• We examine varietal trait preferences of farmer segments using an intersectional lens by considering intersecting social categories and marginalization, and not just binary gender model.

• Trait preferences of men and women become similar with identical marginalization; they are more similar in poorer households and diverge in high-wealth households.

• Poorer farmers and widows withdraw from traditional gender-associated traits.

• Class, marital status, gender roles, and agency transform trait preferences.

• Compounding levels of marginalization drive trait preferences and not gender in isolation.

Improved crop varieties help farmers adapt to changing climate and socioeconomic challenges. They are essential for meeting the global food demand, but their adoption remains slow and low. One reason for this unsuccessful adoption is the disregard of trait preferences and marginalized contexts of diverse users by actors in varietal development and delivery. The general wisdom regarding trait preferences includes gender-distinct priorities, in which men focus on high yield and marketability, while women prefer good taste and other cooking attributes. However, although gender is a first step toward nuanced preferences, most analyses restrict themselves to gender-based comparisons (frequently using the sex of heads of households), which homogenizes socioeconomic conditions and preferences within gender. Using intrahousehold preference data, our study reveals that the intersection between gender and other social categories presents compounded marginalization that corresponds to similarities or differences in women’s and men’s trait preferences. Cluster analysis reveals that trait preferences of women and men overlap but differ in the traits’ relative importance. Trait preferences are comparable in low-wealth clusters as they operate in similar marginalized contexts and diverge in high-wealth clusters. Furthermore, logit regression shows that factors of marginalization, gender roles, and agency are associated with increased odds of prioritizing specific traits, such as market and culinary traits. Our results demonstrate how diversity of marginalization and intersectionality matters more than gender dichotomies. We anticipate that our intersectional approach to understanding gendered trait preferences can enhance targeted, demand-led, and inclusive varietal development and delivery in the future. 

Mission-oriented governance of research focuses on inspirational, yet attainable goals and targets the sustainable development goals through innovation pathways. We disentangle its implications for plant breeding research and thus impacting the sustainability transformation of agricultural systems, as it requires improved crop varieties and management practices. Speedy success in plant breeding is vital to lower the use of chemical fertilizers and pesticides, increase crop resilience to climate stresses and reduce postharvest losses. A key question is how this success may come about? So far plant breeding research has ignored wider social systems feedbacks, but governance also failed to deliver a set of systemic breeding goals providing directionality and organization to research policy of the same. To address these challenges, we propose a heuristic illustrating the core elements needed for governing plant breeding research: Genetics, Environment, Management and Social system (GxExMxS) are the core elements for defining directions for future breeding. We illustrate this based on historic cases in context of current developments in plant phenotyping technologies and derive implications for governing research infrastructures and breeding programs. As part of mission-oriented governance we deem long-term investments into human resources and experimental set-ups for agricultural systems necessary to ensure a symbiotic relationship for private and public breeding actors and recommend fostering collaboration between social and natural sciences for working towards transdisciplinary collaboration. 

Automated phenotyping is hailed to transform modern agricultural systems and relieve many sustainability challenges, like maintaining food security, halting biodiversity loss, and adapting to climate change. Yet, these issues can be traced from farming back to plant breeding and highly depend on the crop genetic diversity in use. Engineering and plant science usually take a look at automated phenotyping from a technical perspective and value its merits for research in plant breeding. In contrast, we lay out a more holistic view and ask what the social-ecological-technical repercussions to the robustness of on-site crop genetic diversity are from laboratory to breeding nursery where varieties for farming are being produced. We argue that automated phenotyping has a twofold impact on systemic robustness. On the one hand, it improves adaptive capacity by accelerating the breeding process. On the other hand, it's implementation can destabilize the system and have unforeseen negative impacts on on-site crop genetic diversity. Therefore, we call for explicit monitoring of the possible side effects by the system's governance.

The social–ecological systems (SES) framework (Ostrom 2009, Science. 325(5939):419–22) typologically decomposes SES characteristics into nested, tiered constituent variables. Yet, aligning the framework’s concepts of resource system (RS) and resource unit (RU) with realities of individual case studies poses challenges if the underlying SES is not a single RS, but a mid to large-scale nested RS (NRS). Using a diagnostic approach, we describe NRSs—and the activities and networks of adjacent action situations (NAAS) containing them. An NRS includes the larger RS and multiple interlinked semi-autonomous subsidiary RSs, each of which support simultaneous, differently managed appropriation of individual RUs. We further identify NAASs operating within NRSs in two diverse empirical cases—networks of lake systems in Bengaluru, India and German wheat breeding systems—representing a lever towards understanding transformation of SESs into sustainable futures. This paper contributes towards unpacking and diagnosing complexities within mid to large-scale RSs and their governance. It provides a generalizable, rigorous approach to SES case study analyses, thereby advancing methods for synthesis in sustainability science. 

