Abstract: Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at evaluating the effect of temperature and humidity on milk production in highly selected dairy cattle populations across 3 European regions differing in climate and production systems to detect differences and similarities that can be used to optimize heat stress (HS) effect modeling. Milk, fat, and protein test day data from official milk recording for 1999 to 2010 in 4 Holstein populations located in the Walloon Region of Belgium (BEL), Luxembourg (LUX), Slovenia (SLO), and southern Spain (SPA) were merged with temperature and humidity data provided by the state meteorological agencies. After merging, the number of test day records/cows per trait ranged from 686,726/49,655 in SLO to 1,982,047/136,746 in BEL. Values for the daily average and maximum temperature-humidity index (THIavg and THImax) ranges for THIavg/THImax were largest in SLO (22-74/28-84) and shortest in SPA (39-76/46-83). Change point techniques were used to determine comfort thresholds, which differed across traits and climatic regions. Milk yield showed an inverted U-shaped pattern of response across the THI scale with a HS threshold around 73 THImax units. For fat and protein, thresholds were lower than for milk yield and were shifted around 6 THI units toward larger values in SPA compared with the other countries. Fat showed lower HS thresholds than protein traits in all countries. The traditional broken line model was compared with quadratic and cubic fits of the pattern of response in production to increasing heat loads. A cubic polynomial model allowing for individual variation in patterns of response and THIavg as heat load measure showed the best statistical features. Higher/lower producing animals showed less/more persistent production (quantity and quality) across the THI scale. The estimated correlations between comfort and THIavg values of 70 (which represents the upper end of the THIavg scale in BEL-LUX) were lower for BEL-LUX (0.70-0.80) than for SPA (0.83-0.85). Overall, animals producing in the more temperate climates and semi-extensive grazing systems of BEL and LUX showed HS at lower heat loads and more re-ranking across the THI scale than animals producing in the warmer climate and intensive indoor system of SPA.

Abstract: A field experiment was conducted in Southern Italy to evaluate the effects of different water quality and fertilizers on yield performance of tomato crop. In mineral nitrogen (N) fertilizer and irrigation with fresh water (Electrical Conductivity, EC, = 0.9 dS m⁻¹) (FWF); mineral N fertilizer and irrigation with saline water (EC = 6.0 dS m⁻¹) (SWF); municipal solid waste (MSW) compost and irrigation with fresh water (EC = 0.9 dS m⁻¹) (FWC); MSW compost and irrigation with saline water (EC = 6.0 dS m⁻¹) (SWC). At harvest, weight and number of fruits and refractometric index (°Brix) were measured, total and marketable yield and dry matter of fruit were calculated. The results indicated that MSW compost, applied as amendment, could substitute the mineral fertilizer. In fact, in the treatments based on compost application, the tomato average marketable yield increased by 9% compared with treatments with mineral fertilizer. The marketable yield in the SWF and SWC treatments (with an average soil EC in two years to about 3.5 dS m⁻¹) decreased respectively of 20 and 10%, in respect to fresh water treatments. At the end of the experiment, application of compost significantly decreased the sodium absorption rate (SAR) of SWC treatment in respect of SWF (−29.9%). Significant differences were observed among the four treatments both on soil solution cations either exchangeable cations. In particular compost application increased the calcium (Ca) and potassium (K) contents in saturated soil paste respect to the SWF ones (31.4% and 59.5%, respectively). At the same time saturated soil paste sodium (Na) in SWC treatment recorded a decrease of 17.4% compared to SWF.

Abstract: Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.