A multi-attribute approach to evaluating the impact of biostimulants on crop performance.

An ever-growing collection of commercial biostimulants is becoming available in a wide variety of forms and compositions to improve crop performance. Given the intricate nature of deciphering the underlying mechanisms of commercial products, which typically comprise various biological components, it is crucial for research in this area to have robust tools to demonstrate their effectiveness in field trials. Here, we took a multi-attribute approach to evaluating the impact of biostimulants on crop performance. First, we assessed the impact of a biostimulant on the soil and rhizosphere microbiomes associated to crops in eight reference farms, including corn (3 farms), soybean (2), cotton (2) and sugarcane (1), in different biomes and production contexts in Brazil and Paraguay. Second, we modeled a set of integrated indicators to measure crop responses to biostimulant application, including five analytical themes as follows: i) crop development and production (9 indicators), ii) soil chemistry (9), iii) soil physics (5), iv) soil biology (6) and v) plant health (10). Amplicon 16S rRNA and ITS sequencing revealed that the use of the biostimulant consistently changes the structure of bacterial and fungal communities associated with the production system for all evaluated crops. In the rhizosphere samples, the most responsive bacterial taxa to biostimulant application were Prevotella in cotton; Prauserella and Methylovirgula in corn; and Methylocapsa in sugar cane. The most responsive fungal taxa to biostimulant use were Arachnomyces in soybean and cotton; and Rhizophlyctis in corn. The proposed integrated indicators yielded highly favorable positive impact indices (averaging at 0.80), indicating that biostimulant-treated fields correlate with better plant development and crop performance. Prominent indices were observed for indicators in four themes: soil biology (average index 0.84), crop production (0.81), soil physics (compaction reduction 0.81), and chemical fertility (0.75). The multi-attribute approach employed in this study offers an effective strategy for assessing the efficacy of biostimulant products across a wide range of crops and production systems

A reduced-order strategy for 4D-Var data assimilation

This paper presents a reduced-order approach for four-dimensional variational data assimilation, based on a prior EO F analysis of a model trajectory. This method implies two main advantages: a natural model-based definition of a mul tivariate background error covariance matrix $\textbf{B}_r$, and an important decrease of the computational burden o f the method, due to the drastic reduction of the dimension of the control space. % An illustration of the feasibility and the effectiveness of this method is given in the academic framework of twin experiments for a model of the equatorial Pacific ocean. It is shown that the multivariate aspect of $\textbf{B}_r$ brings additional information which substantially improves the identification procedure. Moreover the computational cost can be decreased by one order of magnitude with regard to the full-space 4D-Var method

An international survey of the structure and process of care for traumatic spinal cord injury in acute and rehabilitation facilities : lessons learned from a pilot study

BACKGROUND: To describe the key findings and lessons learned from an international pilot study that surveyed spinal cord injury programs in acute and rehabilitation facilities to understand the status of spinal cord injury care. METHODS: An online survey with two questionnaires, a 74-item for acute care and a 51-item for rehabilitation, was used. A subset of survey items relevant to the themes of specialized care, timeliness, patient-centeredness, and evidence-based care were operationalized as structure or process indicators. Percentages of facilities reporting the structure or process to be present, and percentages of indicators met by each facility were calculated and reported separately for facilities from high-income countries (HIC) and from low and middle-income countries (LMIC) to identify "hard to meet" indicators defined as those met by less than two-thirds of facilities and to describe performance level. RESULTS: A total of 26 acute and 26 rehabilitation facilities from 25 countries participated in the study. The comparison of the facilities based on the country income level revealed three general observations: 1) some indicators were met equally well by both HIC and LMIC, such as 24-hour access to CT scanners in acute care and out-patient services at rehabilitation facilities; 2) some indicators were hard to meet for LMIC but not for HIC, such as having a multidisciplinary team for both acute and rehabilitation settings; and 3) some indicators were hard to meet by both HIC and LMIC, including having peer counselling programs. Variability was also observed for the same indicator between acute and rehabilitation facilities, and a wide range in the total number of indicators met among HIC facilities (acute 59-100%; rehabilitation 36-100%) and among LMIC facilities (acute: 41-82%; rehabilitation: 36-93%) was reported. CONCLUSIONS: Results from this international pilot study found that the participating acute and rehabilitation facilities on average adhered to 74% of the selected indicators, suggesting that the structure and processes to provide ideal traumatic spinal cord injury care were broadly available. Recruiting a representative sample of SCI facilities and incorporating regional attributes in future surveys will be helpful to examine factors affecting adherence to indicators.publishedVersionPeer reviewe