The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach. A set of 192 bunches from four cultivars, collected at sites located in Portugal and South Africa, were imaged using a conventional digital RGB camera, followed by image analysis, where several bunch features were extracted, along with physical measurements performed in laboratory conditions. Image data features were explored as predictors of bunch weight, individually and in a multiple stepwise regression analysis, which were then tested on 37% of the data. The results show that the variables bunch area and visible berries are good predictors of bunch weight (R2 ranging from 0.72 to 0.90); however, the simple regression lines fitted between these predictors and the response variable presented significantly different slopes among cultivars, indicating cultivar dependency. The elected multiple regression model used a combination of four variables: bunch area, bunch perimeter, visible berry number, and average berry area. The regression analysis between the actual and estimated bunch weight yielded a R2 = 0.91 on the test set. Our results are an important step towards automatic yield estimation in the vineyard, as they increase the possibility of applying image-based approaches using a generalized model, independent of the cultivar.
Networks and partnerships are commonly-used tools to foster knowledge sharing between actors and organisations in the Agricultural Knowledge and Innovation System (AKIS), but in Europe the policy emphasis on including users, such as farmers and foresters, is relatively recent. This...
Accurate and operational indicators of the start of growing season (SOS) are critical for crop modeling, famine early warning, and agricultural management in the developing world. Erroneous SOS estimates–late, or early, relative to actual planting dates–can lead to inaccurate crop...
Depuis sa création, le Parc national du Mont Péko est sujet à diverses pressions anthropiques. Ces pressions ont été accentuées durant les conflits armés en Côte d’Ivoire entre 2002 et 2011. L’intensification des pressions aurait entraîné une augmentation du taux...
Innovation system approach offers an holistic, multidisciplinary and comprehensive framework for analyzing innovation process, the roles of science and technology actors and their interactions, emphazing on wider stakeholder participation, linkages and institutional context of innovation and processes. This paper was aimed to:...
The objective of this study is to evaluate the ability of soil physical characteristics (i.e., texture and moisture conditions) to better understand the breeding conditions of desert locust (DL). Though soil moisture and texture are well-known and necessary environmental conditions...