EFFECTS OF HIGH AND LOW MANAGEMENT INTENSITY ON PROFITABILITY FOR THREE WATERMELON GENOTYPES

A replicated, small plot study on watermelon [Citrullus lanatus (Thunberg) Matsumura and Nakai] in 1997, 1999, and 2000 revealed that production management intensity affected yields and profitability of watermelon, in Oklahoma. Management intensity was based on a combination of cultural practices and levels of use of production methods. Low intensity management (LM) consisted of use of soil fertilization and weed control. High intensity management (HM) included the same weed control and fertilization as LM but also included use of plastic mulch, drip irrigation, insect pest control, and plant disease control. Cost and return analyses were based on the range of actual prices during the cropping season and the range of yields during the three years. Yields from the seedless triploid genotype 'Gem Dandy' consistently resulted in greater positive net revenue under HM than the diploid open pollinated 'Allsweet' or the hybrid diploid 'Sangria'. Under LM, yields from the seedless triploid also resulted in greater net revenues when conditions were favorable or lost less money than the open pollinated 'Allsweet' or the hybrid diploid 'Sangria' when conditions were unfavorable.Crop Production/Industries,

Effect of increasing fruit and vegetable intake by dietary intervention on nutritional biomarkers and attitudes to dietary change : a randomised trial

This work was funded by The Scottish Government Rural and Environmental Science and Analytical Sciences Division (RESAS) and supported by the Rank Prize Funds.Peer reviewedPublisher PD

Archaeal abundance in post-mortem ruminal digesta may help predict methane emissions from beef cattle

The Rowett Institute of Nutrition and Health and SRUC are funded by the Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government. The project was supported by DEFRA and DA funded Agricultural Greenhouse Gas Inventory Research Platform. Our thanks are due to the excellent support staff at the SRUC Beef Research Centre, Edinburgh, also to Graham Horgan of BioSS, Aberdeen, for conducting multivariate analysis.Peer reviewedPublisher PD

Adoption of precision livestock farming technologies has the potential to mitigate greenhouse gas emissions from beef production

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometer based sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kgCO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3  months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems

Adoption of precision livestock farming technologies has the potential to mitigate greenhouse gas emissions from beef production

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometer based sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kgCO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3  months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems

The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm

Precision livestock farming (PLF) tools are increasingly used in daily herd management to improve health, welfare, and overall production. While not intended to reduce greenhouse gas (GHG) emissions on farm, PLF tools can do so indirectly by improving overall efficiency, thereby reducing the emissions per unit of product. This work modelled the potential effects of commercially available PLF tools on whole enterprise and product emissions of two average Scottish dairy farm systems (an 8,000  L and 10,000  L herd) using the Agrecalc carbon foot printing tool. Scenarios modelled included an improvement infertility and an improvement in fertility and yield from the introduction of an accelerometer-based sensor, and an improvement in health from introduction of an accelerometer-based sensor, with and without the use of management interventions. Use of a sensor intended to improve fertility had the large streduction in total emissions (kg CO2e) of −1.42% for a 10,000  L farm, with management changes applied. The largest reduction in emissions from milk production (kg CO2e) of −2.31% was observed via fertility technology application in an 8,000  L farm, without management changes. The largest reduction in kg CO2e per kg fat and protein corrected milk of −6.72% was observed from an improvement in fertility and yield in a 10,000  L herd, with management changes. This study has highlighted the realistic opportunities available to dairy farmers in low and high input dairy systems to reduce their emissions through adoption of animal mounted PLF technologies

Patient satisfaction with lower gastrointestinal endoscopy: doctors, nurse and nonmedical endoscopists

Aim Assessment of patient satisfaction with lower gastrointestinal endoscopy (LGE) comprising colonoscopy and flexible sigmoidoscopy is gaining increasing importance. We have now trained non healthcare professionals such as nonmedical endoscopists (NMEs) to perform LGE to overcome shortage of trained endoscopists. The aim of this study was to prospectively determine patient satisfaction, factors affecting satisfaction with LGE and to compare with nurses, NME and medical endoscopists, in terms of patient satisfaction. Method Consecutive patients undergoing LGE answered specially developed patient satisfaction questionnaire at discharge and 24 h thereafter. This questionnaire was a modification of m-Group Health Association of America questionnaire. Construct and face validity of questionnaire were tested by an expert group. Demographic and clinical data was prospectively collected. Multivariate regression analysis was performed to determine factors influencing patient satisfaction. Results Some 503 patients were surveyed after LGE. Examinations were performed by nurse (n = 105), doctor (n = 191), or NMEs (n = 155). There were no differences between three groups in terms of completion rates/complications. No differences were detected between endoscopists in patient rating for overall satisfaction (P = 0.6), technical skills (P = 0.58), communication skills (P = 0.61) or interpersonal skills (0.59). Multivariate regression analysis showed that higher preprocedure anxiety, history of pelvic operations/hysterectomy and higher pain scores were associated with adverse patient satisfaction and preprocedure anxiety, history of hysterectomy and female gender were associated with higher pain scores. Conclusion This study has shown that there are no differences in patient satisfaction with LGE performed by nurse, doctor or NME. The most important factor affecting patient satisfaction is degree of discomfort/pain experienced by patient

Expression of KOC, S100P, mesothelin and MUC1 in pancreatico-biliary adenocarcinomas: development and utility of a potential diagnostic immunohistochemistry panel

<b>Background</b> Pancreatico-biliary adenocarcinomas (PBA) have a poor prognosis. Diagnosis is usually achieved by imaging and/or endoscopy with confirmatory cytology. Cytological interpretation can be difficult especially in the setting of chronic pancreatitis/cholangitis. Immunohistochemistry (IHC) biomarkers could act as an adjunct to cytology to improve the diagnosis. Thus, we performed a meta-analysis and selected KOC, S100P, mesothelin and MUC1 for further validation in PBA resection specimens.<p></p> <b>Methods</b> Tissue microarrays containing tumour and normal cores in a ratio of 3:2, from 99 surgically resected PBA patients, were used for IHC. IHC was performed on an automated platform using antibodies against KOC, S100P, mesothelin and MUC1. Tissue cores were scored for staining intensity and proportion of tissue stained using a Histoscore method (range, 0–300). Sensitivity and specificity for individual biomarkers, as well as biomarker panels, were determined with different cut-offs for positivity and compared by summary receiver operating characteristic (ROC) curve.<p></p> <b>Results</b> The expression of all four biomarkers was high in PBA versus normal ducts, with a mean Histoscore of 150 vs. 0.4 for KOC, 165 vs. 0.3 for S100P, 115 vs. 0.5 for mesothelin and 200 vs. 14 for MUC1 (p < .0001 for all comparisons). Five cut-offs were carefully chosen for sensitivity/specificity analysis. Four of these cut-offs, namely 5%, 10% or 20% positive cells and Histoscore 20 were identified using ROC curve analysis and the fifth cut-off was moderate-strong staining intensity. Using 20% positive cells as a cut-off achieved higher sensitivity/specificity values: KOC 84%/100%; S100P 83%/100%; mesothelin 88%/92%; and MUC1 89%/63%. Analysis of a panel of KOC, S100P and mesothelin achieved 100% sensitivity and 99% specificity if at least 2 biomarkers were positive for 10% cut-off; and 100% sensitivity and specificity for 20% cut-off.<p></p> <b>Conclusion</b> A biomarker panel of KOC, S100P and mesothelin with at least 2 biomarkers positive was found to be an optimum panel with both 10% and 20% cut-offs in resection specimens from patients with PBA.<p></p&gt