El objetivo de este trabajo presentado en la II Jornadas de Sociología es analizar el rol que cumplen las TIC en el proceso de comercialización implementado por Tu Raíz atendiendo el uso de dichas tecnologías en la compra de productos como en la venta, desde una concepción de la complejidad de los procesos de innovación y de comunicación.
This article analyses spatial innovation dispersion and also level of innovation development across the crop sector. For this, five crude indicators viz. Mechanisation indicator, Vulnerability indicator, Concentration indicator, Stability indicator and Adoption indicator were constructed which determined the direction of innovation. Agricultural Innovation System encompasses both the facets of technology development and technology dissemination. However, much concentration and efforts were exerted on innovation and technology development part while the other part i.e.
This paper analyzes the status of Pakistan’s agriculture in the world and quantifies the potential of improving productivity and quality of value chain at its different nodes. A great potential of expansion in the value chain of large number of agricultural commodities produced in Pakistan are observed. Just bringing the average crop yield levels at par to the world average yield can generate over US$11 billion additional revenues to the producers. Despite lower yield, majority of commodities have lower prices compared to the world average prices at the farmgate.
Este artículo hace un análisis del perfil de la avicultura a pequeña escala realizada en el Estado de Espirito Santo, en Brasil, de los roles que posee en la agricultura familiar y de los que podría tener en una agricultura más sostenible.
The present study considered the current state of internet of things in Nigeria, future prospects and challenges to the usage of the technology in Nigerian Agriculture. In Nigeria, IoT has been used to dispense feed and water to chicks, virtual fences for monitoring farmlands and forest trees, cashless sales and purchases of farm produce and input, monitoring and management of staff performances on the farm and e-wallet for input, loan and information accessibility on agricultural issues.
Agricultural machinery manufacturers historically referred to the intermediate players for selling, maintenance, customer service and/or training of equipment appear to interact with farmers and end-users. Intermediate players have therefore faced the burden to master the technology, in constant evolution, and the associated training needs at the interface between sophisticated equipment and the end-user and its sociological characteristics (age, education, background, etc.).
It has long been recognized that investment is needed to build capacity in Science Technology and Innovation (STI) particularly in low and medium income (LMI) countries. Yet there is little understanding as to how to do this.
Cet article présente une nouvelle approche à base de logique floue pour évaluer le risque phytosanitaire dans une serre produisant des roses. Le but de cette étude est de fournir à l’agriculteur un indice représentant le risque de présence de nuisible : Western Flower Thrips (WFT) ou Frankliniella Occidentalis, et d’enlever la phase decomptage manuel. Un systéme d’aide à la décision modulaire basé sur la connaissance d’experts a été conçu. Le systéme proposé fournit un facteur de risque en fonction des données météorologiques et statiques.
For an intelligent agricultural robot to reliably operate on a large-scale farm, it is crucial to accurately estimate its pose. In large outdoor environments, 3D LiDAR is a preferred sensor. Urban and agricultural scenarios are characteristically different, where the latter contains many poorly defined objects such as grass and trees with leaves that will generate noisy sensor signals. While state-of-the-art methods of state estimation using LiDAR, such as LiDAR odometry and mapping (LOAM), work well in urban scenarios, they will fail in the agricultural domain.
3D Move To See (3DMTS) is a mutli-perspective visual servoing method for unstructured and occluded environments, like that encountered in robotic crop harvesting. This paper presents a deep learning method, Deep-3DMTS for creating a single-perspective approach for 3DMTS through the use of a Convolutional Neural Network (CNN). The novel method is developed and validated via simulation against the standard 3DMTS approach.