Evaluating Winter Malting Barley Grain Yield with Fractional Green Canopy Cover

Because of growth in the craft brewing industry, farmers in the eastern United States are planting winter malting barley (Hordeum vulgare L.) to meet demands for locally sourced grain. However, given that barley is a relatively new crop in this region, basic agronomic information relating to stand assessment is needed. This is particularly relevant in this region, as climatic variability from extreme temperature fluctuations during the winter and spring can reduce a barley stand, creating the need for farmers to estimate grain yield potential. The objective of the research was to evaluate the relationship between spring stem counts, fractional green canopy cover (FGCC), and normalized difference vegetation index (NDVI) and barley grain yield. Trials were established at five site-years in Ohio, where seeding rate treatments of 0.75, 1.0, 1.5, 2.0 and 2.5 million seeds acre−1 were used to simulate a range of poor to excellent plant stands. All barley stand assessment methods were conducted in the spring at the Feekes 5 growth stage. Stem counts were correlated with FGCC and NDVI measurements (r = .76 and .74, respectively). Stem counts (R2 = .67) and FGCC (R2 = .65) measurements accounted for the greatest variability in barley grain yield. Specifically, FGCC ≤5% corresponded to yield between 27 and 39 bu acre−1, whereas 5 to 10% corresponded to yield between 60 and 89 bu acre−1. Fractional green canopy cover should be considered as a stand and yield assessment tool, as it reduces labor compared with stem counting techniques

Programming of central and peripheral insulin resistance by low birthweight and postnatal catch-up growth in male mice.

AIMS: Intra-uterine growth restriction (IUGR) followed by accelerated postnatal growth is associated with an increased risk of obesity and type 2 diabetes. We aimed to determine central and peripheral insulin sensitivity in mice that underwent IUGR followed by postnatal catch-up growth and investigate potential molecular mechanisms underpinning their physiology. METHODS: We used a C57BL/6J mouse model of maternal diet-induced IUGR (maternal diet, 8% protein) followed by cross-fostering to a normal nutrition dam (maternal diet, 20% protein) and litter size manipulation to cause accelerated postnatal catch-up growth. We performed intracerebroventricular insulin injection and hyperinsulinaemic-euglycaemic clamp studies to examine the effect of this early nutritional manipulation on central and peripheral insulin resistance. Furthermore, we performed quantitative real-time PCR and western blotting to examine the expression of key insulin-signalling components in discrete regions of the hypothalamus. RESULTS: IUGR followed by accelerated postnatal growth caused impaired glucose tolerance and peripheral insulin resistance. In addition, these 'recuperated' animals were resistant to the anorectic effects of central insulin administration. This central insulin resistance was associated with reduced protein levels of the p110β subunit of phosphoinositide 3-kinase (PI3K) and increased serine phosphorylation of IRS-1 in the arcuate nucleus (ARC) of the hypothalamus. Expression of the gene encoding protein tyrosine phosphatase 1B (PTP1B; Ptpn1) was also increased specifically in this region of the hypothalamus. CONCLUSIONS/INTERPRETATION: Mice that undergo IUGR followed by catch-up growth display peripheral and central insulin resistance in adulthood. Recuperated offspring show changes in expression/phosphorylation of components of the insulin signalling pathway in the ARC. These defects may contribute to the resistance to the anorectic effects of central insulin, as well as the impaired glucose homeostasis seen in these animals

Characterizing the Decision Process in Setting Corn and Soybean Seeding Rates

Selecting optimal corn and soybean seeding rates are difficult decisions to make. A survey of Ohio and Michigan farm operators finds that, although generally keen to learn from others, they tend to emphasize their own experience over outside information sources. Soybean growers declare university and extension recommendations as more important than do corn growers. In response to direct queries and in free comments, growers place more emphasis on understanding the agronomic and technological problems at hand than on adjusting to the market environment. Given the decision environment, we argue that these responses are reasonable

Field validation of a farmer supplied data approach to close soybean yield gaps in the US North Central region

CONTEXT: Producer-reported data can be used to identify suites of management practices that lead to higher yield and profit. However, a rigorous validation of the approach in relation to its potential impact on farmer yield and profit is lacking. OBJECTIVE: This study aimed to validate a producer-data approach on its capability to guide on-farm evaluation of management practices with greatest potential for increasing producer yield and profit. We show proof of concept using soybean in the North Central US region as a case study. METHODS: We used a combination of regression tree analysis and a spatial framework to determine practices with highest influence on yield for specific climate domains across the region. These practices were used as a basis for designing an ‘improved’ management package for each domain. The impact associated with adoption of the ‘improved’ management package on producer yield, seed constituents, and profit was evaluated against a ‘reference’ treatment that follows farmer management via replicated on-farm trials across 100 sites over two crop seasons. RESULTS AND CONCLUSIONS: Average yield was 278 kg ha-1 higher in the improved versus reference management, equivalent to a closure of the current exploitable yield gap by 40%. In turn, adoption of the improved management led to an average increase of $76 ha-1 in net profit. Sensitivity analysis showed that adoption of the improved management packages should increase farmer profit across a wide range of grain price scenarios, with very small downside risk. Seed protein concentration was negatively associated with the positive yield advantage of the improved management, whereas seed oil concentration tended to increase. SIGNIFICANCE: Analysis of producer data can accelerate discovery, evaluation, and adoption of suites of management practices that consistently lead to higher farmer yield and profit, which, in turn, would help speed up current rates of yield gain

Archaeology and modern reflections on death

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Emotion Regulation Predicts Pain and Functioning in Children With Juvenile Idiopathic Arthritis: An Electronic Diary Study

Objectives This study utilized e-diaries to evaluate whether components of emotion regulation predict daily pain and function in children with juvenile idiopathic arthritis (JIA). Methods 43 children ages 8–17 years and their caregivers provided baseline reports of child emotion regulation. Children then completed thrice daily e-diary assessments of emotion, pain, and activity involvement for 28 days. E-diary ratings of negative and positive emotions were used to calculate emotion variability and to infer adaptive emotion modulation following periods of high or low emotion intensity. Hierarchical linear models were used to evaluate how emotion regulation related to pain and function. Results The attenuation of negative emotion following a period of high negative emotion predicted reduced pain; greater variability of negative emotion predicted higher pain and increased activity limitation. Indices of positive emotion regulation also significantly predicted pain. Conclusions Components of emotion regulation as captured by e-diaries predict important health outcomes in children with JIA

Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing

With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large‐scale genomic testing effort. We preserve the provision of pre‐test education and informed consent as established in Mendelian/single‐gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post‐counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow‐up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147027/1/jgc41111.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147027/2/jgc41111-sup-0001.pd