AN EXPERT SYSTEM FOR VINEYARD MANAGEMENT BASED UPON PERVASIVE COMPUTER TECHNOLOGIES

Size: px
Start display at page:

Download "AN EXPERT SYSTEM FOR VINEYARD MANAGEMENT BASED UPON PERVASIVE COMPUTER TECHNOLOGIES"

Transcription

1 AN EXPERT SYSTEM FOR VINEYARD MANAGEMENT BASED UPON PERVASIVE COMPUTER TECHNOLOGIES Giuseppe AIELLO, Mario ENEA, Cinzia MURIANA Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale Università degli Studi di Palermo Viale delle Scienze, 90128, Palermo Italia aiello@dtpm.unipa.it ; enea@unipa.it; muriana@unipa.it Abstract: Determining the optimal maturity level for performing viticulture operations and harvesting activities is a difficult task, because, depending on the variety, the climatic conditions and cultural practices, the phenologic maturation process occurs at different times. Recently, ubiquitous computing technologies allow an extremely precise and cost effective monitoring of environmental conditions by means of an RFID based sensor networks. The implementation of such technologies in vineyard management is nowadays under development, however, besides the possibility of gathering data, the need is perceived of developing decision support tools to fully exploit the potential opportunities of these new technologies. The present research aims at establishing a suitable method to support the decision process with the environmental data gathered automatically by a sensor network. The paper reports the results of an experimental study on a Sicilian vineyard showing that by means of the data collected by an RFID infrastructure it is possible to forecast the occurrence of phenologic maturity stage. Keywords: Decision support system, RFID, Production planning INTRODUCTION Sicily is the Italian region with the highest winemaking heritage and wine production constitutes a fundamental resource for the local economy accounting for 15% of the gross output of the entire agricultural turnover. In order to achieve high quality production, viticulture operations and harvesting activities must occur at the correct phenologic maturation level. In particular scheduling of the harvest operations has a fundamental role, as in fact grapes that are harvested before a desired maturity, result in the production of acidic wines while late harvesting generally results in unbalanced fruit composition. Determining the optimal maturity level for performing viticulture operations and harvesting activities however is a difficult task, because, depending on the variety, the climatic conditions and cultural practices, the phenologic maturation process occurs at different times. The environmental conditions that essentially affect grape ripeness are temperature, relative humidity, solar irradiation, and rainfall. In particular the temperature plays a fundamental role for grape maturation, including the aroma and the coloration [4]. In order to achieve the desired quality, hence, fruit maturity level must be closely monitored. Although several indices have been proposed, ripeness is currently an entirely subjective judgment, based upon the right mix of phenolic compounds, aroma, colour, sugars and acidity levels. In particular, the evaluation of the sugar and acid content, or ph of the berries, is of fundamental importance to manage the vineyard operations and schedule the harvesting process [2]. The sampling activities related to the evaluation of the maturity level must be manually performed, thus resulting in a costly and time consuming process. In such sense recent ubiquitous computing technologies may represent an effective solution which easily integrates with existing decision processes, providing extremely detailed and reliable information about environmental data. Pervasive computing technologies such as sensor network systems in fact give new capabilities for sensing and gathering data about an environment and new digital processing opportunities. Innovative infrastructures based on Wireless Sensor Networks (WSN) are a real-time, pervasive, non intrusive, low-cost, and

2 highly flexible data analysis technologies that can ensure high accuracy in detecting climatic conditions on the ground. Recently, WSNs have been employed in the specific area of farming monitoring and a few preliminary works describe applications for precision agriculture. [1]. According to such considerations, in this research the decision process regarding the timing of the vineyard operations is analyzed and a model is presented in order to forecast the occurrence of phenologic maturation stages on the basis of the information gathered by a wireless sensor network. The opportunities of practical application of the proposed methodology have also been verified against an experimental campaign. Sensor based vineyard management system In this section the decision processes concerning vineyard operations are investigated and a proactive vineyard management system is proposed to be employed in conjunction with ubiquitous computing technologies. The analysis of the decision processes involves the preliminary identification of the objectives they are supposed to fulfill and the subsequent formalization of the input data and the methodology required to produce the output decisions. Typical winemaking operations and harvesting decisions in particular, involve the interaction between the enologist and the vineyard manager, which have different priorities and objectives. The enologist is mostly concerned about wine quality, while the vineyard manager considers more specific agricultural variables, including operational costs. The assessment of grape maturity level is a primary information for winemakers and enologists. The date when optimal maturity is reached or when a new phenologic phase is entered, varies depending upon the quality of wine, the varietal typology of the vines, the site climatic conditions, the seasonal specific factors and the viticulture practices. Due to the complexity of the decision processes involved in vineyard management, viticulturists have developed an assessment method based upon the establishment of a set of indicators to be evaluated experimentally by periodically sampling the vineyard. The decision about the harvesting time grapes is such an important decision that most winemakers and grape growers start sampling grapes several weeks before the harvest time and continue sampling with increasing frequency as harvest time approaches. The maturation process is then monitored on the basis of maturation curves reporting sugar content, ph and total acidity of the samples. According to the previous considerations, the main drawback of the current winemaking practice is that it requires a direct sampling process of the berries, which must be manually carried out. The present research aims reducing the amount of manual sampling operations by supporting the decision processes with the environmental data gathered automatically by a sensor network. In particular the decision process here adopted is referred to the well known growth models proposed in the literature. Branas (1946), Winkler (1975) and Huglin (1986) in different years have studied parameters that affect grape ripeness and proposed some indices that allow to monitor the development of grapes. According to such models the five phenological phases (sprouting, flowering, fruit set, veraison, ripening) which characterize the grape maturation process can be related to environmental temperature. Based on studies conducted from the aforementioned authors, grapes ripeness can be related to the heat that the plant has stored during its growing period, that allows it to move from one phenological phase to the next. Heat needed to reach one phenological phase is commonly expressed through the heat quantity that a plant can store depending on daily temperatures, that define the Sum of Active Temperatures (STA), expressed in degree day (DD). STA allows to express phenological cycle length or single phase length in terms of thermal units according to (1): STA (1) where T Max and T min are the maximum and the minimum of daily air temperatures; if T Max is more than 35 C T Max is posed equal to this value; cardinalemin is the zero vegetative, i.e.

