Rural Resources

This perspective paper draws on insights from a 2024 symposium entitled ‘ Exploring methods for researching shifts in knowledge production for agroecology transition ’. The symposium critically examined emerging conceptual and methodological challenges arising from combining agroecology with living labs and research infrastructures as key instruments promoted within EU policy to strengthen Agricultural Knowledge and Innovation Systems (AKIS). Through presentations, group discussions, and iterative reflections, we identified four key tensions: structural constraints limiting farmers’ agency within living lab approaches, the problematic nature of AKIS as supposedly neutral frameworks, the oversimplification of transition frameworks as linear rather than overlapping categories, and risks of definitional dilution or cooptation. We then demonstrate that these tensions are not unique to agroecology, bridging the concepts and methods within agroecology research with those used in other fields of sustainable food system transition research, such as transdisciplinary research and sustainable transitions. This conceptual mapping of shared tensions reveals opportunities for mutual learning. Bridging these fields would help create clarity at the conceptual and methodological levels, ultimately strengthening the theoretical foundations and enabling more nuanced approaches to food system transition research.

Abstract The loss of agrobiodiversity is a world damage both in biological and cultural aspects. Although mountainous areas in Italy still preserve many traditional cultivars (landraces), they face increasing risk from genetic erosion and disappearance. This study focused on the identification and multidisciplinary characterization of 16 previously undocumented bean landraces ( Phaseolus vulgaris and P. coccineus ) from the Lombardy Alps (Italy) using genetic, morphological, nutritional and ecological approaches. Genetic analyses based on simple sequence repeat (SSR) markers revealed moderate but structured diversity among 18 bean genotypes, with 1–5 alleles per locus and polymorphism information content (PIC) values ranging from 0 to 0.772. The principal coordinate analysis (PCoA) explained 66.01% of total genetic variation and, together with the unweighted pair group method with arithmetic mean (UPGMA) clustering, clearly separated landraces from commercial controls and distinguished P. vulgaris from P. coccineus , highlighting high intra-specific variability likely linked to geographic origin and absence of formal breeding. In contrast, morphological outline analysis and nutritional profiling showed that each landrace possesses unique and distinctive traits without major intra-specific variation. All beans showed high levels of proteins (20–29%) and some accessions (pigmented seeds) had a good quantity of antioxidants and other functional compounds, reinforcing their value as nutritious and health-promoting products. Furthermore, the ecological assessment indicated a shared competitive/competitive-ruderal strategy while morphometric seed analysis explained 90.9% of total shape variation (LD1 = 60.5%; LD2 = 30.4%) and identified three main morphotypes (reniform, elliptic, roundish), without clustering consistent with species or genetic groups. The results underscore the remarkable intra-genus and intra-specific diversity within Phaseolus landraces suggesting that this variability is genetic, nutritional and phenotypic. Their cultivation (on farm conservation) and integration into local value chains could support sustainable development in marginal areas and bring new opportunities for mountain economies. Moreover, the data collected provide a scientific basis for the registration of these landraces in Italian and European agrobiodiversity registers, a key step for their protection and promotion.

The sugar beet cyst nematode（SBCN）, Heterodera schachtii Schmidt（Rhabditida: Hoplolaimidae）, was first detected in Japan in 2017 and has since been officially controlled using chemical nematicides. Resistant cultivars and cultural practices against SBCN have been investigated, and two radish cultivars have been selected as a trap crop available in Japan. However, there is limited information on the ecology of the SBCN population in Japan. Among its various ecological traits, hatching is particularly important because of its direct impact on the effectiveness of cultural control measures and the survival period of the nematode. In this study, we conducted long-term hatching tests using field-collected SBCN cysts to explore the hatching dynamics of the nematode. Hatching of SBCN second-stage juveniles（J2）continued for 28 weeks, with approximately 85% of J2 emerging within 8 weeks. Our results indicate that the hatching of SBCN under field conditions can continue for a long time.

