Using slow-release fertilizer is one of the sustainable strategies to improve the effectiveness of fertilizers and mitigate the environmental pollution caused by excess usage of fertilizer. In this study, a slow-release urea fertilizer with water retention and photosensitivity properties was prepared by a two-step method. It was characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, scanning electron microscopy and an infrared camera. This fertilizer can prolong the release period of urea, improve water-retention capacity of soil, and carry out photothermal conversion under illumination. Comparing four release kinetics models, the Ritger–Peppas model was the best fitting model for releasing behavior in soil, and diffusion followed the Fickian mechanism. The application of fertilizer on winter wheat was carried out to intuitively evaluate the fertilizer’s effects on promoting plant growth and resisting water stress. Thus, this study provides a new strategy for improving fertilizer utilization rate and maintaining soil moisture, which will be beneficial for sustainable agriculture.

Fertilizers that release nutrients slowly can provide crops with consistent nutrients, while soils with good water-holding capacity can alleviate the impact of droughts on crops. Sodium alginate/carboxymethyl starch sodium/polydopamine/urea (SCPU) is a new kind of slow-release fertilizer with water absorption property. In this study, the Box–Behnken response surface methodology (RSM) was used to reveal the effects of concentrations of sodium alginate, carboxymethyl starch sodium, urea, calcium chloride and dopamine on the encapsulation efficiency and water absorption of SCPU. The results show that the optimum preparation conditions to obtain the highest level of encapsulation efficiency (89.27%) and water absorption (167.05%) are 2.2% sodium alginate, 5% carboxymethyl starch sodium, 30% urea, 1.9% calcium chloride and 0.52% dopamine.

As a native crop in central Asia, pomegranate (Punica granatum L.) has been cultivated in China for more than 2000 years (Yuan et al. 2007). In August 2022, typical symptoms of anthracnose were observed on pomegranate fruitlets in the main cultivation area (34°22'36″N, 109°15'58″E) in Shaanxi Province, China. The disease incidence was approximately 10 to 15% in the field. The initial symptoms were slightly small, light, dark, sunken lesions with irregular, circular shapes. As the disease progressed, the necrotic lesions gradually expanded and merged, eventually leading to the abscission of fruits (Figure 1, A). The symptomatic lesion samples of the pomegranate were sterilized for 1.5 min in 75% ethanol and 2 min in 1% NaClO and rinsed for 2 min in sterile water three times. The sterilized samples were dried on sterile filter paper and placed on potato dextrose agar (PDA) media at 25 ℃ for 5 days. The mycelia of the isolate were white, cottony, and diffuse (Figure 1, B and C). The conidia were single-celled, smooth, aseptate, and cylindrical with slightly rounded ends, measured 13.5 to 17.5 μm long and 3.5 to 6.5 μm wide (mean 16.0 × 4.5 μm, n = 50) (Figure 1, D). These morphological characteristics were identical to those of Colletotrichum siamense (Weir et al. 2012; Cannon et al. 2012; Zhuo et al. 2022). For accurate molecular characterization of the fungus, genomic DNA was extracted from the hyphae of the two isolates using microorganism lysis buffer (Takara, Japan). The internal transcribed spacer (ITS), calmodulin (CAL), actin (ACT), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and beta-tubulin (TUB2) regions were amplified and sequenced. All the sequences were submitted to GenBank with accession numbers OQ832556 (ITS), OQ848589 (GAPDH), OQ848590 (ACT), OQ848591 (CAL), and OQ986593 (TUB2). The isolates showed 99 to 100% identity with sequences of Colletotrichum siamense (100% with GAPDH, ACT, CAL, and TUB2; 99.81% with ITS). The morphology of the strain was studied, and multilocus (ITS, GAPDH, ACT, CAL, and TUB2) phylogenetic analysis was performed (Figure 2). Therefore, the causal pathogen was identified as C. siamense based on the results of morphological and molecular analyses. Pathogenicity assays were performed on pomegranate (cv. Lishanhong) fruits. A conidial suspension (1×106 conidia/mL) was sprayed onto 10 unwounded fruits to inoculate them as infected samples, and the controls were inoculated with a sterile water suspension. All the samples were maintained in an artificial climate box at 25 ± 2 ℃ with 70% relative humidity, and the photoperiod was set as 12:12 light:dark. After 5 to 7 days, anthracnose symptoms developed on the surface of the inoculated fruit, whereas the control fruits remained healthy. The diseased fruits exhibited brown necrotic lesions, whereas the upper surfaces of the control fruits remained asymptomatic. The morphological and molecular characteristics of the reisolated pathogen were identical to those of the original fungus isolated from the natural fruit. C. siamense has been reported to cause anthracnose in the southeastern United States (Xavier et al. 2019). The pathogen causing anthracnose on pomegranates has been reported to be Colletotrichum fructicola in China (Hu et al. 2023). To our knowledge, this is the first report of anthracnose on pomegranate fruits caused by C. siamense in China. This disease can directly affect the quality and yield of the fruit. Thus, information about the characteristics of this disease could provide a theoretical basis for its prevention and control.

The computational fluid dynamics is a modern study that utilize computational methods such as the direct numerical simulation, and analyze or simulate the interested fluid mechanical models such as air foils and the turbulence model. This paper reports the acquired knowledge of a literature research and introduces the computational fluid dynamics andalgorithms of quantum computation as well as discusses examples of applications of the quantumcomputationalgorithms. Quantum computation or quantum information is an area that utilizes the properties of quanta and trytobuildvarious quantum circuits or even quantum computers. On the one hand, it has an analogy to the classical computation; onthe other hand, it also gains uniqueness and superiority at problem solving. Compared with the classical computingmethods, the quantum algorithms can be quite faster at computing with higher accuracy as well as security. Due tothedemand of improvement with respect to the computational methods in this area and the recent development in quantumcomputation field, there exists an opportunity to closely relate these two areas. By constructing new quantumalgorithms, the computing methods can be expected to be exponentially faster than classical computing methods. Aproposal israised to consider the features of the quanta and try to apply the advantages towards the computational fluid dynamics.

Liquid- and solid-state fermentation are both used to produce Eurotium cristatum-fermented Fu tea, but their final soluble products have rarely been compared directly. We compared a liquid-state fermented tea infusion (LFt-D7) with an aqueous extract of solid-state fermented Fu tea (SFt-D7), using an unfermented sterilized tea extract (SHt-D0) as the reference group. LFt-D7 developed a darker reddish-brown appearance and had higher theaflavin and theabrownin contents, lower thearubigin content, and larger Commission Internationale de l’Éclairage L*a*b* (CIELAB) color differences than SHt-D0 and SFt-D7. Liquid chromatography–tandem mass spectrometry (LC–MS/MS) profiling separated the three endpoint groups; 221, 180, and 203 Level 2 annotations met the variable importance in projection (VIP > 1) and nominal p < 0.05 screening criteria in LFt-D7 versus SHt-D0, SFt-D7 versus SHt-D0, and LFt-D7 versus SFt-D7, respectively. Targeted analyses showed substantially lower free amino acid levels in SFt-D7. LFt-D7 retained a larger soluble free-amino-acid pool, had the highest total quantified flavonoid content with a stronger flavanol contribution, and showed higher relative peak-intensity signals for selected alkaloid- and phenolic acid-related metabolites. Mantel analysis showed covariation between metabolite modules and pigment indices, CIELAB parameters, total free amino acid (FAA) content, and total quantified flavonoid content. Together, these results show that the two complete preparation routes produce different soluble chemical profiles.