3 sprouting temperature. On the basis of this growth model some researchers have proposed numerical indexes capables to predict when one phenological phase happens. In our study we will refer to Winkler Index that is calculated as in (2): / / 10 (2) where negative values of (T med -10) should be set to zero. The establishment of referenced growth models based upon the aforementioned index allows to determine the phenologic maturation process by means of suitable thresholds. Winkler index varies depending on the quality of wine you want to produce. The typical values of the thresholds range from 1200 to 1400 for quality of wine as Cabernet Sauvignon (Red) or from for Nebbiolo (Red) and Malvasia (White) [3]. According to the above considerations, Heat summation based growth models in conjunction with thresholds allow to roughly assess the maturation process and approximately establish the optimal dates for viticulture operations. In this research the use of heat summation based growth models is supported by extremely detailed micro-climatic information measured continuously by means of a sensor network. This methodology will not allow to predict exact harvest dates at the beginning of the season due to inherent approximations and to the many variables that influence the rate of fruit ripening. However, with experience and record keeping, it is possible to make reasonably accurate projections as the season progresses. It is also expected that the performance achievable with the initial setup of the system, based on referenced parameters and thresholds will increase as actual records of different seasons will be available. At the initial deployment of the system, the dates of major phenological stages, along with harvested yield and fruit quality parameters obtained by standard fruit sampling procedures should be recorded for each area of the vineyard together with local weather records and degree-day accumulations, in order to tune up growth models and the threshold values thus improving the quality of the assessments. This is a common feature in the deployment of expert systems. The relationship between temperature (heat summation) and grapes growth, in fact, defined by the degree-day, combined with developmental thresholds can be exploited to estimate the optimal timing of viticulture operations. The ripening condition in fact can be related to a Cumulative Degree Days threshold, representing the total number of degree days necessary for the grape berries to reach the ripening stage. In such conditions it is possible to predict the effects of the changing seasons and climatic conditions during the growth period of the berries that determine an initial slow heat accumulation process, which dynamically increases as the weather gets hot in summer, thus resulting in a non-stationary process. In such context, the most common forecasting methods are adaptive and nonadaptive regression models, generalized exponential smoothing methods. The classical Bayesian linear regression models are unable to reproduce some of the features frequently observed in non-stationary processes, while, on the contrary, in such cases time series methods are extremely effective. In this research the growth of the berries is predicted by means of the previously discussed growth model on the basis of the heat summation. The heat summation value is updated daily with field measurements, and results in a nondecreasing series of values, originating trended time series. Future values of heat summation can hence predicted by means of the well known Holt s model, which is an exponential adaptive forecasting method for trended data, based on (3), (4), (5): (3) 1 (4) 1 (5)

4 The three updating equations result in the evaluation of the updated component at a future time t as a weighted average of the (adjusted) previous estimate and the most recent information acquired at time t, while, the trend is updated by averaging the previous trend component (Tt 1) with the difference between the two most recent level estimates (the trend is defined as the change in level). On the basis of the updated component and trend at time t, the forecasted value can be evaluated for any future time t+k. This method requires the establishment of two smoothing constants, α, and β. A common approach is to determine the values of α, and β that minimize the mean or median absolute error, or a similar measure. Finally, as stated before, the decision about the harvesting time is based upon the comparison of the predicted value with a pre-established threshold. The violation of this threshold means that a new phenologic phase has been entered. In order to support the decision process, hence the estimation of the probability of the forecast violating a threshold must be evaluated. This is generally accomplished by estimating the mean and variance of the future observations and relaying on the assumption of gaussian error terms to estimate the probability of violating the threshold. The standard deviation of the tracked data can be calculated as usual referring to the Jensen s inequality for the Gaussian distribution. According to such relation, the standard deviation is about 1,25 the mean absolute deviation. The Probability of the signal exceeding the ripening threshold T (see Figure 1) can hence be evaluated as in (6): 1 (6) Figure 1: Probability of exceeding a fixed threshold. For the decision model hence, the establishment of an acceptance probability (A) is required, resulting in a risk of accepting the hypothesis of the achievement of the optimal ripening level at time t+k when it is not (1-A), and rejecting this hypothesis when optimal ripening level is achieved with probability (A). In conclusion, the methodology proposed for predicting the harvest date involves getting available information on the lower developmental threshold temperature, cumulative degree days, and the observed temperatures for the area considered. Additionally the proposed system takes into account the possibility that the same variety may not behave in the same ripening state from one area to another. Ubiquitous Computing for climatic data acquisition The growth forecast model above described is based on the measurement of local temperatures for the evaluation of the heat summation index. The practical application of the proposed methodology therefore required a reliable measurement system allowing fast and precise evaluation of local micro-climatic parameters such as air temperature, relative humidity, and solar irradiation.[4]. Sensor based ubiquitous computing techniques are spreading nowadays as a cost effective technology for such purposes. In this research a sensor network has been designed and deployed in the vineyard in order to have extremely

5 precise local estimates of the air temperature. Deploying such technology in a vineyard requires the definition of the density and number of sensors according to the vineyard topology. Vineyards are typically organized into a hedgerow system, which is characterized by a supporting structure made of zinc-plated iron, wooden, or concrete poles, and some lines of steel wires to hold the vine canopy. The microclimate of the grapevine is affected by the environmental conditions of a limited area close to the rootstock. In order to obtain more accurate data than weather station or satellite monitoring, temperature wireless sensors have been placed in each pole in the vineyard. Battery powered. Sensor nodes placed along the rows of grapevines form a connected multi-hop network which, once configured, runs unsupervised. For the purpose of this research Sensor nodes placed in the vineyard are equipped with temperature sensors only, however different technologies allow the evaluation of light exposure, and humidity. Such elements, therefore, can be further integrated in the decision support system as soon as suitable decision models are developed. Temperature Data are collected via the wireless network, gathered at a central storage unit. Commercially available boards have been used equipped with the Sensirion SHT11 combined temperature/relative humidity sensor. Temperature range of the sensor is (-40 C -123,8 C), while Humidity range is (0 100% RH). The distance between the hedgerows is 2.20 m, while iron poles are positioned at 80 cm from each other. Three nodes were positioned on each pole at 90 cm, in order to obtain measurements about the micro-climate at the productive area of the grapevine, measurements about the micro-climate of the leaf-covered area, measurements from the top of the green canopy to be used as reference for the lower areas; all nodes were TelosB motes equipped with temperature and relative humidity sensors. An immediate advantage arising from the adoption of a WSN-based approach is that corrective actions on the cultivations may be timely and selectively chosen; furthermore, the system allows to build a history of past events, and stored data may be analyzed in order to extract potential hidden correlations among the sensed environmental variables and the obtained result. The availability of a considerable amount of precise data, superior to what is commonly attainable through traditional random sampling, allows for the construction of accurate models, and thus favors the proposals of improvements in the cultivation process. In addition to this parameters surveyed around the plants allow us to determine more accurately the microclimate in the vineyard and, consequently, assess the ripening process. Experimental analysis In order to evaluate the effectiveness of the proposed methodology an experimental analysis has been carried out involving the forecasting of the harvest date on the basis of the experimental values gathered by means of the previously described sensors network. The experiments have been carried out in the area of Monreale (Sicily) where many varieties of DOC wines (Ansonica or Insolia, Cabernet Sauvignon, Chardonnay, Muller Thurgau etc.) are grown. Monreale has the typical Mediterranean climate, with mild and rainy winters and hot and dry summers; with an average annual rainfall of approx. 700 mm and average annual temperature of 18 C. The experiments were carried on Chardonnay variety, which typically sprouts between the third decade of March and the first decade of April, flowers between the third decade of April and the second decade of May and ripens between the second and the third decade of August. The vineyard has been divided in 15 zones with homogenous slope of the soil and solar exposure. Sensors have been set to record temperature values every hour from April 2008 to May Data collected were analyzed to determine daily average temperature for each zone in order to calculate Winkler index. As a result of our study we evaluated the date of flowering related to each of 15 areas. The Winkler index (expressed in DD) for the period from April to May for each of 15 areas under study is shown in Figure 2.

