Analysis and agrometeorological modelling of grapevine responses to different trellising systems

As the greater part of current viticulture is based on traditional trellising systems, usually in single hedgewall training, the aim of this research is to evaluate the possibility of introducing alternative trellising systems in order to improve canopy architecture and leaf distribution, and optimize light interception. In 2001 and 2002 field measurements (agrometeorological variables, vegetative growth, productivity and physiological behaviour) and modeling were performed on Sangiovese grapevines in a Tuscan vineyard with two trellis systems: a single hedgewall and a low double hedgewall (lyre trellis). The vines were spur pruned and cordon trained and the planting density was 6,667 vines/hectare. The two trellising systems were distributed in a randomized block design with 4 replications of 3 rows each. Data were collected from the central row. The simulation was obtained using a model, implemented with the Stella language, consisting of three sub-modules concerning photosynthesis, respiration and biomass accumulation. Light interception was greater for the lyre system than for the single cordon, while no differences were obtained in single leaf photosynthesis measurements between the trellis systems. Vegetative growth was higher for the lyre, indicating that lyre had a higher whole plant photosynthesis. The lyre system had greater yield due to a higher cluster number and a higher cluster weight compared to the single cordon training. No differences in must sugar content, titratable acidity or anthocyanins were observed. Models satisfactorily simulate the growth of grapevine under the single cordon system, while the growth of the lyre vine was extremely underestimated.

An Analysis of Preference Weights and Setting Priorities by Irrigation Advisory Services Users Based on the Analytic Hierarchy Process

Objective: Stakeholders-farmers from four different European areas (Campania (IT), Kujawsko-Pomorskie (PL), Limburg (NL), Andalusia (ES))-are asked to share, from the OPERA project, their opinions on five criteria that all aim at improving the use of irrigation advisory services (IASs). Each criterion has different characteristics that affect the way farmers rank it. The present study has two objectives. The first is to individuate the priorities of the preferences expressed by the stakeholders. The second objective is to carry out a ranking of the weights of the criteria by case study, ranking the groups and their associated properties among farmers' profiles. Methods: The answers to 120 questionnaires dispensed to the future users of IASs in the four agricultural sites were analyzed in detail, and then the given priorities were evaluated through the analytic hierarchy process (AHP). The AHP methodology was used to determine the relative weights of the five assessment criteria, and finally, to select the one with major value. Results and conclusions: The results show that A5 (assuring economic sustainability) was the most important criterion. The contributions provided by this study are twofold: Firstly, it presents an application of a methodology that involves the conversion of a linguistic judgement of farmers in a correspondence weight. Secondly, it tackles decision making regarding improving the use of IASs, evaluating the preferences expressed by the stakeholders. Irrigation advisory services can play a key role in assisting users to adopt new techniques and technologies for more efficient water use and increased production

Modelling durum wheat (Triticum turgidum L. var. durum) grain protein concentration

The goal of the present study was to improve the CERES-wheat model simulation of grain protein concentration (GPC) for winter durum wheat and to use the model as a basis for the development of a GPC Simplified Forecasting Index (SFIpro). The performances of CERES-wheat, which is one of the most widespread crop simulation models, with (i) its standard GPC routine and (ii) a novel equation developed to improve the model GPC simulation for durum wheat, were assessed through comparison with field data. Subsequently, CERES-wheat was run for a 56-year period in order to identify the most important status and forcing variables affecting GPC simulation. The number of dry days during the early growth stages and the leaf area index (LAI; green leaf area per unit ground surface area) at heading stage (LAI5) were identified as the main variables positively correlated with CERES-wheat predicted GPC, and so included in the SFIpro. At validation against observed data SFIpro was found to perform differently on the basis of observed plant LAI. In fact, SFIpro was able to forecast GPC variability for intermediate values of LAI5 ranging from 1 to 2, while it totally failed when LAI5 was outside this range (LAI5 2). The results suggest that the relationship between LAI and GPC is not linear and that the model assumptions for GPC simulation in CERES-wheat are only partially confirmed, being valid for an intermediate range of LAI