BAT (Berry Analysis Tool): A high-throughput image interpretation tool to acquire the number, diameter, and volume of grapevine berries

QTL-analysis (quantitative trait loci) and marker development rely on efficient phenotyping techniques. Objectivity and precision of a phenotypic data evaluation is crucial but time consuming. In the present study a high-throughput image interpretation tool was developed to acquire automatically number, size, and volume of grape berries from RGB (red-green-blue) images. Individual berries of one cluster were placed on a black construction (300 x 300 mm) to take a RGB image from the top. The image interpretation of one dataset with an arbitrary number of images runs automatically using the BAT (Berry-Analysis-Tool) developed in MATLAB. For validation of results, the number of berries was counted and their size was measured using a digital calliper. A measuring cylinder was used to determine reliably the berry volume by displacement of water. All placed berries could be counted by BAT 100 % correctly. Manual ratings compared with BAT ratings showed strong correlation of r = 0.96 for mean berry diameter/image and r = 0.98 for cluster volume.

Initial steps for high-throughput phenotyping in vineyards

The evaluation of phenotypic characters of grapevines is required directly in vineyards and is strongly limited by time, costs and the subjectivity of person in charge. Sensor-based techniques are prerequisite in order to allow non-invasive phenotyping of individual plant traits, to increase the quantity of object records and to reduce error variation. Thus, a Prototype-Image-Acquisition-System (PIAS) was developed for semi-automated capture of geo-referenced images in an experimental vineyard. Different strategies were tested for image interpretation using MATLAB®. The interpretation of images from the vineyard with real background is more practice-oriented but requires the calculation of depth maps. Different image analysis tools were verified in order to enable contactless and non-invasive detection of bud burst and quantification of shoots at an early developmental stage (BBCH 10) and enable fast and accurate determination of the grapevine berry size at BBCH 89. Depending on the time of image acquisition at BBCH 10 up to 94 % of green shoots were visible in images. The mean berry size (BBCH 89) was recorded non-invasively with a precision of 1 mm.

Effects of canopy architecture and microclimate on grapevine health in two training systems

Semi minimal pruned hedge (SMPH) is a time and cost saving grapevine training system, which is becoming more and more popular in German viticulture. In this study we compared the canopy architecture and its effect on the microclimate of SMPH trained grapevines with those of plants trained in vertical shoot positioning (VSP). We detected a 3 % points higher humidity and a 0.9 °C lower mean temperature within the complex canopy architecture of SMPH trained vines compared to VSP. Moreover, we investigated the influence of the differing microclimate, canopy and bunch architecture, as well as berry skin characteristics of the two training systems on the incidence of the major fungal grapevine diseases Downy Mildew, Powdery Mildew and Botrytis Bunch Rot, as well as on the occurrence and damage of the invasive insect pest Drosophila suzukii. We demonstrate that SMPH trained vines can be more susceptible to Downy Mildew and Powdery Mildew than VSP trained vines. The incidence of Botrytis Bunch Rot can be higher in the latter system, even if berry skin characteristics are the same in both training systems. We trapped a higher number of D. suzukii in SMPH canopies, however no increased berry damage was observed. Based on our results we recommend a more adapted plant protection regime for SMPH trained vines due to their higher susceptibility to the major fungal diseases. Furthermore, we propose a combination of SMPH and fungal resistant grapevine cultivars, e.g. 'Reberger', to achieve a more competitive, environmentally friendly and high quality grapevine production

Smartspectrometer—embedded optical spectroscopy for applications in agriculture and industry

The ongoing digitization of industry and agriculture can benefit significantly from optical spectroscopy. In many cases, optical spectroscopy enables the estimation of properties such as substance concentrations and compositions. Spectral data can be acquired and evaluated in real time, and the results can be integrated directly into process and automation units, saving resources and costs. Multivariate data analysis is needed to integrate optical spectrometers as sensors. Therefore, a spectrometer with integrated artificial intelligence (AI) called SmartSpectrometer and its interface is presented. The advantages of the SmartSpectrometer are exemplified by its integration into a harvesting vehicle, where quality is determined by predicting sugar and acid in grapes in the field

Evaluating Trade-Offs Between Sustainability, Performance, and Cost of Green Machining Technologies

The growing demand to reduce environmental impacts has encouraged manufacturers to pursue various green manufacturing technologies and strategies. These solutions, though, may have a direct impact on several productivity metrics including availability, quality, service life, and cost. This study presents an approach to evaluate the trade-offs between the environmental, performance, and financial impacts of green machining technologies by combining green manufacturing principles into life cycle performance evaluation. The approach is validated by investigating the implications of reducing the processing time by increasing the cutting speed and chip load to green a horizontal milling process

The sweet spot in sustainability: a framework for corporate assessment in sugar manufacturing

The assessment of corporate sustainability has become an increasingly important topic, both within academia and in industry. For manufacturing companies to conform to their commitments to sustainable development, a standard and reliable measurement framework is required. There is, however, a lack of sector-specific and empirical research in many areas, including the sugar industry. This paper presents an empirically developed framework for the assessment of corporate sustainability within the Thai sugar industry. Multiple case studies were conducted, and a survey using questionnaires was also employed to enhance the power of generalisation. The developed framework is an accurate and reliable measurement instrument of corporate sustainability, and guidelines to assess qualitative criteria are put forward. The proposed framework can be used for a company’s self-assessment and for guiding practitioners in performance improvement and policy decision-maki