Cross-validation of stagewise mixed-model analysis of Swedish variety trials with winter wheat and spring barley

In cultivar testing, linear mixed models have been used routinely to analyze multienvironment trials. A single‐stage analysis is considered as the gold standard, whereas two‐stage analysis produces similar results when a fully efficient weighting method is used, namely when the full variance–covariance matrix of the estimated means from Stage 1 is forwarded to Stage 2. However, in practice, this may be hard to do and a diagonal approximation is often used. We conducted a cross‐validation with data from Swedish cultivar trials on winter wheat (Triticum aestivum L.) and spring barley (Hordeum vulgare L.) to assess the performance of single‐stage and two‐stage analyses. The fully efficient method and two diagonal approximation methods were used for weighting in the two‐stage analyses. In Sweden, cultivar recommendation is delineated by zones (regions), not individual locations. We demonstrate the use of best linear unbiased prediction (BLUP) for cultivar effects per zone, which exploits correlations between zones and thus allows information to be borrowed across zones. Complex variance–covariance structures were applied to allow for heterogeneity of cultivar × zone variance. The single‐stage analysis and the three weighted two‐stage analyses all performed similarly. Loss of information caused by a diagonal approximation of the variance–covariance matrix of adjusted means from Stage 1 was negligible. As expected, BLUP outperformed best linear unbiased estimation. Complex variance–covariance structures were dispensable. To our knowledge, this study is the first to use cross‐validation for comparing single‐stage analyses with stagewise analyses

Adding Natural Frequency Data to a Decision Aid for Colorectal Cancer Screening: Results of a Randomized Trial

Guidelines recommend that decision aids provide natural frequency data regarding baseline risk, risk reduction, and chances of false positives and negatives. Such quantitative information may confuse patients, especially those with low numeracy. We conducted a randomized trial to compare effects of 2 colorectal cancer (CRC) screening decision aids—one with and one without natural frequency data

Differenzialdiagnose: Eine Methode zur Ursacheneingrenzung bei Bodenmüdigkeit

Fertile soils are highly important for arable farming. To maintain soil fertility, crop rotation including legumes is applied, particularly in stockless farms. Yet, many commercial farms report yield reductions for legumes. The aim of the present study was to evaluate whether the causes for the observed soil fatigue can be narrowed down by a bioassay (modified differential diagnosis according to Bouhot) and whether this bioassay could be a useful tool to predict the suitability of a field to grow legumes

Presenting Stool Testing as the Default Option for Colorectal Cancer Screening: Results of a Randomized Trial

Individuals eligible for colorectal cancer (CRC) screening can choose from multiple approved tests, including colonoscopy and stool testing. The existence of multiple options allows patients to choose a preferred strategy but also may lead to indecision and delay. Behavioral economics suggests presenting one option as a default choice, i.e. the one that patients should receive if they do not wish to decide. We conducted a randomized trial to measure the impact of describing stool testing as the default option for CRC screening in a decision aid (DA)

The effect of organic and conventional management on the yield and quality of wheat grown in a long-term field trial

The performance of winter wheat was evaluated under organic (ORG) and conventional (CON) management systems in the Nafferton Factorial Systems Comparison (NFSC) long-term field trial. The present study separates out the crop protection and fertility management components of organic and conventional production systems using two levels each of crop protection (CP) and fertility management (FM). The experimental design provided the four combinations of crop protection and fertility (CON-CP CONFM, CON-CP ORG-FM, ORG-CP CON-FM and ORG-CP ORG-FM) to evaluate their effects on yield, quality (protein content and hectolitre weight) and disease levels during the period 2004–2008. The conventional management system (CON-CP CON-FM) out-yielded the organic management system (ORG-CP ORG-FM) in all years by an average of 3.1 t ha−1, i.e. 7.9 t ha−1 vs. 4.8 t ha−1. Fertility management was the key factor identified limiting both yield and grain protein content in the ORG management system. The CON-FM produced on average a 3% higher protein content than ORG-FM in all years (12.5% vs. 9.7%). However the ORG-CP system produced higher protein levels than CON-CP although it was only in 2008 that this was statistically significant. In contrast to protein content it was ORG-FM which produced a higher hectolitre weight than the CON-FM system (71.6 kg hl−1 vs. 71.0 kg hl−1). The clear and significant differences in yield and protein content between the ORG-FM and CON-FM systems suggest a limited supply of available N in the organic fertility management system which is also supported by the significant interaction effect of the preceding crop on protein content. The pRDA showed that although fertilisation had the greatest effect on yield, quality and disease there was also a considerable effect of crop protection and the environment