No 1/2021, March | Agris on-line Papers in Economics and Informatics

Are Yam Farmers Aware and Willing to Adopt the Aeroponics Farming System in Oyo State, Nigeria?

Abimbola Oluyemisi Adepoju Oluwadamilola Christiana Olaseni DOI: 10.7160/aol.2021.130101
No 1/2021, March
pp. 3 - 13

ABSTRACT

Despite the immense returns of new agricultural technologies to increase agricultural productivity and meet rising food demand, there is a lag in the adoption of these technologies by farmers. The aeroponics system is one of such innovative technologies implemented for seed yam propagation. This study assessed the awareness and the determinants of the willingness of yam farmers to adopt the aeroponics farming system, employing the likert scale and the logit regression model. Results showed that more than three-fifths of the farmers had never heard of the aeroponics farming system but were willing to adopt it for yam and seed yam propagation, although high cost of capital required for adoption was a major constraint. Key determinants of farmers' awareness of the aeroponics system include gender, age, education, membership of cooperative society, monthly income and access to extension agent, while the main factors influencing its adoption were marital status, age, access to credit, membership of cooperative society, farm size and income. Efforts at dissemination of aeroponics farming system for increased productivity should be intensified for its effective adoption by the farmers.

KEYWORDS

The aeroponics system, yam farmers, awareness, perception, willingness to adopt.

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Diamond Model and Competition of Rubber Export Markets: Evidence from Sumatra Economic Growth Center

Ansofino Ansonfino Zusmelia Zusmelia Lovelly Dwinda Dahen Yossi Eka Puteri DOI: 10.7160/aol.2021.130102
No 1/2021, March
pp. 15 - 27

ABSTRACT

The focus of this research is on how the position of competitiveness of Indonesian rubber exports among ASEAN countries and the dominant factors causing the competitiveness of Indonesian rubber exports experienced a downward. Approach to measuring rubber export competitiveness uses the Lafay Index, and factors that affect the competitiveness using the Diamond model by using panel data analysis method. The results show that there has been a decline in the competitiveness of Indonesia's rubber exports to ASEAN countries, the greatest decline in competitiveness that occurred in Singapore, Malaysia, and Thailand. Factors that affect Indonesia's export competitiveness that is more dominant are a foreign direct investment, price levels, and interest rates. FDI should be directed at improving the quality of export products following the quality of ISNR and upgrading the quality of rubber export products from SIT 20, and directly more beneficial for the manufacture of goods for final consumers.

KEYWORDS

Export competitiveness, the Lafay index, diamond model.

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Similarity and Competition of Polish Agri-food Export with the Largest Agricultural Producers in the EU. Analysis of EU, US and China Market

Bartłomiej Bajan Joanna Łukasiewicz Luboš Smutka DOI: 10.7160/aol.2021.130103
No 1/2021, March
pp. 29 - 47

ABSTRACT

Poland is one of the largest agricultural producers within European Union (EU). Since joining EU in 2004, Poland has significantly increased its agri-food trade turnover and strengthened its net exporter standing in this regard. With the understanding that countries exporting similar goods to a specific market can be considered competitors, the examination covered similarities in Poland’s export of agri-food products compared to the two largest agricultural producers in EU, namely Germany and France, in three markets: EU-28, China and United States. The agri-food export was analyzed in terms of structure, value and quality, using ComExt data. The growth of the Polish agri-food trade following the accession to the European Union, allowed the country to become a competitor to the common market’s biggest agricultural producers. Poland’s competitiveness in the US market in relation to Germany is also rising. On the other hand, looking at the Chinese market, the value of the exported agri-food products is too low to consider Poland a major competitor to Germany or France. Poland’s competitiveness in the trade of agri-food products is relatively well covered in the literature, but the studies usually focus on the issue of volume and structure or comparative advantages. The export similarity is omitted, in particular with regard to Central and Eastern European countries (CEEC) and to quality similarities issues. The study also suggests a way to identify countries similar in terms of export structure that is based on entire population results. This study fills in a certain research gap that emerged in the context of CEEC, consisting in the analysis of Poland's export in the background of EU’s largest agricultural producers.

