ABSTRACT
Accurate prediction of flowering times is essential for efficient orchard management for kiwifruit, facilitating timely pest and disease control and pollination interventions. In this study, we developed a predictive model for flowering time using weather data and observations of budbreak dynamics for the 'Hayward' and 'Zesy002' kiwifruit. We used historic data of untreated plants collected from 32 previous studies conducted between 2007 and 2022 and analyzed budbreak and flowering timing alongside cumulative heat sum (growing degree days, GDDs), chilling unit (CU) accumulation, and other environmental variables using weather data from the weather stations nearest to the study orchards. We trained/parameterized the model with data from 2007 to 2019, and then evaluated the model's efficacy using testing data from 2020 to 2022. Regression models identified a hierarchical structure with the accumulation of GDDs at the start of budbreak, one of the key predictors of flowering time. The findings suggest that integrating climatic data with phenological events such as budbreak can enhance the predictability of flowering in kiwifruit vines, offering a valuable tool for kiwifruit orchard management.
ABSTRACT
Bringing biobased nanomaterials into polymer manufacturing is essential to enhance polymers' properties and address the challenges posed by plastic waste. Using polymers such as polyamide 6 (PA6) in advanced industries, e.g., automotive sector, has been impeded as a direct consequence of their inability to meet the required mechanical properties. Herein, we utilize bio-based cellulose nanofibers (CNFs) to enhance the properties of PA6 by green processing, with no footprint on the environment. We address the issue of the dispersion of the nanofillers in polymeric matrices and demonstrate direct milling (cryo-milling and planetary ball milling) to facilitate a thorough integration of the components. Nanocomposites incorporating 1.0 wt% CNF, processed by pre-milling followed by compression molding, are shown to possess a storage modulus of 3.8 ± 0.2 GPa, Young's modulus of 2.9 ± 0.2 GPa, and ultimate tensile strength of 63 ± 3 MPa (all measured at room temperature). To show the superiority of direct milling in achieving these properties, other frequent approaches used to disperse CNF in polymers, such as solvent casting and hand mixing, are meticulously investigated and compared for the performance of their resulting specimens. The ball-milling method is demonstrated to provide PA6-CNF nanocomposites with excellent performance, better than solvent casting, with no associated environmental concerns.
ABSTRACT
SARS-CoV-2 has caused over 100,000,000 cases and almost 2,500,000 deaths globally. Comprehensive assessment of the multifaceted antiviral Ab response is critical for diagnosis, differentiation of severity, and characterization of long-term immunity, especially as COVID-19 vaccines become available. Severe disease is associated with early, massive plasmablast responses. We developed a multiplex immunoassay from serum/plasma of acutely infected and convalescent COVID-19 patients and prepandemic and postpandemic healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 nucleocapsid (N), spike domain 1 (S1), S1-receptor binding domain (RBD) and S1-N-terminal domain. For diagnosis, the combined [IgA + IgG + IgM] or IgG levels measured for N, S1, and S1-RBD yielded area under the curve values ≥0.90. Virus-specific Ig levels were higher in patients with severe/critical compared with mild/moderate infections. A strong prozone effect was observed in sera from severe/critical patients-a possible source of underestimated Ab concentrations in previous studies. Mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared with severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 mo after symptom onset. Measurement of the Ab responses in sera from 18 COVID-19-vaccinated patients revealed specific responses for the S1-RBD Ag and none against the N protein. This highly sensitive, SARS-CoV-2-specific, multiplex immunoassay measures the magnitude, complexity, and kinetics of the Ab response and can distinguish serum Ab responses from natural SARS-CoV-2 infections (mild or severe) and mRNA COVID-19 vaccines.