Improving in vivo plant nitrogen content estimates from digital images: trueness and precision of a new approach as compared to other methods and commercial devices

Operational tools to support nitrogen (N) management in cropping systems are increasingly needed to maximise profit, minimise environmental impact, and to cope with market requirements. In this study, a new method (18%-grey DGCI) for estimating leaf and plant N content from digital photography was evaluated and compared with others based on image processing (DGCI and Corrected DGCI) and with commercial tools (leaf colour chart, SPAD-502, and Dualex 4). All methods were evaluated for rice using data collected in northern Italy in 2013, by adapting the ISO 5725-2 validation protocol. 18%-grey DGCI was further validated on independent data collected in 2014. Dualex achieved the best performances for trueness (R2 = 0.96 and 0.92 for leaf and plant N contents), although it presented partly unsatisfying values for precision (12.33% for repeatability and 14.81% for reproducibility). SPAD, instead, demonstrated the highest precision (repeatability = 4.51%, reproducibility = 4.98%), even if it was ranked third for trueness (R2 = 0.82 and 0.81 for leaf and plant N contents). 18%-grey DGCI was ranked second for trueness (R2 = 0.83 for both leaf and plant N contents) and third for precision (11.11% and 14.47% for repeatability and reproducibility). The good performances of the new method were confirmed during the 2014 experiment (R2 = 0.87 for leaf N content). The 18%-grey DGCI method has been implemented in a smartphone app (PocketN) to provide farmers and technicians with a low-cost diagnostic tool for supporting N management at field level in contexts characterised by low availability of resource

Understanding Factors Associated With Psychomotor Subtypes of Delirium in Older Inpatients With Dementia

Objectives: Few studies have analyzed factors associated with delirium subtypes. In this study, we investigate factors associated with subtypes of delirium only in patients with dementia to provide insights on the possible prevention and treatments. Design: This is a cross-sectional study nested in the “Delirium Day” study, a nationwide Italian point-prevalence study. Setting and Participants: Older patients admitted to 205 acute and 92 rehabilitation hospital wards. Measures: Delirium was evaluated with the 4-AT and the motor subtypes with the Delirium Motor Subtype Scale. Dementia was defined by the presence of a documented diagnosis in the medical records and/or prescription of acetylcholinesterase inhibitors or memantine prior to admission. Results: Of the 1057 patients with dementia, 35% had delirium, with 25.6% hyperactive, 33.1% hypoactive, 34.5% mixed, and 6.7% nonmotor subtype. There were higher odds of having venous catheters in the hypoactive (OR 1.82, 95% CI 1.18-2.81) and mixed type of delirium (OR 2.23, CI 1.43-3.46), whereas higher odds of urinary catheters in the hypoactive (OR 2.91, CI 1.92-4.39), hyperactive (OR 1.99, CI 1.23-3.21), and mixed types of delirium (OR 2.05, CI 1.36-3.07). We found higher odds of antipsychotics both in the hyperactive (OR 2.87, CI 1.81-4.54) and mixed subtype (OR 1.84, CI 1.24-2.75), whereas higher odds of antibiotics was present only in the mixed subtype (OR 1.91, CI 1.26-2.87). Conclusions and Implications: In patients with dementia, the mixed delirium subtype is the most prevalent followed by the hypoactive, hyperactive, and nonmotor subtype. Motor subtypes of delirium may be triggered by clinical factors, including the use of venous and urinary catheters, and the use of antipsychotics. Future studies are necessary to provide further insights on the possible pathophysiology of delirium in patients with dementia and to address the optimization of the management of potential risk factors