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The application of modern biotechnology to crop and food production is one of the most significant technological advances to impact modern agriculture. Barely a dozen years since their introduction, genetically modified (GM) crops are currently grown on more than 300 million acres worldwide. GM (or transgenic) crops are produced using plant biotechnology to select desirable characteristics in plants and transfer genes from one organism to another. As a result, crops can survive under harsher conditions, costs are lowered, and yields are improved. Scientists are introducing genes into plants that will give the plants resistance to herbicides, insects, disease, drought, and salt in the soil. Crop research in bioengineering is also aimed at improving the nutritional quality of food, such as providing healthier vegetable oils. Pharmaceutical and industrial crops (or “pharma” crops) are also on the horizon, with the potential to dramatically reduce drug production costs. Compared to traditional plant breeding, biotechnology can produce new varieties of plants more quickly and efficiently, and it can introduce desirable traits into plants that could not be established through conventional plant breeding techniques.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

This chapter opens the second part of the Volume, focusing on the small farms' role and dynamics within the evolving food system. Assessing small farmers' actual and potential contribution to the change towards a sustainable food and nutrition security requires a deep understanding of their strategic decision-making processes. These processes take place in a context highly conditioned by internal and external conditions, including the complex relations between farm and household, which are mapped and described. Building on an adaptation of Porter's model (Porter, 1990), the chapter investigates how farmers, given those conditions, define their strategies (in particular their innovation strategies) aimed at economic and financial sustainability through a multidisciplinary analysis of scientific literature. Internal conditions are identified in the light of the Agricultural Household Model (Singh & Subramanian, 1986) which emphasizes how family farming strategies aim at combining business-related objectives, and family welfare. Then, a comprehensive set of external conditions is identified and then grouped within eight categories: ‘Factors’, ‘Demand’, ‘Finance and Risk’, ‘Regulation and Policy’, ‘Technological’, ‘Ecological’, ‘Socio-institutional’ and ‘Socio-demographic’. Similarly, six types of strategies are identified: ‘Agro-industrial competitiveness’, ‘Blurring farm borders’, ‘Rural development’, ‘Risk management’, ‘Political support’ and ‘Coping with farming decline’.

This chapter aims at building a conceptual framework that could inspire innovation policies able to take into account the emerging agricultural and rural agenda, based on a comprehensive conceptualization of the innovation system. The systems of innovation and the broader processes of knowledge creation (and co-creation), transfer and adoption represent a crucial set of conditions influencing family farms' trajectories in response to the various opportunities and drivers of change, as well as their capability to contribute to sustainable food systems and FNS. This chapter analyzes the concept of innovation in relation to transition towards new configurations with a non-linear and multidimensional vision based on actors assembling themselves in a geographical space where resources and information are used to generate change. This leads to consider knowledge as an asset co-generated by the interaction of different actors within agricultural knowledge and innovation systems (AKIS) (Leeuwis & van den Ban, 2004). Agriculture and countryside are experiencing deep transformations towards concentration and globalization on one side and post-productivism and rural development on the other (Van der Ploeg et al., 2000). These processes of change require innovation policies aimed at pursuing ‘second-order’ innovation based on new goals and new rules. From a transition perspective (Geels, 2004) these radical innovations can develop within niches to a certain extent protected from mainstream market forces, to be then progressively embodied into higher structuration levels (the ‘regimes’).

Purpose – This chapter compares bioenergy policy developments in Germany and Denmark to better understand the responses of EU country policy regimes to global shocks; to examine potentially emerging new trends of productivist policy models; and to explore potential land use conflicts in the context of a multifunctional EU agricultural policy.

Design/methodology/approach – The chapter reviews the bioenergy policy development pathways taken by Germany and Denmark, highlighting key consequences for agricultural land use and rural development. Findings from both case studies are then compared in summary tables, followed by a discussion of the possible emergence of productivist policy approaches in the bioenergy sector in these countries.

Findings – The bioenergy policies pursued by both countries differ in key respects and yet have had the same result-an increase in the productivist orientation of agriculture, legitimised by the environmental concerns of bioenergy policy. The Danish and German case studies also demonstrate that the particular pathways taken to establish bioenergy policies in each country have been strongly influenced by local political, farming and technological dynamics.

Originality/value – This chapter presents a telling case of what Burton and Wilson (this volume) call “repositioned productivism”, where productivist approaches benefit from environmental or multifunctional policy rationale to continue at the farm level.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.