6 MITIP 2009,, Octobe er, Bergamo W Winkler Indexx 8/4 1/4 1 15/4 22/4 29/4 6/5 13 3/5 20/5 27/5 F Figure 2: Winklerr Index of 15 zo ones of vineyard d. To determine e start and end flowering da ate we referre ed to the refere enced thresho olds given in Table 1 that show medium m Winkler ind dex values for the major stages of grap pes ripeness calculated ovver the three years y for chard donnay varietyy [3]. Cu ultivar Start Flo owering E End Flow wering Sttart Vera aison En nd Vera aison ation Matura Charrdonnay ± 30,2 386,9 ± 3 32,2 1010,3 ± 82 2, ± 96 6,3 1319,6 ± 130,,5 Table 1. Trien nnal average ( ) of Winkler Wi index durring the phenolo ogical phase in some s present cultivars in DOC D Monreale appellation a (ave erage ± standard d deviation). Results are shown in Ta able 2, where the average e value of the e days to Sta art and End d the range be etween them are a calculated for all zones. The average value of the flowering and days at Startt flowering and days at End d flowering arre 30 and 41,33 respectively, while the average valu ue between sta art and end flo owering is 11. Averag ge Days from m 1 April to Start flowering f Days from 1 April ering to End flowe Disttance between Start and End floweriing 30± 3,288 41,33± 2, ,00 Table 2. Number of zones Figure 3 repo orts distribution of Start date es for every off 15 zones of vineyard. v 4 3; 4; 5; 14 8; 9; ; /5 6/ /4 26/4 28/4 30/4 2//5 Da ay Start flowe ering Figure 3. 8/5

7 Winkler index has highlighted that the 15 zones under study have different date of flowering, due to different sunlight of every zone or different soil slope. This is an important information to realize a precision farming policy. Predicting when every phase happens allows to decide when is the moment to fertilize or when it needs to intervene to avoid the peronospora. In the same manner Winkler index calculated from April to October allows us to predict optimal harvest date and to plan harvest for every zone of the vineyard. As we have already said one of the most important goals of employ of eliothermal indexes is the possibility to predict when a thermal phase happens. To do this we analyzed the thermal sum of Winkler index for all zones of vineyard. Value of Winkler index expected with linear regression model and Holt s model are compared with those calculated with data collected and some parameters were calculated. As we have said in the previous paragraph to apply Holt s model it needs to determine for every zone of vineyard α and β values. For every zone we have determined the value of these parameters that minimize the Mean Absolute Error. The values of α and β determined for the area examined are respectively equal to 0,99 e 0,5446. Through the estimates made by the Regression model and Holt s model Winkler index value were determined for each zone of vineyard. Figure 4 reports expected value of Winkler index for one zone of vineyard. 550 Data Observed Holt Linear Regression 26/4 29/4 2/5 5/5 8/5 11/5 14/5 17/5 20/5 23/5 26/5 29/5 Figure 4: Winkler index predicted with Holt s model and Linear Regression for one zone of vineyard. Table 6 reports MSE, MAD, ET and SD value for one sample of data (26 April- 31 May) of the same Zone of vineyard. They indicate how the expected value of Winkler Index differs from that observed. As you can see the Holt s model seems to predict Winkler index value better than the Regression model. This result is verified in almost all zones of vineyard. Average values of MSE, MAD, ET and SD, calculated for all zones resulted respectively equals to 657,98, 20,53, 194,47, 25,66 for Holt s model and 1610,57, 29,91, -302,95, 37,39 for Linear Regression. Holt s model Linear Regression MSE (DD) 981, ,11 MAD (DD) 27,37 67,37 ET (DD) 153, ,28 SD (DD) 34,22 84,21 Table 3. Based on the thresholds chosen for start and end flowering dates of start and end flowering predicted with the two models for every of 15 zones were calculated. Because the expected

8 values are affected by uncertainty because of their variance, it is useful to determine the probability of a single value exceeding a threshold chosen, for example, the value of the Winkler start or end of flowering. The normal distribution can be used to determine R(σ,µ t ),where σ is the standard deviation of data provided and µ t is the value of Winkler index provided at the time t. Results are shown in Figure 5, where the probability (1-R), to exceed the threshold of beginning of flowering was calculated for each of the two linear models used for forecasting. (1-R) 1,0 0,5 0,0 Figure 5: Probability of exceeding the threshold of beginning flowering. Conclusions In the present research a method that allow to predict the evolution of maturation process for the grape wine is proposed. The research aims to demonstrate that traditional systems can be replaced by innovative and non expensive technologies such as sensors networks. However, these capabilities pose several questions in the application space regarding for example what data should be gathered and how often, how information must be processed and how should the result be presented to the user, how can the knowledge based be employed to support the decision processes. Such issues must be considered in the general framework of the design of farming decision support systems, involving the analysis of the decision processes, the establishment of decision parameters, the identification of required information and datasets and the selection of the most suitable technologies for data acquisition. As a consequence, the potential of such technologies is currently exploited to a very limited extent due to the lack of suitable decision models and post-processing procedures to be included in farming decision support systems. The proposed methodology can be effectively employed to plan and schedule the harvesting operations taking into consideration the optimal maturity of the berries and coping with constraints related to the limited stocking capacity of the winery and the availability of the harvesting machineries. References Holt Linear Regression 26-Apr 29-Apr 2-May 5-May 8-May 11-May 14-May [1] Anastasi G., Farruggia O., Lo Re G., Ortolani M., (2009). Monitoring High-Quality Wine Production using Wireless Sensor Networks, in 42st Hawaii International Conference on Systems Science : Waikoloa, Big Island, HI, USA. [2] Hellman E., (2004). How to judge Grape Ripeness Before Harvest, in 23rd Annual Meeting of New Mexico Grape Growers and Wine Makers. Albuquerque, New Mexico.February [3] Policarpo M., Pernice V., Dimino G., Cartabellotta D., (2008). Agroclimatic characterization of Monreale DOC appellation for vine growing, in VII th International terroir Congress, (Nyon, Switzerland). [4] Tonietto J., Carbonneau A.,(2004). A multicriteria climatic classification system for grape-growing regions worldwide, in Agricultural and Forest Meteorology, Volume 124, Issues 1-2, 20 July 2004, Pages [5] Watson B., (2003). Evaluation of Winegrape Maturity, in Oregon Viticulture, Editor, E.W. Hellman, Oregon State University, p. 241.

Colorado State University Viticulture and Enology. Grapevine Cold Hardiness

Colorado State University Viticulture and Enology. Grapevine Cold Hardiness Colorado State University Viticulture and Enology Grapevine Cold Hardiness Grapevine cold hardiness is dependent on multiple independent variables such as variety and clone, shoot vigor, previous season

More information

Relation between Grape Wine Quality and Related Physicochemical Indexes

Relation between Grape Wine Quality and Related Physicochemical Indexes Research Journal of Applied Sciences, Engineering and Technology 5(4): 557-5577, 013 ISSN: 040-7459; e-issn: 040-7467 Maxwell Scientific Organization, 013 Submitted: October 1, 01 Accepted: December 03,

More information

Regression Models for Saffron Yields in Iran

Regression Models for Saffron Yields in Iran Regression Models for Saffron ields in Iran Sanaeinejad, S.H., Hosseini, S.N 1 Faculty of Agriculture, Ferdowsi University of Mashhad, Iran sanaei_h@yahoo.co.uk, nasir_nbm@yahoo.com, Abstract: Saffron

More information

1. Continuing the development and validation of mobile sensors. 3. Identifying and establishing variable rate management field trials

1. Continuing the development and validation of mobile sensors. 3. Identifying and establishing variable rate management field trials Project Overview The overall goal of this project is to deliver the tools, techniques, and information for spatial data driven variable rate management in commercial vineyards. Identified 2016 Needs: 1.

