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The virtual organization (VO) emerged intending to improve products and services in a globalized environment through collaborative work between organizations of different kinds. There is abundant literature around this topic for more than ten years. Today, with the mandatory trend of digital transformation, the aim is to redefine VO concepts and study them in the context of Industry 4.0. This paper will study the evolution of VO, from its beginnings (2010) to 2020, with a systematic literature review (SLR). This SLR will be quantified by a meta-analysis, which will allow an orderly view of the findings found. The objective is to find all the studies that have been carried out on VO frameworks based on Industry 4.0, collaborative works, and autonomous processes.

A systematic literature review is a synthesis of the available evidence, in which a review of quantitative and qualitative aspects of primary studies is carried out, to summarize the existing information regarding a particular topic. The researchers extract key criteria from papers collected about their study area, answering research questions and conducting document analysis. Nonetheless, in some cases, these criteria are improperly justified, unknowing their true level of importance in the study subject. Hence, an additional study is necessary to explain the criteria relevance in the papers studied using qualitative and quantitative premises. The correct identification of these key criteria is a critical factor in prioritizing and achieving appropriate results in any scientific research work. In our paper, a new method to determine key criteria from a literature review is proposed, composed of three components: input-process-output. First, the inputs are a set of criteria to evaluate and a set of documents to analyze. Next, the process component examines the document set to indicate whether the criteria to be analyzed are found. The process component produces a Boolean matrix, which is the input of the mathematical logic process that will get the key criteria considered necessary and sufficient as the output component. The iKeyCriteria method has been applied in different computing domains, particularly for serious games design and virtual organizations, giving positive results in each context. Finally, we developed an online tool that provides global support to the execution of our method.

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.

A Virtual Organization (VO) unites companies or independent individuals to achieve a shared, short-term objective by leveraging information technologies for communication and coordination in personalized product creation. Despite extensive research, existing VO management architectures lack alignment with Industry 4.0 standards, do not incorporate intelligent requirement-gathering mechanisms, and are not based on the RAMI 4.0 framework. These limitations hinder support for Autonomous Virtual Organizations (AVOs) in evaluation, risk management, and continuity, often excluding small and medium-sized enterprises (SMEs) during the partner selection process. This study proposes a comprehensive architecture for AVO management, grounded in ACODAT (Autonomous Cycle of Data Analysis Tasks) and RAMI 4.0 principles. The methodology includes a literature review, an architectural design, and a detailed specification of the ACODAT for the digital supply chain design. A prototype was developed and applied in a case study involving a virtual organization within an editorial consortium. Evaluation addressed core service performance, scalability of the batch selection algorithm, resource-use efficiency, and accessibility/SEO compliance. Benchmarking demonstrated that the prototype met or exceeded thresholds for scalability, efficiency, and accessibility, with minor performance deviations attributed to the testing environment. The results highlight significant time savings and improved automation in requirement identification, partner selection, and supply chain configuration, underscoring the architecture’s effectiveness and inclusivity.

Fusarium wilt, a vascular disease of strawberry (Fragaria × $\\times$ananassa) caused by the soilborne fungal pathogen Fusarium oxysporum f. sp. fragariae, has emerged over the past 20 years as a leading cause of severe plant wilt and death in California and many other parts of the world. We previously described several sources of resistance to race 1 of the pathogen; showed that resistance was conferred by dominant resistance genes (R‐genes) on chromosomes 2B (FW1, FW2, and FW5), 1A (FW3), and 6B (FW4); and identified a cultivar (Earliglow) that was hypothesized to be a source of novel R‐genes. Earliglow S1 ${\\mathrm{S}_{1}}$progeny segregated 15 resistant:1 susceptible (χ2=0.03;p=0.87 $\\chi ^2 = 0.03; p = 0.87$ ), the Mendelian distribution expected when the phenotypes are caused by unlinked dominant duplicate epistasis. Here, we show that Earliglow carries a dominant R‐gene (FW6) in the FW1 cluster on chromosome 2B and an incompletely dominant R‐gene (FW7) on chromosome 2A, where Fusarium wilt R‐genes have not been previously reported. The effect of FW7 was masked by the epistatic effect of FW6; this was determined by self‐pollinating an S1 ${\\mathrm{S}_{1}}$individual predicted to be homozygous for the recessive (susceptible) FW6 allele and heterozygous for FW7 alleles, creating and whole‐genome sequencing Fusarium wilt resistant and susceptible S2 ${\\mathrm{S}_{2}}$bulks, and physically mapping the FW7 locus by bulked segregant analysis. Lastly, we identified candidate genes for FW7, in addition to highly predictive FW6‐ and FW7‐associated SNPs for marker‐assisted selection of FW6 and FW7 alleles. This study laid the foundation for identifying the causal gene underlying FW7 and increasing the durability of resistance to Fusarium wilt by pyramiding FW7 with independent R‐genes. Core Ideas The resistance of the heirloom cultivar Earliglow to Fusarium wilt race 1 is conferred by a dominant gene on chromosome 2B (FW6) and a nearly additive gene on chromosome 2A (FW7). The effect of FW7 was weaker than and masked by the epistatic effect of FW6. Whole‐genome sequencing bulked segregant analysis (WGS‐BSA) was validated as an approach for discovering and physically mapping DNA markers associated with large‐effect loci in octoploid strawberry. Highly predictive FW6‐ and FW7‐associated DNA markers were identified by genome‐wide association studies and WGS‐BSA. FW6 and FW7 can be pyramided to increase the durability of resistance to Fusarium wilt race 1. Plain Language Summary Fusarium wilt, a strawberry disease that causes wilting and death in susceptible genotypes, has become an increasingly serious problem in home gardens and farms around the world. There are, however, natural genetic sources of resistance to the causal pathogen (Fusarium oxysporum f. sp. fragariae), including wild relatives and heirloom and modern cultivars. We previously identified genes on three chromosomes (1A, 2B, and 6A) that confer resistance to the most common race of the pathogen found in California (race 1). Using insights gained from previous studies, we discovered that the heirloom cultivar Earliglow carries a novel race 1 resistance gene on chromosome 2A (FW7). The effect of this newly identified resistance gene was hidden by the epistatic effect of a dominant gene (FW6) found in a previously identified cluster of resistance genes on chromosome 2B. We uncovered and physically mapped FW7 using high‐throughput sequencing of resistant and susceptible bulks in combination with physical mapping of sequences to an octoploid reference genome, a tried‐and‐true approach known as bulked segregant analysis. Our study shows that strawberry has evolved multiple Fusarium wilt resistance genes that can be combined through marker‐assisted selection to prevent losses to the disease and increase the durability of resistance.