KEYWORDS

Agri-food sector, export, structure similarity, international competitiveness.

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A Strategic Analytics Using Convolutional Neural Networks for Weed Identification in Sugar Beet Fields

Brahim Jabir Noureddine Falih Asmaa Sarih Adil Tannouche DOI: 10.7160/aol.2021.130104
No 1/2021, March
pp. 49 - 57

ABSTRACT

Researchers in precision agriculture regularly use deep learning that will help growers and farmers control and monitor crops during the growing season; these tools help to extract meaningful information from large-scale aerial images received from the field using several techniques in order to create a strategic analytics for making a decision. The information result of the operation could be exploited for many reasons, such as sub-plot specific weed control. Our focus in this paper is on weed identification and control in sugar beet fields, particularly the creation and optimization of a Convolutional Neural Networks model and train it according to our data set to predict and identify the most popular weed strains in the region of Beni Mellal, Morocco. All that could help select herbicides that work on the identified weeds, we explore the way of transfer learning approach to design the networks, and the famous library Tensorflow for deep learning models, and Keras which is a high-level API built on Tensorflow.

KEYWORDS

Deep learning, CNN, precision agriculture, decision making, strategic analytics.

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NB-IoT Sensor Network for Obtaining the Input Data for Hydrological Simulation Model

Oskars Java Aleksandrs Sigajevs Juris Binde Michal Kepka DOI: 10.7160/aol.2021.130105
No 1/2021, March
pp. 59 - 69

ABSTRACT

The article describes the choice of appropriate network technology that provides sufficient coverage to allow the sensor network to be placed even in the remote and difficult to reach locations and the data to reach the cloud server. Further it describes the components of the sensor network, the operating principle, architecture and the processing of the data obtained to convert them into the input data used in the hydrological simulation model. The NB-IoT sensor network proposed by the authors would not only collect the data needed to operate hydrological simulation models, but, for example, could provide the data needed to forecast weather conditions, particularly if the architecture of this sensor network, because of its low cost, would be widely applied around the globe, joining a unified global sensor network.

KEYWORDS

Sensor network, internet of things, IoT, sensor data processing, NB-IoT.

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Barriers to and Benefits of the Use of Smart Farming Technologies for Small and Medium Winemakers, Specifically Sensors and Weather Stations: A Pilot Study

Lucie Kaňovská DOI: 10.7160/aol.2021.130106
No 1/2021, March
pp. 71 - 85

ABSTRACT

Digitization is becoming part of agriculture. Winemakers can use monitoring technologies to map land or control the quality of grapes, and telematics, e.g., in tractors, or use entire autonomous machines. The aim of this paper is to find out the barriers to and benefits of the use of smart farming technologies by small and medium winemakers, specifically sensors and weather stations, which allow the collection of site-specific data for subsequent application in viticulture. Therefore, the pilot study analyses how winemakers in traditional industry are able to employ smart farming technologies (SFT) to gain some benefits and also describe possible barriers. The primary method of data collection was through 27 semi-structured interviews with relevant wine industry actors, accessing documents created by SFT providers and an academic literature review. Three groups of actors were researched: 1) 22 winemakers including the Ekovin Association, 2) three SFT providers and, 3) one supplier of hardware for soil and temperature sensors. According to the information of winemakers, it is clear that SFT are used by some of them and they are clearly aware of their benefits, which is also confirmed by SFT providers. The findings revealed that the main STF benefits are adjustment of the product portfolio, savings, consulting and organization of activities. However, respondents also mentioned barriers to SFT implementation, such as low need for information, another source of information, conservative approaches, ignorance of SFT, financial demands, low state support and age of winemakers. The novelty of this paper is in providing an analysis of the issue of SFT, specifically sensors and weather stations, for winemakers from three different perspectives, that of winemakers, suppliers of SFT and HW manufacturer for SFT.

KEYWORDS

Smart farming technologies, precision agriculture, precision viticulture, winemakers, Czech Republic.