More information

World of Wine: From Grape to Glass

World of Wine: From Grape to Glass World of Wine: From Grape to Glass Course Details No Prerequisites Required Course Dates Start Date: th 18 August 2016 0:00 AM UTC End Date: st 31 December 2018 0:00 AM UTC Time Commitment Between 2 to

More information

Predicting Wine Quality

Predicting Wine Quality March 8, 2016 Ilker Karakasoglu Predicting Wine Quality Problem description: You have been retained as a statistical consultant for a wine co-operative, and have been asked to analyze these data. Each

More information

COMPARISON OF CORE AND PEEL SAMPLING METHODS FOR DRY MATTER MEASUREMENT IN HASS AVOCADO FRUIT

COMPARISON OF CORE AND PEEL SAMPLING METHODS FOR DRY MATTER MEASUREMENT IN HASS AVOCADO FRUIT New Zealand Avocado Growers' Association Annual Research Report 2004. 4:36 46. COMPARISON OF CORE AND PEEL SAMPLING METHODS FOR DRY MATTER MEASUREMENT IN HASS AVOCADO FRUIT J. MANDEMAKER H. A. PAK T. A.

More information

Development of smoke taint risk management tools for vignerons and land managers

Development of smoke taint risk management tools for vignerons and land managers Development of smoke taint risk management tools for vignerons and land managers Glynn Ward, Kristen Brodison, Michael Airey, Art Diggle, Michael Saam-Renton, Andrew Taylor, Diana Fisher, Drew Haswell

More information

Study of Compatibility of Grape with East-Azerbaijan Climate

Study of Compatibility of Grape with East-Azerbaijan Climate Available online at http://www.ijabbr.com International journal of Advanced Biological and Biomedical Research Volume 2, Issue 4(2), 2014: 192-198 Study of Compatibility of Grape with East-Azerbaijan Climate

More information

DEVELOPMENT OF A RAPID METHOD FOR THE ASSESSMENT OF PHENOLIC MATURITY IN BURGUNDY PINOT NOIR

DEVELOPMENT OF A RAPID METHOD FOR THE ASSESSMENT OF PHENOLIC MATURITY IN BURGUNDY PINOT NOIR PINOT NOIR, PAGE 1 DEVELOPMENT OF A RAPID METHOD FOR THE ASSESSMENT OF PHENOLIC MATURITY IN BURGUNDY PINOT NOIR Eric GRANDJEAN, Centre Œnologique de Bourgogne (COEB)* Christine MONAMY, Bureau Interprofessionnel

More information

Elderberry Ripeness and Determination of When to Harvest. Patrick Byers, Regional Horticulture Specialist,

Elderberry Ripeness and Determination of When to Harvest. Patrick Byers, Regional Horticulture Specialist, Elderberry Ripeness and Determination of When to Harvest Patrick Byers, Regional Horticulture Specialist, byerspl@missouri.edu 1. Ripeness is an elusive concept for many people a. Ripeness is often entirely

More information

Big Data and the Productivity Challenge for Wine Grapes. Nick Dokoozlian Agricultural Outlook Forum February

Big Data and the Productivity Challenge for Wine Grapes. Nick Dokoozlian Agricultural Outlook Forum February Big Data and the Productivity Challenge for Wine Grapes Nick Dokoozlian Agricultural Outlook Forum February 2016 0 Big Data and the Productivity Challenge for Wine Grapes Outline Current production challenges

More information

The aim of the thesis is to determine the economic efficiency of production factors utilization in S.C. AGROINDUSTRIALA BUCIUM S.A.

The aim of the thesis is to determine the economic efficiency of production factors utilization in S.C. AGROINDUSTRIALA BUCIUM S.A. The aim of the thesis is to determine the economic efficiency of production factors utilization in S.C. AGROINDUSTRIALA BUCIUM S.A. The research objectives are: to study the history and importance of grape

More information

AWRI Refrigeration Demand Calculator

AWRI Refrigeration Demand Calculator AWRI Refrigeration Demand Calculator Resources and expertise are readily available to wine producers to manage efficient refrigeration supply and plant capacity. However, efficient management of winery

More information

Environmental Monitoring for Optimized Production in Wineries

Environmental Monitoring for Optimized Production in Wineries Environmental Monitoring for Optimized Production in Wineries Mounzer SALEH Applications Engineer Agenda The Winemaking Process What Makes a great a Wine? Main challenges and constraints Using Technology

More information

Relationship between Mineral Nutrition and Postharvest Fruit Disorders of 'Fuerte' Avocados

Relationship between Mineral Nutrition and Postharvest Fruit Disorders of 'Fuerte' Avocados Proc. of Second World Avocado Congress 1992 pp. 395-402 Relationship between Mineral Nutrition and Postharvest Fruit Disorders of 'Fuerte' Avocados S.F. du Plessis and T.J. Koen Citrus and Subtropical

More information

Using Growing Degree Hours Accumulated Thirty Days after Bloom to Help Growers Predict Difficult Fruit Sizing Years

Using Growing Degree Hours Accumulated Thirty Days after Bloom to Help Growers Predict Difficult Fruit Sizing Years Using Growing Degree Hours Accumulated Thirty Days after Bloom to Help Growers Predict Difficult Fruit Sizing Years G. Lopez 1 and T. DeJong 2 1 Àrea de Tecnologia del Reg, IRTA, Lleida, Spain 2 Department

More information

THE NATURAL SUSCEPTIBILITY AND ARTIFICIALLY INDUCED FRUIT CRACKING OF SOUR CHERRY CULTIVARS

THE NATURAL SUSCEPTIBILITY AND ARTIFICIALLY INDUCED FRUIT CRACKING OF SOUR CHERRY CULTIVARS THE NATURAL SUSCEPTIBILITY AND ARTIFICIALLY INDUCED FRUIT CRACKING OF SOUR CHERRY CULTIVARS S. Budan Research Institute for Fruit Growing, Pitesti, Romania sergiu_budan@yahoo.com GENERALITIES It is agreed

More information

Temperature effect on pollen germination/tube growth in apple pistils

Temperature effect on pollen germination/tube growth in apple pistils FINAL PROJECT REPORT Project Title: Temperature effect on pollen germination/tube growth in apple pistils PI: Dr. Keith Yoder Co-PI(): Dr. Rongcai Yuan Organization: Va. Tech Organization: Va. Tech Telephone/email:

More information

Vineyard IPM Scouting Report for week of 15 September 2014 UW-Extension Door County and Peninsular Agricultural Research Station

Vineyard IPM Scouting Report for week of 15 September 2014 UW-Extension Door County and Peninsular Agricultural Research Station NO. 12 1 Vineyard IPM Scouting Report for week of 15 September 2014 UW-Extension Door County and Peninsular Agricultural Research Station Cold Slows Grape Maturity Grape maturity is reliant on a number

More information

EFFECT OF TOMATO GENETIC VARIATION ON LYE PEELING EFFICACY TOMATO SOLUTIONS JIM AND ADAM DICK SUMMARY

EFFECT OF TOMATO GENETIC VARIATION ON LYE PEELING EFFICACY TOMATO SOLUTIONS JIM AND ADAM DICK SUMMARY EFFECT OF TOMATO GENETIC VARIATION ON LYE PEELING EFFICACY TOMATO SOLUTIONS JIM AND ADAM DICK 2013 SUMMARY Several breeding lines and hybrids were peeled in an 18% lye solution using an exposure time of

More information

Climate Change and Wine

Climate Change and Wine Gregory V. Jones Director: Center for Wine Education Chair: Wine Studies Professor: Environmental Studies 26-27 November, 2018 Amsterdam, Netherlands The global wine map is changing Climate change is