Strawberry (Fragaria × $\\times$ananassa) reproduces sexually through seeds and asexually through stolons. The ability to cost‐effectively clonally propagate hybrid individuals on a large scale has shaped strawberry breeding and production practices. Despite the technical and economic importance of clonal propagation, little is known about the genetic regulation of runnering in strawberry, apart from the pleiotropic effects of PERPETUAL FLOWERING (PF), a dominant gene introgressed from a wild relative that abolishes temperature‐dependent photoperiod sensitivity and incompletely and variably suppresses runnering. Here, we show that runnering phenotypes are heritable and highly variable in strawberry, ranging from runnerless to prolific in short‐day (pfpf) and day‐neutral (PF_) plants. The PF locus was physically mapped to Mb 26.4–27.3 on chromosome 4B and found to explain 22% of the genetic variance for runnering (78% of the heritability was missing). PF was the only runnering‐associated locus identified by genome‐wide association studies among diverse clonal genetic resources and progeny from narrow and wide crosses (1537 individuals). The pleotropic effect of PF on runnering was temporal, variable, and incompletely dominant. Genomic selection was found to be a viable strategy for modifying runnering phenotypes in strawberry. Genomic prediction accuracies ranged from 0.53 to 0.79 for runnering, were greater within than between populations, and increased when corrected for PF. Our study builds the foundation for improving the productivity of strawberry by developing runnerless cultivars for seed‐propagation or reduced runnering cultivars for clonal‐propagation through phenotypic or genomic selection. Core Ideas Variation for runnering is substantial and heritable within seasonal and perpetual flowering strawberry populations. The pleiotropic suppression of runnering by the PERPETUAL FLOWERING (PF) allele is continuously variable, temporal, and incompletely dominant. The accuracy of breeding value prediction is sufficient for modifying the runner growth characteristics of the strawberry plant by genomic selection. The productivity of strawberry can be improved by introducing seed‐propagated cultivars with runnerless and clone‐propagated cultivars with reduced runnering phenotypes. Plain Language Summary The ability to clone individual plants has shaped strawberry breeding and production practices, and runner (stolon) growth is well known to home gardeners and farmers alike and important for the propagation of strawberry cultivars. The energy that the strawberry plant diverts into runner growth can decrease fruit yield. To circumvent maximize fruit yield, farmers mechanically trim runners. The genetic factors that control runner growth are complex but mostly unknown apart from PERPETUAL FLOWERING, a gene controlling photoperiod sensitive flowering and affecting runnering. We observed a full spectrum of runner growth phenotypes in seasonal and perpetual flowering populations, found that runnering phenotypes are heritable, and showed that the runner growth of strawberry plants can be modified by phenotypic or genomic selection. Lastly, we identified extreme transgressive segregates for runnering and showed that runnerless and reduced runnering cultivars can be developed to reduce production costs and improve productivity.

Two hydrothermal techniques under microwave irradiation were used to synthesize γ-MnO 2 from 90°C to 150°C in 10−30 min. The first technique is based on reducing KMnO 4 with MnSO 4 , and the second one involves liquid-phase oxidation between MnSO 4 and (NH 4 ) 2 S 2 O 8 . The structures and morphologies of the samples were analyzed using X-ray diffraction, scanning electron microscopy, and N 2 physisorption measurements. The electrochemical properties were evaluated through cyclic voltammetry and electrochemical impedance spectroscopy. The γ-MnO 2 materials obtained by the first technique mainly exhibited nanorods with diameters of 40–60 nm, and the samples obtained by the second technique showed flower-like microspheres with diameters of 1−2 µm; each flower was composed of nanosheets with a thickness of 10−20 nm. The processing time directly depends on the size of the nanorods. The sample synthesized by the first technique at 150°C and 10 min has the highest specific surface area of up to 59.08 m 2 g −1 and mean pore diameter of 34.11 nm. Furthermore, this sample exhibits a near-rectangular cyclic voltammetry curves and high specific capacitance of 331.3 F g −1 in 0.1 M Na 2 SO 4 solution at 5 mV s −1 scan rate. Graphic abstract