Occurrence of Hyd R3 fenhexamid resistance among Botrytis isolates in Northern German soft fruit production

2010 ◽  
Vol 117 (4) ◽  
pp. 177-179 ◽  
Author(s):  
R. W. S. Weber
Keyword(s):  
Fruit Production ◽  
Soft Fruit

Horticultural food crops

1986 ◽  
Vol 87 (3-4) ◽  
pp. 165-172
Author(s):  
C. E. Taylor
Keyword(s):  
Crop Production ◽  
Fruit Production ◽  
Fruit And Vegetables ◽  
Border Region ◽  
Food Crops ◽  
Vegetable Production ◽  
Processing Industry ◽  
Horticultural Crops ◽  
Moray Firth ◽  
Soft Fruit

SynopsisIn Scotland horticultural food crops occupy about 1·4% of the tillage land, and contribute about 4% of the total Scottish agricultural output. Climate, soil type and factors such as distance to markets and availability of labour have influenced the location of horticultural crops. This has changed with time, particularly because of the influence of the processing industry. Soft fruit production (3,630 hectares), with raspberries being the dominant crop, is concentrated in the Tayside region; more than 90% of the raspberry crop is processed by pulping (for jam, etc.), freezing or canning. Vegetable production (6,130 hectares) is somewhat more dispersed from the Border region to the Moray Firth; more than half the total area is occupied by peas for canning and freezing. Glasshouse production of tomatoes is now only 25 hectares located mainly in the Clyde Valley.The future for Scottish horticultural food production will continue to be influenced by the requirements of the processing industry, but there is also an increasing outlet for fresh fruit and vegetables in supermarkets. Expansion of the production of horticultural food crops in Scotland depends on the ability of the industry to meet market demands in terms of quality and continuity of supply. Increasing reference to the need for an improved British diet may stimulate the consumption of fruit and vegetables on the home market and there continue to be opportunities for increasing the export of processed and fresh produce. Scotland has the land resources, crop production expertise and processing and marketing facilities to respond to these opportunities.

scholarly journals RASberry - Robotic and Autonomous Systems for Berry Production

2018 ◽  
Vol 140 (06) ◽  
pp. S14-S18
Author(s):  
Pål Johan From ◽  
Lars Grimstad ◽  
Marc Hanheide ◽  
Simon Pearson ◽  
Grzegorz Cielniak
Keyword(s):  
Control Point ◽  
Autonomous Systems ◽  
Fruit Production ◽  
Point Of View ◽  
Production Costs ◽  
Term Operation ◽  
Manual Labour ◽  
Soft Fruit ◽  
Human Robot Collaboration

The soft fruit industry is facing unprecedented challenges due to its reliance of manual labour. We are presenting a newly launched robotics initiative which will help to address the issues faced by the industry and enable automation of the main processes involved in soft fruit production. The RASberry project (Robotics and Autonomous Systems for Berry Production) aims to develop autonomous fleets of robots for horticultural industry. To achieve this goal, the project will bridge several current technological gaps including the development of a mobile platform suitable for the strawberry fields, software components for fleet management, in-field navigation and mapping, long-term operation, and safe human-robot collaboration. In this paper, we provide a general overview of the project, describe the main system components, highlight interesting challenges from a control point of view and then present three specific applications of the robotic fleets in soft fruit production. The applications demonstrate how robotic fleets can benefit the soft fruit industry by significantly decreasing production costs, addressing labour shortages and being the first step towards fully autonomous robotic systems for agriculture.

scholarly journals Assuring autonomy of robots in soft fruit production

2021 ◽  
Author(s):  
Muhammad Khalid ◽  
◽  
Leonardo Guevara ◽  
Marc Hanheide ◽  
Simon Parsons ◽  
...  
Keyword(s):  
Fruit Production ◽  
Soft Fruit

scholarly journals The fertilization problems of cultivated red- and black currant varieties in Hungary

2002 ◽  
Vol 8 (2) ◽  
Author(s):  
A. Porpáczy
Keyword(s):  
Fruit Set ◽  
Fruit Production ◽  
Important Change ◽  
Climatic Conditions ◽  
Commercial Production ◽  
Black Currant ◽  
Small Fruit ◽  
Soft Fruit ◽  
Labour Power ◽  
Red Currant

Small fruits have a modest share in the fruit production of Hungarys. Red currant was grown traditionally in home gardens 60-70 years ago. Commercial production was established only in the surroundings of some town. The black currant was unknown until after Wold War II. An important change occured in small fruit production in the 1950s. Socialist countries, which had cheaper labour power, made efforts to meet these demands. In this time we produced 25.000 t. Presently the country produces 13-15.000 tons currant fruit yearly 60% from this is black currant, which has a better market. It is our own interest to make our currant production more profitable. The currant is the second most widely cultivated soft fruit. Our product is disposed mostly on EU markets. There was no breeding activity in this field in Hungary earlier. Cultivars used were mostly of foreign origin (W. European; Boskoop Giant, Silvergieter, Wellington XXX, Russian; Altaiskaya Desertnaya, Neosupaiuschaiasya, N. European; Brikltorp, Ojebyn). Besides well-known advantageous this cultivars have also some defects mainly unfavourable—adaptation to climatic conditions, which caused fertilisation problems, reduced the fruit set and uneven growth with decreased yields (Dénes & Porpáczy, 1999). About 140 black currant cultivars were investigated during the last four decades in our variety trials and only four of them were introduced with satisfying yielding capacity (3.5-5.5 t/ha).