Wheat is a globally important crop and one of the “big three” US field crops. But unlike the other two (maize and soybean), in the United States its development is commercially unattractive, and so its breeding takes place primarily in public universities. Troublingly, the incentive structures within these universities may be hindering genetic improvement just as climate change is complicating breeding efforts. “Business as usual” in the US public wheat-breeding infrastructure may not sustain productivity increases. To address this concern, we held a multidisciplinary conference in which researchers from 12 US (public) universities and one European university shared the current state of knowledge in their disciplines, aired concerns, and proposed initiatives that could facilitate maintaining genetic improvement of wheat in the face of climate change. We discovered that climate-change-oriented breeding efforts are currently considered too risky and/or costly for most university wheat breeders to undertake, leading to a relative lack of breeding efforts that focus on abiotic stressors such as drought and heat. We hypothesize that this risk/cost burden can be reduced through the development of appropriate germplasm, relevant screening mechanisms, consistent germplasm characterization, and innovative models predicting the performance of germplasm under projected future climate conditions. However, doing so will require coordinated, longer-term, inter-regional efforts to generate phenotype data, and the modification of incentive structures to consistently reward such efforts. 

Climate change and social conflicts put modern agricultural systems under pressure, necessitating systemic transformations of these systems towards sustainability. At the core of these sustainability challenges to agriculture lie the seed we use to produce plants giving us food, feed and fiber. To achieve high crop yields, farmers need varieties with the right combination of characteristics, called traits, which fit to the pedo-climatic conditions of their farms and to other preferences regarding product qualities. The route from developing a trait combination in a plant that such characteristics, however, is long and novel traits need to pass through a complex social-ecological system to reach the farm gate. Each chapter of this thesis engages with different organizing principles of social-ecological systems and what they mean for the governance of plant breeding within the seed systems. Seed systems entail all activities along the breeding and seed supply chain needed for creating (new) varieties for use on farms. These activities of plant breeding depend on sustained flows of genetic material within the seed and cropping system. The various activities are structured by rules, norms and strategies, also referred to as institutions (Ostrom 2005). Institutions need to be designed consciously to achieve sustainable outcomes. The aggregated processes of creating, maintaining, directing, recognizing, and enforcing institutions are the governance of the seed system. Overall the thesis inquires how to best govern seed systems towards more sustainable outcomes in seed and cropping systems. Hence, we first ask what the governance challenges are in providing and appropriating crop genetic diversity as the underlying resource. We found that provisioning symmetric and credible information between different actor groups will grant a smoothly running seed system. Second, we further unpack the activities around the nested adjacent action situations for social-ecological systems and provide a set of diagnostic questions to untangle the nested and multi-tiered variables of the resource system within mid to large-scale SESs. Third, we develop a governance heuristic showing that Genetics, Environment, Management and Social system (GxExMxS) are core elements, which need to be considered when governing plant breeding research under the premise of mission-oriented governance. Fourth, we ask the question whether pest shocks lead to a increase in multiplication area of resistant varieties. Using data from seed variety trials matched with data on seed multiplication area per variety. The no-effect hypothesis could not be refuted.

Durch den Klimawandel und gesellschaftliche Konflikte erhöht sich zunehmend der Druck auf moderne Agrarsysteme sich zu nachhaltigeren Systemen zu transformieren. Im Zentrum dieser systemischen Transformation zu einer nachhaltigen Landwirtschaft steht das Saatgut zur Produktion von Nahrungs- und Futtermitteln sowie zur Produktion von Pflanzenfasern. Um hohe Erträge zu erreichen benötigen Landwirt*innen Sorten die die entscheidenden Eigenschaften in sich vereinen und sowohl zu den jeweiligen Boden-Klimaräume ihrer Standorte passen als auch die gewünschten Produktqualitäten gewährleisten. Doch der Weg von der Entwicklung dieser Eigenschaften bis zum Anbau auf dem Acker führt durch ein komplexes sozial-ökologisches System. Jedes Kapitel dieser Dissertation setzt sich mit verschiedenen Organisationsprinzipien sozial-ökologischer Systeme und deren Konsequenzen für die Steuerung, Führung und Governance von Pflanzenzüchtungs- und Saatgutsysteme auseinander. Saatgutsysteme umfassen alle Aktivitäten entlang der Wertschöpfungskette der Saatgutentwicklung und -vermarktung, die notwendig sind, um neue Sorten auf den Acker zu bringen. Die Saatgutentwicklung ist dabei auf eine zuverlässige Weitergabe von genetischem Material durch das Saatgut und Anbausystem angewiesen. Die verschiedenen Aktivitäten werden durch Regeln, Normen und Strategien strukturiert, den sogenannten Institutionen (Ostrom 2005). Um nachhaltigere Ergebnisse zu ermöglichen, müssen diese Institutionen bewusst verändert werden. Die Prozesse, die notwendig sind, um Institutionen zu gestalten, zu erhalten, zu steuern, zu erkennen und durchzusetzen, werden als Governance der Saatgutsysteme bezeichnet. Die Dissertation beschäftigt sich mit der generellen Frage wie die Governance von Saatgutsystemen am besten aussehen sollte um nachhaltigere Saatgut- und Agrarsysteme zu erreichen. In Kapitel 2 wird untersucht, welchen Herausforderungen sich das Saatgutsystem bei der Steuerung und Organisation der Bereitstellung und Verwendung von genetischer Vielfalt von Kulturpflanzen stellen muss. Wir haben festgestellt, dass die Bereitstellung symmetrischer und glaubwürdiger Informationen zwischen verschiedenen Akteursgruppen ein reibungslos funktionierendes Saatgutsystem gewährleistet. Im Anschluss, Kapitel 3, analysieren wir vernetzte und angrenzende Handlungssituationen (nested adjacent action situations) sozial-ökologischer Systeme und stellen einen diagnostischen Fragenkatalog zur Verfügung, welcher die vernetzten und mehrschichtigen Variablen des Ressourcensystems für mittlere bis große sozialökologische Systeme beinhaltet. In Kapitel 4 entwickeln wir eine Faustformel für die Governance der Pflanzenzüchtungsforschung, welche belegt, dass Genetik, Umwelt, Bewirtschaftung und Rückkopplungen aus dem Sozialen System (GxExMxS) als Kernelemente bei der zielorientierten Governance der Pflanzenzüchtungsforschung zu berücksichtigen sind. Kapitel 5 ist eine empirische Arbeit, die analysiert ob sich Schädlingsepidemien auf die Entscheidungen in der Saatgutvermehrung zur Allokation von Vermehrungsflächen auswirkt. Dies konnte für Vermehrungsflächen in Bayern nicht nachgewiesen werden. 

