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[Objective]The daylily, a perennial herb in the lily family, boasts a rich nutritional profile. Given its economic importance, enhancing its yield is a crucial objective. However, current research on daylily cultivation is limited, especially regarding three-dimensional dynamic growth simulation of daylily plants. In order to establish a technological foundation for improved cultivation management, growth dynamics prediction, and the development of plant variety types in daylily crops, this study introduces an innovative three-dimensional dynamic growth and yield simulation model for daylily plants.[Methods]The open-source GroIMP software platform was used to simulate and visualize three-dimensional scenes. With Datong daylily, the primary cultivated variety of daylily in the Datong area, as the research subject, a field experiment was conducted from March to September 2022, which covered the growth season of daylily. Through actual cultivation experiment measurements, morphological data and leaf photosynthetic physiological parameters of daylily leaves, flower stems, flower buds, and other organs were collected. The functional-structural plant model (FSPM) platform's three-dimensional modeling technology was employed to establish the Cloud Cover-based solar radiation models (CSRMs) and the Farquhar, von Camerer, and Berry model (FvCB model) suitable for daylily. Moreover, based on the source-sink relationship of daylily, the carbon allocation model of daylily photosynthetic products was developed. By using the β growth function, the growth simulation model of daylily organs was constructed, and the daily morphological data of daylily during the growth period were calculated, achieving the three-dimensional dynamic growth and yield simulation of daylily plants. Finally, the model was validated with measured data.[Results and Discussions]The coefficient of determination (R2) between the measured and simulated outdoor surface solar radiation was 0.87, accompanied by a Root Mean Squared Error (RMSE) of 28.52 W/m2. For the simulated model of each organ of the daylily plant, the R2 of the measured against the predicted values ranged from 0.896 to 0.984, with an RMSE varying between 1.4 and 17.7 cm. The R2 of the average flower bud yield simulation was 0.880, accompanied by an RMSE of 0.5 g. The overall F-value spanned from 82.244 to 1 168.533, while the Sig. value was consistently below the 0.05 significance level, suggesting a robust fit and statistical significance for the aforementioned models. Subsequently, a thorough examination of the light interaction, temperature influences, and photosynthetic attributes of daylily leaves throughout their growth cycle was carried out. The findings revealed that leaf nutrition growth played a pivotal role in the early phase of daylily's growth, followed by the contribution of leaf and flower stem nutrition in the middle stage, and finally the growth of daylily flower buds, which is the crucial period for yield formation, in the later stages. Analyzing the photosynthetic traits of daylily leaves comprehensively, it was observed that the photosynthetic rate was relatively low in the early spring as the new leaves were initially emerging and reached a plateau during the summer. Considering real-world climate conditions, the actual net photosynthetic rate was marginally lower than the rate verified under optimal conditions, with the simulated net assimilation rate typically ranging from 2 to 4 μmol CO2/(m2·s).[Conclusions]The three-dimensional dynamic growth model of daylily plants proposed in this study can faithfully articulate the growth laws and morphological traits of daylily plants across the three primary growth stages. This model not only illustrates the three-dimensional dynamic growth of daylily plants but also effectively mimics the yield data of daylily flower buds. The simulation outcomes concur with actual conditions, demonstrating a high level of reliability.

A simple and efficient photometric methodology is presented, covering all steps from field data acquisition to binarization and allowing for leaf contour modelling. This method comprises the modelling of area and size (correlated and modelled with a Chapman-Richards growth function, using final length as one parameter), and four shape descriptors, from which the entire contour can be reconstructed rather well using a specific spline methodology. As an improvement of this contour modelling method, a set of parameterized polynomials was used. To model the temporal kinetics of the shape, geodesics in shape spaces were employed. Finally it is shown how this methodology is integrated into the 3D modelling platform GroIMP.

In the wake of technological innovation, supply chain transparency has become a concrete avenue for long-awaited improvements to supply chain processes and practices. Transparency is of particular interest to Supply Chain Finance; however, it is yet empirically unknown whether and how benefits would materialise. Being at the interface of finance and operations, Supply Chain Finance aims at improving the inter-company management of financial flows. Nowadays, different financing schemes are offered foremost by cooperation between financial institutions and fintechs. Uncertainty remains on whether and how supply chain transparency would benefit these schemes to allow the adoption of more sophisticated, higher-value schemes. By applying the Gioia method, we analysed a series of interviews with experts from the Supply Chain Finance industry regarding transaction cost economics, agency theory, and dynamic capability. The resulting series of pragmatic, theory-grounded but practice-inspired propositions untangle the relationship and barriers between supply chain transparency and Supply Chain Finance. The propositions provide advances in the theoretical understanding of Supply Chain Finance and uncover relevant directions for future research. This poses the base for actionable results in future research and leads to an impact in research by addressing the concerns and tensions raised by Supply Chain Finance experts. [ABSTRACT FROM AUTHOR]

Introduction: Optimizing the dynamics of daylily (Hemerocallis citrina Baroni) growth under various planting patterns is critical for enhancing production efficiency. This study presents a comprehensive model to simulate daylily growth and optimize planting patterns to maximize bud yield while minimizing land resource utilization. Methods: The model incorporates source-sink relationship specific to daylilies into physiological process modeling, considering environmental factors such as micro-light and temperature climate, and CO2 concentration. Spatial factors, including planting pattern, row spacing, plant spacing, and plant density were examined for their impact on light interception, photosynthesis, and resource efficiency. Employing partial least square path modeling (PLS-PM), we analyzed the interrelations and causal relationships between planting configurations and physiological traits of daylily canopy leaves and buds. Through in situ simulations of 36 planting scenarios, we identified an optimal configuration (Scenario ID5) with a density of 83,000 plants·ha−1, row spacing of 0.8 m, and equidistant planting with a plant spacing of 0.15 m. Results and discussion: Our research findings indicate that increased Wide+Narrow row spacing can enhance yield to a certain extent. Although planting patterns influence daylily yield, their overall impact is relatively minor, and there is no clear pattern regarding the impact of plant spacing on individual plant yield. This modeling approach provides valuable insights into daylily plant growth dynamics and planting patterns optimization, offering practical guidance for both farmers and policymakers to enhance daylily productivity while minimizing land use. [ABSTRACT FROM AUTHOR]

Purpose: Digital platforms transform supply chains. However, no unified theoretical understanding of digital platforms exists. Thus, the underlying research aims at investigating platform theories for supply chain management tasks. Design/methodology/approach: The authors conduct a systematic literature review to identify relevant theories in the context of digital platforms and synthesize the respective findings for supply chain management tasks. Findings: In total, 43 papers and 41 different relevant theories are identified. The most prominent theories are the resource-based view, transaction cost economics, internalization theory and the dynamic capabilities approach. Digital platforms alter and change the boundary decisions of firms. Therefore, they have various implications for supply chain management tasks such as make-or-buy decisions or the orchestration of resources to sustain a competitive advantage. Practical implications: The identified supply chain theories as well as platform theories and their overlap provide a meaningful starting point for discussing and developing new and platform-based supply chain management approaches in the B2B domain. Originality/value: The conducted systematic literature review provides a first starting point for building a holistic theoretical approach to digital platforms in supply chains. Thus, the paper contributes a missing link for discussing digital platforms and their theoretical foundations for supply chain management tasks. [ABSTRACT FROM AUTHOR]