Climate Change Impacts on UK Top and Soft Fruit Production

2010 ◽  
Vol 39 (4) ◽  
pp. 257-262 ◽  
Author(s):  
Mark Else ◽  
Chris Atkinson
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Fruit Production ◽  
Soft Fruit

scholarly journals INNOVATION TECHNOLOGIES IN SOFT FRUIT PRODUCTION

2019 ◽  
Vol 17 (Suppl.1) ◽  
pp. 215-220
Author(s):  
Dobri Dunchev
Keyword(s):  
New Technologies ◽  
Nutrient Use Efficiency ◽  
Fruit Production ◽  
High Tech ◽  
Water Shortages ◽  
Innovative Methods ◽  
Nutrient Use ◽  
Efficiency Increase ◽  
Soft Fruit ◽  
Use Efficiency

The global challenges associated with climate change, food security and the growing instability with land and water shortages are changing the agriculture. The innovation technologies are crucially important to meet those issues and to improve productivity and sustainability of agricultural production. The aim of the study is to analyze the innovative technologies that could help farmers to improve soft fruit producing. The paper uses various methods of analysis – graphic, comparative and statistical. The new technologies in high-tech greenhouse horticulture are observed. The survey focuses on sensors (sensors for measuring water and air temperature, advanced sensors to determine microclimate and the activity of the crop) energy solutions, production technology, polytunnels, precision irrigation and robotics. The results indicate that the innovation technologies could improve water and nutrient use efficiency, increase yields and reduce the environmental impact. The innovation technologies in fruit sector are also important for human health. The implementation of innovative methods could stimulate the production of quality fruits which are environmentally friendly and internationally competitive.

Klasifikasi Tahap Kematangan Pisang Ambon Berdasarkan Warna Menggunakan Naive Bayes

2018 ◽  
Vol 5 (2) ◽  
pp. 60-67 ◽  
Author(s):  
Dwi Yulianto ◽  
Retno Nugroho Whidhiasih ◽  
Maimunah Maimunah
Keyword(s):  
Naive Bayes ◽  
Fruit Production ◽  
Naïve Bayes ◽  
Primary Data ◽  
Banana Fruit ◽  
Bayes Method ◽  
Classification Image ◽  
Average Accuracy ◽  
The Government

ABSTRACT   Banana fruit is a commodity that contributes a great value to both national and international fruit production achievement. The government through the National Standardization Agency establishes standards to maintain the quality of bananas. The purpose of this Project is to classify the stages of maturity of Ambon banana base on the color index using Naïve Bayes method in accordance with the regulations of SNI 7422:2009. Naive Bayes is used as a method in the classification process by comparing the probability values generated from the variable value of each model to determine the stage of Ambon banana maturity. The data used is the primary data image of 105 pieces of Ambon banana. By using 3 models which consists of different variables obtained the same greatest average accuracy by using the 2nd model which has 9 variable values (r, g, b, v, * a, * b, entropy, energy, and homogeneity) and the 3rd model has 7 variable values (r, g, b, v , * a, entropy and homogeneity) that is 90.48%.   Keywords: banana maturity, classification, image processing     ABSTRAK   Buah pisang merupakan komoditas yang memberikan kontribusi besar terhadap angka produksi buah nasional maupun internasional. Pemerintah melalui Badan Standarisasi Nasional menetapkan standar untuk buah pisang, menjaga mutu  buah pisang. Tujuan dari penelitian ini adalah klasifikasi tahapan kematangan dari buah pisang ambon berdasarkan indeks warna menggunakan metode Naïve Bayes  sesuai dengan SNI 7422:2009. Naive bayes digunakan sebagai metode dalam proses pengklasifikasian dengan cara membandingkan nilai probabilitas yang dihasilkan dari nilai variabel penduga setiap model untuk menentukan tahap kematangan pisang ambon. Data yang digunakan adalah data primer citra pisang ambon sebanyak 105. Dengan menggunakan 3 buah model yang terdiri dari variabel penduga yang berbeda didapatkan akurasi rata-rata terbesar yang sama yaitu dengan menggunakan model ke-2 yang mempunyai 9 nilai variabel (r, g, b, v, *a, *b, entropi, energi, dan homogenitas) dan model ke-3 yang mempunyai 7 nilai variabel (r, g, b, v, *a, entropi dan homogenitas) yaitu sebesar 90.48%.   Kata Kunci : kematangan pisang,  klasifikasi, pengolahan citra

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