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Predicting Trends in Cereal Production in the Czech Republic by Means of Neural Networks

Vít Malinovský DOI: 10.7160/aol.2021.130107
No 1/2021, March
pp. 87 - 103

ABSTRACT

This paper deals with problems of processing agricultural production data into the form of time series and analysing consequent results by means of two completely different methods. The first method for calculating cereals production figures uses the MS-Excel spreadsheet using conventional mathematical and statistical functions while the second one uses the ELKI software providing users with development environment including algorithms of neural networks. The obtained results are similar to a certain extent which shows new possibilities of progressive use of neural networks in future and enables modern approach to analysing time series not only in agricultural sector.

KEYWORDS

Comparative analysis, cereals production, ELKI software, Excel spreadsheet, neural networks, predicting, statistics, time series, trends.

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Factors Affecting Fast Food Restaurant Image in Peshawar: Moderating Role of Customer Personality Traits

Henrietta Nagy Safdar Sana Wisal Ahmad Ragif Huseynov Muhammad Farooq Jan Peter Bielik DOI: 10.7160/aol.2021.130108
No 1/2021, March
pp. 105 - 119

ABSTRACT

Relating unique identity of product with consumer buying behavior is not so straight forward. Many factors need to be studied in order to investigate this relationship. This study was conducted to see the direct effects of various marketing elements including brand name, service quality, food price and the ambient factors on customer perception about the restaurant image as well as the moderating influence of consumers’ personality traits on such relationship. Data was collected from two hundred and forty customers in six well known restaurants of Peshawar in order to examine the hypothesized relationships. The findings of the study support the hypothesized relationship between the study variables and hence all the hypotheses of the study are supported. The study findings particularly the moderating role of personality traits of restaurant customers’ in building customers’ restaurant perception is of immense importance for academicians in general and restaurant management in particular. The study also presents valuable future research directions which will further this inquiry in future.

KEYWORDS

Restaurant image, service quality, ambiance, personality traits.

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Sentiment Analysis in Agriculture

Jiří Novák Petr Benda Edita Šilerová Jiří Vaněk Eva Kánská DOI: 10.7160/aol.2021.130109
No 1/2021, March
pp. 121 - 130

ABSTRACT

Sentiment analysis is currently the most actively researched topic in the field of natural language processing, however, despite it being such a powerful tool, it is not very widely used in the agrarian sector. This research focuses on the discovery and analysis of scientific literature related to Sentiment analysis in agriculture, to provide an overview of how and where Sentiment analysis is used in the agrarian sector and which methods are most commonly used. This article also discusses which applications of Sentiment analysis yield the most benefits and suggests a direction for future research.

KEYWORDS

Sentiment analysis, agriculture, opinion mining, natural language processing, text mining.

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Economic Consequences of Invasive Species in ornamental sector in Mediterranean Basin: An Application to Citrus Canker

Giuseppe Timpanaro Arturo Urso Vera Teresa Foti Alessandro Scuderi DOI: 10.7160/aol.2021.130110
No 1/2021, March
pp. 131 - 149

ABSTRACT

Citrus Bacterial Cancer (CBC) is a severe phytopathy capable of compromising the economy, environment, and society in specific areas. To date, it is not present in the Mediterranean Basin. In essence, it could be a signal that European Phytosanitary Services have been able to control its spread, blocking import and marketing of fruits from risk areas or lacking the necessary phytosanitary requirements. However, in 2014 the EFSA launched the alarm on possible new forms of transmission of Xcc or Xanthomonas citri, the causative agent of the CBC, represented by the marketing of ornamental Rutaceae and the flow of tourism, to and from risk areas. In this context, the research carries aim to assess direct and indirect damages that an invasion of the CBC could cause to the sector: its impacts at the micro-economic level fall on the production system and the consumer, while at the macro level on the entire community. The traceability of plant material during commercial operations is proposed as a possible solution, even if it becomes an accessory burden for businesses and consumers. In this sense, this research intends to offer some useful information to public and private, interested parties and to plan intervention policies.

KEYWORDS

Xanthomonas citri, ornamental rutaceae, economic impact, damage assessment with income method, nurseries industry.

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