Abstract: Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work.

Abstract: Farmlands are increasingly exposed to degradation phenomena associated to climate change and agricultural practices, including irrigation. It is estimated that about 20% of the world’s irrigated land is salt affected. In this paper we aimed at evaluating the effect of seasonal and multiannual soil satinization on growth, yield, and radiation use efficiency of tomato in open field. Two field experiments were carried out at the Experimental Station of the University of Naples Federico II (latitude 40 degrees 31’N longitude 14 degrees 58’E) (Italy) on tomato during 2004 and 2005 to study the effect of five levels of water salinity: NSC (EC = 0.5 dS m(-1)), SW1 (EC= 2.3 dS m(-1)), SW2 (EC= 4.4 dS m(-1)), SW3 (EC= 8.5 dS m(-1)) and SW4 (EC= 15.7 dS m(-1)) in a soil exposed to one-season salinization (ST = short-term) and an adjacent soil exposed to >20 years salinization (LT = long-term). Plant growth, yield and fruit quality (pH, EC, total soluble solids and the concentration of reducing sugars and of titratable acids), and plant water relations were measured and radiation use efficiency (RUE) was calculated. Increasing water salinity negatively affected the leaf area index (LAI), radiation use efficiency (RUE) and above-ground dry weight (DW) accumulation resulting in lower total and marketable yield. Maximum total and marketable yield obtained with the NSC treatment were respectively 117.9 and 111.0 Mg ha(-1) in 2004 and 113.1 and 107.9 Mg ha(-1) in 2005. Although the smaller leaf area of salinized plants was largely responsible for reduced RUE, we found approximately 50% of this reduction to be accounted for by processes other than changed crop architecture. These may include an increased stomatal resistance, increased mesophyll resistance and other impaired metabolic functions that may occur at high salinity. Remarkably, we found that LT salinized plants had a slightly better efficiency of use of intercepted radiation (RUEIR) at a given EC of soil extract than ST salinized plants indicating that LT salinization, and consequent permanent modifications of the soil physical properties, may trigger additional physiological mechanisms of adaptation compared to ST salinized plants. These differences are relevant in light of the evolution of salinized areas, also in response to climate change.

Abstract: Short-term perspectives appear to be relevant in formulating adaptation measures to changed climate variability (CCV) as a part of the European Rural Development Policy (RDP). Indeed, short-run CCV is the variation that farmers would perceive to such an extent that a political demand would be generated for adapting support measures. This study evaluates some relevant agronomic and economic impacts of CCV as modelled in a near future time period at the catchment scale in a rural district in Sardinia (Italy). The effects of CCV are assessed in relation to the availability of irrigation water and the irrigation needs of maize. The Environmental Policy Integrated Climate (EPIC) model was used to simulate the impact of key climatic variables on the irrigation water requirements and yields of maize. A three-stage discrete stochastic programming model was then applied to simulate management and economic responses to those changes. The overall economic impact of a simulated CCV was found to be primarily caused by reduced stability in the future supply of irrigation water. Adaptations to this instability will most likely lead to a higher level of groundwater extraction and a reduction in the demand for labour. Changed climate variability will most likely reduce the income potential of small-scale farming. The most CCV-vulnerable farm typologies were identified, and the implications were discussed in relation to the development of adaptation measures within the context of the Common Agricultural Policy of European Union. (C) 2013 Elsevier Ltd. All rights reserved.