Varietal and genetic diversity sustain modern agriculture and is provided by breeding systems. Failures in these systems may cause insufficient responses to plant diseases, which threatens food security. To avoid these failures, an understanding of the governance challenges in providing varietal and genetic diversity is required. Previous studies acknowledge the complexity of seed breeding, framing the discussion in terms of rivalry and excludability. We consider breeding systems as social-ecological systems that focus on activities that generate varietal and genetic diversity and their adaptive ability. We use an inductive approach based on qualitative methods combined with the social-ecological system framework (SESF) to depict how highly context-dependent German winter wheat breeding, multiplication, and farming activities are. Our results show that the challenges for governance lie in providing credible and symmetric information on variety performance to all actors. This is the means to steer actors into collective action by subcontracting, buying, or saving seed. Based on our application of the SESF to the German wheat breeding system, we propose to develop a more general, sectoral SESF for the sustainable governance of plant breeding by offering an adaptable template for analyses of seed systems in other contexts. 

Highlights

• Empirical literature on adoption of digital farming is not well connected with agent-based models on innovation diffusion.

• We connect empirical adoption studies and system approaches of innovation diffusion by review and synthesis.

• Agent-based models can explicitly represent complex systemic relationships but lack empirical validation. 

• We converge the insights from our reviews into a conceptual framework. 

• We provide a reference to study the adoption of digital farming and guide future analyses informing policy-makers.

Abstract

CONTEXT

Adoption and diffusion of digital farming technologies are expected to help transform current agricultural systems towards sustainability. To enable and steer transformation we need to understand the mechanisms of adoption and diffusion holistically. Our current understanding is mainly informed by empirical farm-level adoption studies and by agent-based models simulating systemic diffusion mechanisms. These two approaches are weakly integrated.

OBJECTIVE

Our objective is to build an empirically grounded conceptual framework for adoption and diffusion of digital farming technologies by synthesizing literature on these alternative approaches.

METHODS

We review 32 empirical farm-level studies on the adoption of precision and digital farming technologies and 27 agent-based models on the diffusion of agricultural innovations. Empirical findings are synthesized in terms of significance and partially standardized coefficients, and diffusion studies are categorized by their approaches and theoretical frameworks.

RESULTS AND CONCLUSIONS

We show that farm-level studies focus on farm and operator characteristics but pay less attention to attributes of technology, interactions, institutional and psychological factors. Agent-based models, despite their usefulness for representing system interaction, only loosely connect with empirical farm-level findings. Based on the identified gaps, we develop a conceptual framework integrating farm-level evidence on adoption with a systemic perspective on technology diffusion.

SIGNIFICANCE

Our empirically grounded conceptual framework is the first holistic approach to connect the dots between the wealth of empirical research on technology adoption with more model-driven investigation of innovation diffusion in agent-based studies. Focusing on digital farming technologies, it may serve as a reference for those studying the adoption and diffusion of such technologies beyond farm scale. Furthermore, this framework can be the basis for contextual applications to inform policy-makers trying to foster the diffusion of suitable digital technologies through interventions as it highlights where policy can impact important aspects of adoption via relevant processes of diffusion.