More information

Vintage 2006: Umpqua Valley Reference Vineyard Report

Vintage 2006: Umpqua Valley Reference Vineyard Report Vintage 2006: Umpqua Valley Reference Vineyard Report Summary: The 2006 vintage started off slow with a cool, wet spring and was followed by a largely climatically favorable growing season. The summer

More information

Activity 10. Coffee Break. Introduction. Equipment Required. Collecting the Data

Activity 10. Coffee Break. Introduction. Equipment Required. Collecting the Data . Activity 10 Coffee Break Economists often use math to analyze growth trends for a company. Based on past performance, a mathematical equation or formula can sometimes be developed to help make predictions

More information

ARIMNet2 Young Researchers Seminar

ARIMNet2 Young Researchers Seminar ARIMNet2 Young Researchers Seminar How to better involve end-users throughout the research process to foster innovation-driven research for a sustainable Mediterranean agriculture at the farm and local

More information

Innovations for a better world. Ingredient Handling For bakeries and other food processing facilities

Innovations for a better world. Ingredient Handling For bakeries and other food processing facilities Innovations for a better world. Ingredient Handling For bakeries and other food processing facilities Ingredient Handling For bakeries and other food processing facilities From grain to bread Ingredient

More information

Geographic Information Systemystem

Geographic Information Systemystem Agenda Time 9:00:-9:20 9-20 9:50 9:50 10:00 Topic Intro to GIS/Mapping and GPS Applications for GIS in Vineyards Break Presenter Kelly Bobbitt, Mike Bobbitt and Associates Kelly Bobbitt, Mike Bobbitt and

More information

Coffee zone updating: contribution to the Agricultural Sector

Coffee zone updating: contribution to the Agricultural Sector 1 Coffee zone updating: contribution to the Agricultural Sector Author¹: GEOG. Graciela Romero Martinez Authors²: José Antonio Guzmán Mailing address: 131-3009, Santa Barbara of Heredia Email address:

More information

Réseau Vinicole Européen R&D d'excellence

Réseau Vinicole Européen R&D d'excellence Réseau Vinicole Européen R&D d'excellence Lien de la Vigne / Vinelink 1 Paris, 09th March 2012 R&D is strategic for the sustainable competitiveness of the EU wine sector However R&D focus and investment

More information

wine 1 wine 2 wine 3 person person person person person

wine 1 wine 2 wine 3 person person person person person 1. A trendy wine bar set up an experiment to evaluate the quality of 3 different wines. Five fine connoisseurs of wine were asked to taste each of the wine and give it a rating between 0 and 10. The order

More information

World of Wine: From Grape to Glass Syllabus

World of Wine: From Grape to Glass Syllabus World of Wine: From Grape to Glass Syllabus COURSE OVERVIEW Have you always wanted to know more about how grapes are grown and wine is made? Perhaps you like a specific wine, but can t pinpoint the reason

More information

TEMPERATURE CONDITIONS AND TOLERANCE OF AVOCADO FRUIT TISSUE

TEMPERATURE CONDITIONS AND TOLERANCE OF AVOCADO FRUIT TISSUE California Avocado Society 1961 Yearbook 45: 87-92 TEMPERATURE CONDITIONS AND TOLERANCE OF AVOCADO FRUIT TISSUE C. A. Schroeder and Ernest Kay Professor of Botany. University of California, Los Angeles;

More information

RESOLUTION OIV-ECO

RESOLUTION OIV-ECO RESOLUTION OIV-ECO 563-2016 TRAINING PROGRAMS FOR OENOLOGISTS THE GENERAL ASSEMBLY, based on the work of the FORMAT Expert Group, CONSIDERING the resolution OIV-ECO 492-2013 providing the definition of

More information

Thermal Hydraulic Analysis of 49-2 Swimming Pool Reactor with a. Passive Siphon Breaker

Thermal Hydraulic Analysis of 49-2 Swimming Pool Reactor with a. Passive Siphon Breaker Thermal Hydraulic Analysis of 49-2 Swimming Pool Reactor with a Passive Siphon Breaker Zhiting Yue 1, Songtao Ji 1 1) China Institute of Atomic Energy(CIAE), Beijing 102413, China Corresponding author:

More information

Identification of Adulteration or origins of whisky and alcohol with the Electronic Nose

Identification of Adulteration or origins of whisky and alcohol with the Electronic Nose Identification of Adulteration or origins of whisky and alcohol with the Electronic Nose Dr Vincent Schmitt, Alpha M.O.S AMERICA schmitt@alpha-mos.com www.alpha-mos.com Alpha M.O.S. Eastern Analytical

More information

Computerized Models for Shelf Life Prediction of Post-Harvest Coffee Sterilized Milk Drink

Computerized Models for Shelf Life Prediction of Post-Harvest Coffee Sterilized Milk Drink Libyan Agriculture esearch Center Journal International (6): 74-78, 011 ISSN 19-4304 IDOSI Publications, 011 Computerized Models for Shelf Life Prediction of Post-Harvest Coffee Sterilized Milk Drink 1

More information

Wine-Tasting by Numbers: Using Binary Logistic Regression to Reveal the Preferences of Experts

Wine-Tasting by Numbers: Using Binary Logistic Regression to Reveal the Preferences of Experts Wine-Tasting by Numbers: Using Binary Logistic Regression to Reveal the Preferences of Experts When you need to understand situations that seem to defy data analysis, you may be able to use techniques

More information

Grape Growers of Ontario Developing key measures to critically look at the grape and wine industry

Grape Growers of Ontario Developing key measures to critically look at the grape and wine industry Grape Growers of Ontario Developing key measures to critically look at the grape and wine industry March 2012 Background and scope of the project Background The Grape Growers of Ontario GGO is looking

More information

D Lemmer and FJ Kruger

D Lemmer and FJ Kruger D Lemmer and FJ Kruger Lowveld Postharvest Services, PO Box 4001, Nelspruit 1200, SOUTH AFRICA E-mail: fjkruger58@gmail.com ABSTRACT This project aims to develop suitable storage and ripening regimes for

More information

Notes on the Philadelphia Fed s Real-Time Data Set for Macroeconomists (RTDSM) Capacity Utilization. Last Updated: December 21, 2016

Notes on the Philadelphia Fed s Real-Time Data Set for Macroeconomists (RTDSM) Capacity Utilization. Last Updated: December 21, 2016 1 Notes on the Philadelphia Fed s Real-Time Data Set for Macroeconomists (RTDSM) Capacity Utilization Last Updated: December 21, 2016 I. General Comments This file provides documentation for the Philadelphia

More information

Business Statistics /82 Spring 2011 Booth School of Business The University of Chicago Final Exam

Business Statistics /82 Spring 2011 Booth School of Business The University of Chicago Final Exam Business Statistics 41000-81/82 Spring 2011 Booth School of Business The University of Chicago Final Exam Name You may use a calculator and two cheat sheets. You have 3 hours. I pledge my honor that I

More information

Drought in Northern Mexico by Andrea Munoz-Hernandez

Drought in Northern Mexico by Andrea Munoz-Hernandez Drought in Northern Mexico by Andrea Munoz-Hernandez Objective and Tasks The objective of this presentation is to perform a brief overview of the impacts of drought during the late twentieth century and

More information

Sustainable oenology and viticulture: new strategies and trends in wine production

Sustainable oenology and viticulture: new strategies and trends in wine production Sustainable oenology and viticulture: new strategies and trends in wine production Dr. Vassileios Varelas Oenologist-Agricultural Engineer Wine and Vine Consultant Sweden Aim of the presentation Offer