The rapid expansion of greenhouse agriculture demands sustainable strategies to maintain soil health and productivity from the outset. Priestia megaterium, a plant growth-promoting rhizobacterium (PGPR), has shown promise in improving plant growth and soil nutrient availability, but its efficacy in newly established greenhouse systems, where the soil microbiome is still developing, remains underexplored. This study evaluated the impact of P. megaterium inoculation on cucumber growth, soil nutrient bioavailability, and soil microbial communities in a greenhouse with only two years of operation. A two-year experiment was conducted with conventional fertilization as the control and P. megaterium inoculation (7.0 × 108 cfu mL−1) at different rates (37.5, 75, 150, and 300 L ha−1) and timings. Soil and plant nutrient content were measured, and microbial communities were analyzed through 16S rRNA sequencing and co-occurrence network analysis. Results showed that applying P. megaterium at 75 L ha−1 during seedling transplantation significantly increased soil available phosphorus (AP) by 11.64–26.48% and available potassium (AK) by 11.27–47.31% compared to the control, while enhancing cucumber yield by 6.71–9.28%. The inoculant also increased soil bacterial diversity, enriched beneficial genera such as Lysobacter, Pseudomonas, and Flavobacterium, and reduced the abundance of Xanthomonas. Furthermore, P. megaterium application promoted a more complex and stable bacterial network, with higher connectivity and modularity. These findings suggest that P. megaterium is a viable strategy for enhancing soil health and productivity in newly established greenhouse systems, offering an environmentally sustainable alternative to traditional fertilization methods.

Abstract The fruits of Luffa in the Cucurbitaceae family are characterized by a bitter taste, which is mainly due to cucurbitacin. However, the types of cucurbitacins related to bitterness and the molecular mechanism of cucurbitacin accumulation during Luffa fruit growth and development are poorly understood. Here, we identified a total of 633 metabolites in Luffa , including alkaloids, flavonoids, and terpenoids, with 364 key metabolites showing significant differences between bitter and non-bitter varieties. Cucurbitacins B and D were significantly more abundant in bitter Luffa and showed an upward trend between non-bitter and extra-bitter varieties. Transcriptome analysis revealed 25,577 differentially expressed genes (DEGs) in these Luffa varieties, including the upregulation of biosynthetic pathways of terpenoids in bitter fruits. Integrative metabolite profiling and transcriptome analyses showed that LaCBS , encoding cucurbitadienol synthase, is a hub gene for the first committed step in cucurbitacin biosynthesis, located within gene clusters comprising LaP450 s and LaACT . In addition, two LaCBS genes are located within two gene clusters, alongside LaP450s and LaACT, in the interspecific hybrid of Luffa . A total of 746 DEGs were identified as transcription factors, including 103 LabHLH family members; two LabHLHs positively correlated to LaCBS and LaACT. Heat and abscisic acid stress activated the biosynthesis pathway of cucurbitacins. These findings help to elucidate the molecular mechanism of cucurbitacin biosynthesis in the bitter fruits of Luffa .

Entrepreneurship, innovation, and startup ecosystems have become central components of national development strategies, particularly in Sub-Saharan Africa, where youth unemployment, income inequality, and limited formal employment opportunities remain persistent structural challenges. This paper presents a systematic review of peer-reviewed studies published between 2020 and 2025 to examine how these interconnected elements contribute to Kenya’s socioeconomic development. Guided by the entrepreneurial passion theory and the risk-bearing theory of entrepreneurship, the review synthesizes both empirical and conceptual evidence across four thematic areas: job creation and poverty reduction; financing constraints and governance weaknesses; the role and reach of innovation hubs; and human capital and skills development. The findings indicate that entrepreneurship plays a significant role in employment generation, income creation, and technological progress in Kenya. Small and medium enterprises continue to absorb a substantial share of the labour force, particularly among youth. However, the study finds that the sector’s overall contribution to national development is limited by restricted access to affordable finance, inconsistent policy implementation, weak institutional coordination, and notable skill gaps among enterprise founders. These structural challenges reduce business survival rates and limit long-term growth. The review further finds that innovation hubs, including Nairobi’s iHub and university-based incubation centres, have created valuable support structures through mentorship, networking, and access to digital infrastructure. Despite these gains, their impact remains geographically concentrated and does not adequately address the needs of entrepreneurs operating outside major urban centres. Moreover, many programs do not sufficiently respond to practical business management and financing challenges faced by early-stage enterprises. The paper concludes that achieving Kenya’s Vision 2030 development objectives requires a coordinated and sustained strategy. The study therefore recommended that the government should strengthen entrepreneurship education, expand access to blended financing, decentralize innovation infrastructure, and improve institutional coordination to promote sustainable enterprise development in Kenya

