Previous research on infections of fruit has mainly been focused on the host's genetic and physicochemical factors that inhibit or promote disease. Here, we investigated if fruit pathogens can modify their own infection strategies in response to the ripening stage of the host. To test this hypothesis, we profiled global gene expression of three fungal pathogens that display necrotrophic behavior-Botrytis cinerea, Fusarium acuminatum, and Rhizopus stolonifer-during interactions with unripe and ripe tomato fruit. We assembled and functionally annotated the transcriptomes of F. acuminatum and R. stolonifer as no genomic resources were available. Then, we conducted differential gene expression analysis to compare each pathogen during inoculations versus in vitro conditions. Through characterizing patterns of overrepresented pathogenicity and virulence functions (e.g., phytotoxin production, cell wall degradation, and proteolysis) among the differentially expressed genes, we were able to determine shared strategies among the three fungi during infections of compatible (ripe) and incompatible (unripe) fruit tissues. Though each pathogen's strategy differed in the details, interactions with unripe fruit were commonly characterized by an emphasis on the degradation of cell wall components, particularly pectin, while colonization of ripe fruit featured more heavily redox processes, proteolysis, metabolism of simple sugars, and chitin biosynthesis. Furthermore, we determined that the three fungi were unable to infect fruit from the non-ripening (nor) tomato mutant, confirming that to cause disease, these pathogens require the host tissues to undergo specific ripening processes. By enabling a better understanding of fungal necrotrophic infection strategies, we move closer to generating accurate models of fruit diseases and the development of early detection tools and effective management strategies.

There is an increasing level of interest in the use of black TiO2 prepared by thermal hydrogen treatments (H:TiO2) due to the potential to enhance both the photocatalytic and the light-harvesting properties of TiO2. Here, we examine oxygen-deficient H:TiO2 nanotube arrays that have previously achieved very high solar-to-hydrogen (STH) efficiencies due to incident photon-to-current efficiency (IPCE) values of >90% for photoelectrochemical water splitting at only 0.4 V vs RHE under UV illumination. Our transient absorption (TA) mechanistic study provides strong evidence that the improved electrical properties of oxygen-deficient TiO2 enables remarkably efficient spatial separation of electron-hole pairs on the submicrosecond time scale at moderate applied bias, and this coupled to effective suppression of microsecond to seconds charge carrier recombination is the primary factor behind the dramatically improved photoelectrochemical activity.