More information

Buying Filberts On a Sample Basis

Buying Filberts On a Sample Basis E 55 m ^7q Buying Filberts On a Sample Basis Special Report 279 September 1969 Cooperative Extension Service c, 789/0 ite IP") 0, i mi 1910 S R e, `g,,ttsoliktill:torvti EARs srin ITQ, E,6

More information

Advancing Agriculture Grape Industry Development Program

Advancing Agriculture Grape Industry Development Program 2017-2018 Advancing Agriculture Grape Industry Development Program 1) Objectives: To provide assistance for the establishment of new or more productive vineyards. To assist with the adoption of new technologies

More information

Research Report: Use of Geotextiles to Reduce Freeze Injury in Ontario Vineyards

Research Report: Use of Geotextiles to Reduce Freeze Injury in Ontario Vineyards Research Report: Use of Geotextiles to Reduce Freeze Injury in Ontario Vineyards Prepared by Dr. Jim Willwerth CCOVI, Brock University February 26, 20 1 Cool Climate Oenology & Viticulture Institute Brock

More information

Harvest times vary between growing regions and seasons. As an approximation, harvest times for the most common types are:

Harvest times vary between growing regions and seasons. As an approximation, harvest times for the most common types are: Harvest Maturity Asian pear varieties (ie. Pyrus bretschneideri, Pyrus pyrifolia, Pyrus ussuariensis) more commonly known as nashi typically ripen on the tree. European pears (ie. Pyrus communis) such

More information

Online Appendix to. Are Two heads Better Than One: Team versus Individual Play in Signaling Games. David C. Cooper and John H.

Online Appendix to. Are Two heads Better Than One: Team versus Individual Play in Signaling Games. David C. Cooper and John H. Online Appendix to Are Two heads Better Than One: Team versus Individual Play in Signaling Games David C. Cooper and John H. Kagel This appendix contains a discussion of the robustness of the regression

More information

Mechanical Canopy and Crop Load Management of Pinot Gris. Joseph P. Geller and S. Kaan Kurtural

Mechanical Canopy and Crop Load Management of Pinot Gris. Joseph P. Geller and S. Kaan Kurtural Mechanical Canopy and Crop Load Management of Pinot Gris Joseph P. Geller and S. Kaan Kurtural 3.6 million tons of wine grapes grown in CA More than 50% comes from the San Joaquin Valley More than 60%

More information

INFLUENCE OF THIN JUICE ph MANAGEMENT ON THICK JUICE COLOR IN A FACTORY UTILIZING WEAK CATION THIN JUICE SOFTENING

INFLUENCE OF THIN JUICE ph MANAGEMENT ON THICK JUICE COLOR IN A FACTORY UTILIZING WEAK CATION THIN JUICE SOFTENING INFLUENCE OF THIN JUICE MANAGEMENT ON THICK JUICE COLOR IN A FACTORY UTILIZING WEAK CATION THIN JUICE SOFTENING Introduction: Christopher D. Rhoten The Amalgamated Sugar Co., LLC 5 South 5 West, Paul,

More information

WINE RECOGNITION ANALYSIS BY USING DATA MINING

WINE RECOGNITION ANALYSIS BY USING DATA MINING 9 th International Research/Expert Conference Trends in the Development of Machinery and Associated Technology TMT 2005, Antalya, Turkey, 26-30 September, 2005 WINE RECOGNITION ANALYSIS BY USING DATA MINING

More information

Module 6. Yield and Fruit Size. Presenter: Stephan Verreynne

Module 6. Yield and Fruit Size. Presenter: Stephan Verreynne Presenter: Stephan Verreynne definition Yield Yield refers to the amount of fruit produced, and can be expressed in terms of: Tree yield kg per tree kg/tree Orchard yield tons per hectare t/ha Export yield

More information

2012 Research Report Michigan Grape & Wine Industry Council

2012 Research Report Michigan Grape & Wine Industry Council 2012 Research Report Michigan Grape & Wine Industry Council Early leaf removal to improve crop control, cluster morphology and berry quality in vinifera grapes Paolo Sabbatini 1 and Annemiek Schilder 2

More information

Certified Home Brewer Program. Minimum Certification Requirements

Certified Home Brewer Program. Minimum Certification Requirements Certified Home Brewer Program Minimum Certification Requirements SCA's Minimum Certification Requirements for Coffee Brewers 1. Coffee Volume: The volume of the brew basket must be sized in proportion

More information

Roaster/Production Operative. Coffee for The People by The Coffee People. Our Values: The Role:

Roaster/Production Operative. Coffee for The People by The Coffee People. Our Values: The Role: Are you an enthusiastic professional with a passion for ensuring the highest quality and service for your teams? At Java Republic we are currently expanding, so we are looking for an Roaster/Production

More information

Current trends of agroclimatic indices applied to grapevine and olive tree in central Italy

Current trends of agroclimatic indices applied to grapevine and olive tree in central Italy UNIVERSITY OF FLORENCE Department of Agronomy and Land Management Current trends of agroclimatic indices applied to grapevine and olive tree in central Italy Simone Orlandini, Valentina Di Stefano, Annalena

More information

Optimising harvest date through use of an integrated grape compositional and sensory model

Optimising harvest date through use of an integrated grape compositional and sensory model Optimising harvest date through use of an integrated grape compositional and sensory model Alain DELOIRE, Katja ŠUKLJE, Guillaume ANTALICK, Campbell MEEKS, John W. BLACKMAN & Leigh M. SCHMIDTKE National

More information

THE EFFECT OF DIFFERENT APPLICATIONS ON FRUIT YIELD CHARACTERISTICS OF STRAWBERRIES CULTIVATED UNDER VAN ECOLOGICAL CONDITION ABSTRACT

THE EFFECT OF DIFFERENT APPLICATIONS ON FRUIT YIELD CHARACTERISTICS OF STRAWBERRIES CULTIVATED UNDER VAN ECOLOGICAL CONDITION ABSTRACT Gecer et al., The Journal of Animal & Plant Sciences, 23(5): 2013, Page: J. 1431-1435 Anim. Plant Sci. 23(5):2013 ISSN: 1018-7081 THE EFFECT OF DIFFERENT APPLICATIONS ON FRUIT YIELD CHARACTERISTICS OF

More information

FREQUENTLY ASKED QUESTIONS (FAQS)

FREQUENTLY ASKED QUESTIONS (FAQS) FREQUENTLY ASKED QUESTIONS (FAQS) Table of Contents CAS FAQ... 4 1.1... CAS FAQ 4 2 1.1.1 What is Coffee Assurance Services (CAS)? 4 1.1.2 What is the vision of Coffee Assurance Services? 4 1.1.3 What

More information

Effect of SPT Hammer Energy Efficiency in the Bearing Capacity Evaluation in Sands

Effect of SPT Hammer Energy Efficiency in the Bearing Capacity Evaluation in Sands Proceedings of the 2 nd World Congress on Civil, Structural, and Environmental Engineering (CSEE 17) Barcelona, Spain April 2 4, 2017 Paper No. ICGRE 123 ISSN: 2371-5294 DOI: 10.11159/icgre17.123 Effect

More information

ANALYSIS OF THE EVOLUTION AND DISTRIBUTION OF MAIZE CULTIVATED AREA AND PRODUCTION IN ROMANIA

ANALYSIS OF THE EVOLUTION AND DISTRIBUTION OF MAIZE CULTIVATED AREA AND PRODUCTION IN ROMANIA ANALYSIS OF THE EVOLUTION AND DISTRIBUTION OF MAIZE CULTIVATED AREA AND PRODUCTION IN ROMANIA Agatha POPESCU University of Agricultural Sciences and Veterinary Medicine, Bucharest, 59 Marasti, District

