L’agriculture souffre d’un important déficit d’image : qualité des produits jugée médiocre, non respect de l’environnement, pénibilité des métiers… La réalité est cependant tout autre. Tout en restant profondément ancré dans la vie des territoires, ce secteur est devenu numéro deux de la robotisation. De nouvelles méthodes fondées sur le traitement des données, des outils innovants, intelligents et connectés, ainsi que des réseaux de diffusion des innovations et d’entraide contribuent à transformer en profondeur l’agriculture.
Innovation rests not only on discovery but also on cooperation and interactive learning. In agriculture, forestry and related sectors, multi-actor partnerships for ‘co-innovation’ occur in many forms, from international projects to informal ‘actor configurations’. Common attributes are that they include actors with ‘complementary forms of knowledge’ who collaborate in an innovation process, engage with a ‘larger periphery’ of stakeholders in the Agricultural Knowledge and Innovation System (AKIS) and are shaped by institutions.
Precision Agriculture (PA) has been advocated as a promising technology and management philosophy that provides multidimensional benefits for producers and consumers while being environmentally friendly. In Europe, private stakeholders (farm advisors, farm equipment producers, decision support providers, farmers) and research institutions have been trying to develop, test and demonstrate adoption of precision agriculture solutions with governments financing big projects in these areas. Despite these efforts, adoption is still lagging behind expectations.
El documento se divide en ocho capítulos, en el primero se realiza una introducción al programa ERICA, los antecedentes del proceso y los objetivos que se persiguen. El segundo capítulo presenta un marco de referencia para contextualizar las prácticas de gestión en España, la situación en Colombia, el problema identificado y el marco normativo. El tercero presenta un marco conceptual con algunos de los términos más representativos trabajados en el proyecto.
The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions.
Familiar mixed dairy sheep farm is the most widespread system in the Mediterranean basin, in Latin America and in developing countries (85%). There is a strong lack of technological adoption in packages of feeding and land use in small-scale farms. To increase competitiveness, it would be of great interest to deepen the knowledge of how innovation was selected, adopted, and spread. The objective of this research was to select strategic feeding and land use technologies in familiar mixed dairy sheep systems and later assess dairy sheep farms in Spain.
Improvements in the sustainability of agricultural production depend essentially on advances in the efficient use of nitrogen. Precision farming promises solutions in this respect. Variable rate technologies allow the right quantities of fertilizer to be applied at the right place. This helps to both maintain yields and avoid nitrogen losses. However, these technologies are still not widely adopted, especially in small-scale farming systems. Recent developments in sensing technologies, like drones or satellites, open up new opportunities for variable rate technologies.
This study analyses the impact of the transfer of technological information (among other a priori identified factors) on the uptake of innovative crop technologies using structural equation modelling of data from a representative survey of Scottish crop farmers. The model explains 83% of the variance in current technological uptake behaviour and 63% of the variance in intentions to uptake new technologies.
Sorghum crop is grown under tropical and temperate latitudes for several purposes including production of health promoting food from the kernel and forage and biofuels from aboveground biomass. One of the concerns of policy-makers and sorghum growers is to cost-effectively predict biomass yields early during the cropping season to improve biomass and biofuel management. The objective of this study was to investigate if Sentinel-2 satellite images could be used to predict within-season biomass sorghum yields in the Mediterranean region.
We present a model for research and development (R&D) investment in food innovations based on new plant engineering techniques (NPETs) and traditional hybridization methods. The framework combines uncertain and costly food innovation with consumers' willingness to pay (WTP) for the new food. The framework is applied with elicited WTP of French and US consumers for new improved apples. NPETs may be socially beneficial under full information and when the probability of success under NPETs is relatively high. Otherwise, the traditional hybridization is socially optimal.