Weeds in conservation agriculture. Biology, emergence dynamics and modelling to improve their control

The increasing attention of public opinion towards the environmental impact of production activities has made it imperative to reduce the aggressiveness of productive systems on the environment. Also the agricultural sector, considered one of the principal strengths of transformation of the territory, is asked to predispose eco-compatible programmes of production. The institutions and national and international organisms encourage the adoption of techniques of conservative agriculture as a tool for guaranteeing, on the one hand the necessary crop production to face the demand for food of the growing population and, on the other the safeguarding and improvement of the quality of natural resources. Conservative agriculture is born with the intent to reduce or eliminate the intense tillage of cultivated lands that has caused impoverishment, degradation and loss of soil in favour of a more eco-friendly management of different agroecosystem components. Nevertheless weed management, the complexity of which is a deterrent for the adoption of this type of agronomic system, represents one of the main problems. Weeds are the main cause of economic losses in agriculture worldwide, both as crop yield reduction and control costs. In a conventional farming system weeds are controlled by herbicides and mechanical operations that together are able to maintain the infestation level beneath the threshold of economic damage. In a conservative system, to obtain the same level of crop defence, it is necessary to increase the chemical control with the consequent increased costs for farmers, health risks and environmental impacts. In this scenario, Integrated Weed Management plays a key role in order to achieve environmental, social and economic sustainability of crop production. Particularly, weed emergence and weed-crop competition models can provide useful indications about timing, type and cost-effectiveness of control measures. This research has the goal of providing wider and deeper knowledge of what is involved for the weed science sector in the implementation of conservation agriculture protocols. The main objective, common to all the studies presented in this thesis, is the calibration of a prediction model to optimize the timing for the weed control in a no-tillage soil. The model under study is AlertInf, a model created for tilled soils that is based on the concept of hydrothermal time. According to this approach the emergence dynamics is determined by two main factors: temperature and water potential of the soil. Seeds in the soil accumulate hydrothermal time for their germination according to temperature threshold values and a water potential typical for each species. Chapter 1 describes the experiments for the estimation of temperature thresholds for four no-tillage soil weed species: Taraxacum officinale, Sonchus oleraceus, Senecio vulgaris, Conyza spp, comparing different methods for the estimation of this parameter. Chapter 2 highlights the importance of soil microclimate information acquisition (such as temperature and water potential) in the seed germination area. A field experiment was designed to assess the extent of changes in temperature and soil moisture resulting from no-tillage. In particular, a system of sensors, which allows the measurement of temperature and water potential in the upper soil layers, was tested as the soil surface is involved in the germination processes and weed growth in a conservative system. For modelling purposes, the emergence dynamics of the some weed species were studied and whether and how the dynamics of these species change in a different agronomic management was verified. A study was therefore conducted in a controlled environment to test the effect of the seed burial depth and tillage on the amount of emerging plants and the emergence dynamics (Chapter 3). Seasonal weed surveys were done on three experimental farms in Veneto region from 2011 to 2013 in conventional and conservative management fields to verify the species present in the two different systems and the emergence dynamics (Chapter 4). The last chapter (Chapter 5) shows the transferability of AlertInf model from maize to soybean in conventional management. A result that advances the hypothesis of the transferability also in a conservative environment. With this thesis the bases have been established for the construction of a predictive model of weed emergences in conservation agriculture, but model construction necessitates in-depth knowledge of all the factors involved in the phenomenon determination and accurate inputs, therefore it has been underlined that many problems still have to be solved and further researches are needed