More information

The Implications of Climate Change for the Ontario Wine Industry

The Implications of Climate Change for the Ontario Wine Industry The Implications of Climate Change for the Ontario Wine Industry Tony B. Shaw Department of Geography and Cool Climate Oenology and Viticulture Institute Brock University Climate Change Most scientists

More information

Introduction to Management Science Midterm Exam October 29, 2002

Introduction to Management Science Midterm Exam October 29, 2002 Answer 25 of the following 30 questions. Introduction to Management Science 61.252 Midterm Exam October 29, 2002 Graphical Solutions of Linear Programming Models 1. Which of the following is not a necessary

More information

COFFEE YIELD VARIATIONS AND THEIR RELATIONS TO RAINFALL EVENTS IN NICARAGUA

COFFEE YIELD VARIATIONS AND THEIR RELATIONS TO RAINFALL EVENTS IN NICARAGUA PA 254 COFFEE YIELD VARIATIONS AND THEIR RELATIONS TO RAINFALL EVENTS IN NICARAGUA LARA, Leonel 1,2 *, HAGGAR, Jeremy 3, STOIAN, Dietmar 1, RAPIDEL, Bruno 1,4 1 2 Research Unit Sustainability and Global

More information

The Market Potential for Exporting Bottled Wine to Mainland China (PRC)

The Market Potential for Exporting Bottled Wine to Mainland China (PRC) The Market Potential for Exporting Bottled Wine to Mainland China (PRC) The Machine Learning Element Data Reimagined SCOPE OF THE ANALYSIS This analysis was undertaken on behalf of a California company

More information

Current trends of agroclimatic indices applied to grapevine and olive tree in central Italy

Current trends of agroclimatic indices applied to grapevine and olive tree in central Italy UNIVERSITY OF FLORENCE Department of Agronomy and Land Management Current trends of agroclimatic indices applied to grapevine and olive tree in central Italy Simone Orlandini, Valentina Di Stefano, Annalena

More information

Monitoring High-Quality Wine Production using Wireless Sensor Networks

Monitoring High-Quality Wine Production using Wireless Sensor Networks Monitoring High-Quality Wine Production using Wireless Sensor Networks Giuseppe Anastasi, Orazio Farruggia, Giuseppe Lo Re, and Marco Ortolani Dept. of Information Engineering, University of Pisa Via Diotisalvi,

More information

Greenhouse Effect Investigating Global Warming

Greenhouse Effect Investigating Global Warming Greenhouse Effect Investigating Global Warming OBJECTIVE Students will design three different environments, including a control group. They will identify which environment results in the greatest temperature

More information

IMPROVING THE PROCEDURE FOR NUTRIENT SAMPLING IN STONE FRUIT TREES

IMPROVING THE PROCEDURE FOR NUTRIENT SAMPLING IN STONE FRUIT TREES IMPROVING THE PROCEDURE FOR NUTRIENT SAMPLING IN STONE FRUIT TREES PROJECT LEADER R. Scott Johnson U.C. Kearney Agricultural Center 9240 S. Riverbend Avenue Parlier, CA 9364 (559) 646-6547, FAX (559) 646-6593

More information

and the World Market for Wine The Central Valley is a Central Part of the Competitive World of Wine What is happening in the world of wine?

and the World Market for Wine The Central Valley is a Central Part of the Competitive World of Wine What is happening in the world of wine? The Central Valley Winegrape Industry and the World Market for Wine Daniel A. Sumner University it of California i Agricultural l Issues Center January 5, 211 The Central Valley is a Central Part of the

More information

21/06/2009. Metric Tons (000) '95 '96 '97 '98 '99 '00 '01 '02 '03 '

21/06/2009. Metric Tons (000) '95 '96 '97 '98 '99 '00 '01 '02 '03 ' How Increasing Temperatures Have Reduced Yields and Quality of Californian i Tree Fruit in Warm Years Ted DeJong Department of Plant Sciences UC Davis While much of the climate change discussion is focused

More information

March 2017 DATA-DRIVEN INSIGHTS FOR VINEYARDS

March 2017 DATA-DRIVEN INSIGHTS FOR VINEYARDS March 2017 DATA-DRIVEN INSIGHTS FOR VINEYARDS What do great wine, water on mars and drones have in common? Today: Drone Technologies in Viticulture AGENDA Technology Context: big data, precision ag, drones

More information

Product Consistency Comparison Study: Continuous Mixing & Batch Mixing

Product Consistency Comparison Study: Continuous Mixing & Batch Mixing July 2015 Product Consistency Comparison Study: Continuous Mixing & Batch Mixing By: Jim G. Warren Vice President, Exact Mixing Baked snack production lines require mixing systems that can match the throughput

More information

ANALYSIS OF CLIMATIC FACTORS IN CONNECTION WITH STRAWBERRY GENERATIVE BUD DEVELOPMENT

ANALYSIS OF CLIMATIC FACTORS IN CONNECTION WITH STRAWBERRY GENERATIVE BUD DEVELOPMENT AGRICULTURAL SCIENCES (CROP SCIENCES, ANIMAL SCIENCES) ANALYSIS OF CLIMATIC FACTORS IN CONNECTION WITH STRAWBERRY GENERATIVE BUD DEVELOPMENT Ieva Kalniņa 1,, Sarmīte Strautiņa 1 Latvia University of Agriculture

More information

MBA 503 Final Project Guidelines and Rubric

MBA 503 Final Project Guidelines and Rubric MBA 503 Final Project Guidelines and Rubric Overview There are two summative assessments for this course. For your first assessment, you will be objectively assessed by your completion of a series of MyAccountingLab

More information

International Journal of Business and Commerce Vol. 3, No.8: Apr 2014[01-10] (ISSN: )

International Journal of Business and Commerce Vol. 3, No.8: Apr 2014[01-10] (ISSN: ) The Comparative Influences of Relationship Marketing, National Cultural values, and Consumer values on Consumer Satisfaction between Local and Global Coffee Shop Brands Yi Hsu Corresponding author: Associate

More information

Introduction to the Practical Exam Stage 1

Introduction to the Practical Exam Stage 1 Introduction to the Practical Exam Stage 1 2 Agenda Exam Structure How MW Practical Differs from Other Exams What You Must Know How to Approach Exam Questions Time Management Practice Methodologies Stage

More information

Specific mediterranean characteristics. Mediterranean climate

Specific mediterranean characteristics. Mediterranean climate Effect of global warming in mediterranean conditions Climate change - Average temperatures increase and efficient rainfalls decrease Consequences for vines and grapes - Shortening of phenologic stages

More information

Vineyard Cash Flows Tremain Hatch

Vineyard Cash Flows Tremain Hatch Vineyard Cash Flows Tremain Hatch thatch@vt.edu New grape growers Contemplating retirement or other transitions and considering viticulture and winemaking Alternative crop to existing farm operation Questions

More information

Vinelink Autumn Workshop (October 2012, 25th) Strategies for Reducing Inputs to Winegrowing and Results

Vinelink Autumn Workshop (October 2012, 25th) Strategies for Reducing Inputs to Winegrowing and Results Vinelink Autumn Workshop (October 2012, 25th) Strategies for Reducing Inputs to Winegrowing and Results Vinelink Autumn Workshop Strategies for reducing inputs to winegrowing and results Participants :

More information

Training system considerations

Training system considerations Comparative results of three training systems in Winchester VVA Meeting: 13-15 Feb 2003 Tony K. Wolf Professor of Viticulture Training system considerations Why research training systems in Virginia? increase

More information

PEEL RIVER HEALTH ASSESSMENT

PEEL RIVER HEALTH ASSESSMENT PEEL RIVER HEALTH ASSESSMENT CONTENTS SUMMARY... 2 Overall River Health Scoring... 2 Overall Data Sufficiency Scoring... 2 HYDROLOGY... 3 Overall Hydrology River Health Scoring... 3 Hydrology Data Sufficiency...