The digital transformation of the tourism industry has significantly improved service efficiency, booking convenience, and customer experience. However, the widespread use of online platforms, electronic payments, and mobile applications has also introduced substantial cybersecurity risks, particularly concerning the protection of travelers’ personal and financial data. This paper explores the key cybersecurity threats facing the global tourism industry, with a specific focus on Kazakhstan’s emerging digital travel infrastructure. The study employs a multi-method approach, including analysis of cyber threats, a comparative review of international data protection regulations, evaluation of technical and organizational security practices, and an empirical survey involving tourism and aviation sector professionals in Kazakhstan. The findings indicate that phishing attacks, payment data breaches, and malware are among the most common threats affecting tourism businesses. These vulnerabilities are often exacerbated by outdated security systems, insufficient staff training, and limited awareness of best practices in data protection. Through a comparative analysis of cybersecurity legislation in Kazakhstan, the European Union (GDPR), the United States (CCPA), and Singapore (PDPA), the study highlights significant regulatory gaps and enforcement limitations within Kazakhstan’s legal framework. Survey results further reveal a lack of preparedness in small and medium-sized tourism enterprises, where modern security technologies and training programs are not widely adopted. Based on these insights, the paper recommends implementing multi-factor authentication, encryption protocols, regular cybersecurity audits, and employee awareness initiatives. The use of advanced technologies such as artificial intelligence and blockchain is also encouraged to enhance threat detection and data integrity. This research underscores the urgent need for a robust cybersecurity strategy in the tourism industry. By strengthening data protection measures and aligning with global standards, tourism companies can safeguard consumer trust, reduce financial risks, and support the secure digital growth of the travel sector.

Understanding the mechanisms that regulate methane (CH4) emissions from complex urban drainage systems is essential for targeted mitigation. However, the role of synoptic and local meteorological factors in shaping these mechanisms remains underexplored. Here, we adopt a systems-thinking paradigm and develop a two-stage hybrid modeling framework to disentangle meteorological controls on daily CH4 fluxes. In stage 1, time-series decomposition with piecewise structural equation modeling (PSEM) was combined to resolve causal pathways linking meteorological drivers to CH4 emissions. In stage 2, a XGBoost learner captures short-term nonlinear dynamics while explicitly accounting for temporal autocorrelation. The framework reveals a threshold-dependent, nonlinear relationship between flow rate and CH4 emissions; rainfall modulates CH4 primarily by increasing flow and perturbing system thermodynamics, while temperature and humidity modulate the response, indicating multilayered feedbacks across hydrologic and atmospheric domains. Consistent with a modified Gompertz characterization, CH4 dynamics reflect both historical system states and exogenous meteorological perturbations. The model achieves strong predictive skill (R2 = 0.879; RMSE = 0.071; KGE = 0.873) and generalizes robustly to extrapolated data sets. Methodologically, our causal–machine-learning coupling reconciles interpretability with high-fidelity prediction and provides a transferable template for diagnosing emission drivers in urban drainage networks. Substantively, it uncovers cross-layer response patterns spanning meteorological variability, in-sewer fluctuations, and CH4 flux, advancing mechanistic understanding and demonstrating the potential of soft-sensing tools to inform climate-resilient wastewater infrastructure management.