More information

Research - Strawberry Nutrition

Research - Strawberry Nutrition Research - Strawberry Nutrition The Effect of Increased Nitrogen and Potassium Levels within the Sap of Strawberry Leaf Petioles on Overall Yield and Quality of Strawberry Fruit as Affected by Justification:

More information

OenoFoss. Instant quality control throughout the winemaking process. Dedicated Analytical Solutions

OenoFoss. Instant quality control throughout the winemaking process. Dedicated Analytical Solutions OenoFoss Instant quality control throughout the winemaking process The Oenofoss is a dedicated analyser for rapid, routine measurement of key parameters in winemaking. You can measure multiple components

More information

The Development of a Weather-based Crop Disaster Program

The Development of a Weather-based Crop Disaster Program The Development of a Weather-based Crop Disaster Program Eric Belasco Montana State University 2016 SCC-76 Conference Pensacola, FL March 19, 2016. Belasco March 2016 1 / 18 Motivation Recent efforts to

More information

Plant root activity is limited to the soil bulbs Does not require technical expertise to. wetted by the water bottle emitter implement

Plant root activity is limited to the soil bulbs Does not require technical expertise to. wetted by the water bottle emitter implement Case Study Bottle Drip Irrigation Case Study Background Data Tool Category: Adaptation on the farm Variety: Robusta Climatic Hazard: Prolonged dry spells and high temperatures Expected Outcome: Improved

More information

Gasoline Empirical Analysis: Competition Bureau March 2005

Gasoline Empirical Analysis: Competition Bureau March 2005 Gasoline Empirical Analysis: Update of Four Elements of the January 2001 Conference Board study: "The Final Fifteen Feet of Hose: The Canadian Gasoline Industry in the Year 2000" Competition Bureau March

More information

What Went Wrong with Export Avocado Physiology during the 1996 Season?

What Went Wrong with Export Avocado Physiology during the 1996 Season? South African Avocado Growers Association Yearbook 1997. 20:88-92 What Went Wrong with Export Avocado Physiology during the 1996 Season? F J Kruger V E Claassens Institute for Tropical and Subtropical

More information

Archival copy. For current information, see the OSU Extension Catalog: https://catalog.extension.oregonstate.edu/em9070

Archival copy. For current information, see the OSU Extension Catalog: https://catalog.extension.oregonstate.edu/em9070 EM 9070 June 2013 How to Measure Grapevine Leaf Area Patricia A. Skinkis and R. Paul Schreiner Figure 1. A leaf area template can be easily made using typical office supplies. The template, above, is being

More information

1 a) State three leadership styles used by a food and beverage supervisor. (3 marks)

1 a) State three leadership styles used by a food and beverage supervisor. (3 marks) Sample Mark Scheme 1 State three leadership styles used by a food and beverage supervisor. For each style of leadership stated in, explain a situation when it would be appropriate to be used. Autocratic

More information

Multiple Imputation for Missing Data in KLoSA

Multiple Imputation for Missing Data in KLoSA Multiple Imputation for Missing Data in KLoSA Juwon Song Korea University and UCLA Contents 1. Missing Data and Missing Data Mechanisms 2. Imputation 3. Missing Data and Multiple Imputation in Baseline

More information

Increasing the efficiency of forecasting winegrape yield by using information on spatial variability to select sample sites

Increasing the efficiency of forecasting winegrape yield by using information on spatial variability to select sample sites Increasing the efficiency of forecasting winegrape yield by using information on spatial variability to select sample sites Andrew Hall, Research Fellow, Spatial Science Leo Quirk, Viticulture Extension

More information

Chile. Tree Nuts Annual. Almonds and Walnuts Annual Report

Chile. Tree Nuts Annual. Almonds and Walnuts Annual Report THIS REPORT CONTAINS ASSESSMENTS OF COMMODITY AND TRADE ISSUES MADE BY USDA STAFF AND NOT NECESSARILY STATEMENTS OF OFFICIAL U.S. GOVERNMENT POLICY Required Report - public distribution Date: GAIN Report

More information

Evaluation of desiccants to facilitate straight combining canola. Brian Jenks North Dakota State University

Evaluation of desiccants to facilitate straight combining canola. Brian Jenks North Dakota State University Evaluation of desiccants to facilitate straight combining canola Brian Jenks North Dakota State University The concept of straight combining canola is gaining favor among growers in North Dakota. The majority

More information

GrillCam: A Real-time Eating Action Recognition System

GrillCam: A Real-time Eating Action Recognition System GrillCam: A Real-time Eating Action Recognition System Koichi Okamoto and Keiji Yanai The University of Electro-Communications, Tokyo 1-5-1 Chofu, Tokyo 182-8585, JAPAN {okamoto-k@mm.inf.uec.ac.jp,yanai@cs.uec.ac.jp}

More information

RESOLUTION OIV-VITI OIV GUIDE FOR IMPLEMENTATION OF THE HACCP SYSTEM (HAZARD ANALYSIS AND CRITICAL CONTROL POINTS) TO VITICULTURE

RESOLUTION OIV-VITI OIV GUIDE FOR IMPLEMENTATION OF THE HACCP SYSTEM (HAZARD ANALYSIS AND CRITICAL CONTROL POINTS) TO VITICULTURE RESOLUTION OIV-VITI 469-2012 OIV GUIDE FOR IMPLEMENTATION OF THE HACCP SYSTEM (HAZARD ANALYSIS AND CRITICAL CONTROL POINTS) TO VITICULTURE THE GENERAL ASSEMBLY Following the proposal of Commission I Viticulture

More information

Smoke Taint Risk Management Tools

Smoke Taint Risk Management Tools Smoke Taint Risk Management Tools Glynn Ward, Art Diggle, Michael Saam-Renton 2, and Michael Airey 2, Kristen Kennison, Diana Fisher, Drew Haswell 3, John Gillard 3 Department of Agriculture and Food WA

More information

IT 403 Project Beer Advocate Analysis

IT 403 Project Beer Advocate Analysis 1. Exploratory Data Analysis (EDA) IT 403 Project Beer Advocate Analysis Beer Advocate is a membership-based reviews website where members rank different beers based on a wide number of categories. The

More information

Sustainable Coffee Challenge FAQ

Sustainable Coffee Challenge FAQ Sustainable Coffee Challenge FAQ What is the Sustainable Coffee Challenge? The Sustainable Coffee Challenge is a pre-competitive collaboration of partners working across the coffee sector, united in developing

More information

Oregon Wine Industry Sustainable Showcase. Gregory V. Jones

Oregon Wine Industry Sustainable Showcase. Gregory V. Jones Oregon Wine Industry Sustainable Showcase Gregory V. Jones Panel Framework Oregon wineries and vineyards are implementing innovative sustainability and environmental practices across the entire system

More information