Design and Development of an Intuitive Android Application for Smart Farming

In order to increase agricultural production, profitability and environmental sustainability, precision agriculture integrates geolocation technologies, agronomic knowledge, information technologies and variable rate application technologies to adapt agricultural work intra-plot differences. The adoption of precision agriculture in Algeria has the potential to increase crop yield and profitability, reduce environmental impacts, and modernize agricultural production systems. In this study the attitude of 322 Algerian agricultural engineers towards the challenges that can hinder the adoption of precision agriculture in Algeria was measured as well as their perception on the importance of the state subsidy to overcome these challenges. The results of this study revealed that the 3 main challenges that hinder the adoption of precision agriculture in Algeria are linked to the high cost of the technologies used, the limited number of skilled labor and the unavailability of several technologies in the Algerian market. In addition, according to Algerian agricultural engineers, the state subsidy will help overcome these challenges and promote the adoption of precision agriculture in Algeria.

In recent years, precision farming has been receiving more attention from researchers. Precision farming, which provides a holistic system approach, helps farmers to manage the spatial and temporal crop and soil variability within a field in order to increase profitability, optimize yield and quality, and reduce costs. There has been considerable research in farmers’ adoption of precision agriculture technologies. However, most recent studies have considered only a few aspects, whereas in this study a wide range of farm characteristics and farmer demographics are tested to gain insight into the relevant aspects of adoption of precision farming in German crop farming. The results of a logistic regression analysis show that predictors with positive influence on the adoption of precision farming are agricultural contractor services such as an additional farming business, having under 5 years’ experience in crop farming, having between 16 and 20 years’ experience in crop farming, and having more than 500 ha of arable land. However, having a farm of less than 100 ha and producing barley are factors that exert a negative influence on the adoption of precision farming. The results of this study provide manifold starting points for the further proliferation of precision agriculture technologies and future research directions.

Precision Agriculture in India- Challenges and Opportunities

‘Precision Farming’ or ‘Precision Agriculture’ aims at increasing productivity, decreasing production costs and minimizing the environmental impact of farming. In this context, the present study has been undertaken to understand the impact of precision farming on resource-poor regions and underprivileged farmers. Specifically, the study has looked into productivity, income, employment, and adoption behaviour of technology in agriculture. The study, conducted in the Dharmapuri district, has collected data on precision and non-precision farmings through the interview schedule during the year 2007. Sources of the productivity difference between the precision and conventional farmings have been identified by decomposing the productivity change. Financial impact of adoption has been studied through a two-stage econometric model. The first stage of the model consists of an adoption decision model that describes the factors which influence the likelihood of adopting precision farming. Results of first stage have provided input for the second stage of the model, which has been used to estimate the impact of precision farming on farm financial performance. The study has revealed that adoption of precision farming has led to 80 per cent increase in yield in tomato and 34 per cent in brinjal production. Increase in gross margin has been found as 165 and 67 per cent, respectively in tomato and brinjal farming. The contribution of technology for higher yield in precision farming has been 33.71 per cent and 20.48 per cent, respectively in tomato and brinjal production. The elasticity of 0.39 for the adoption in tomato and 0.28 in brinjal has indicated that as the probability of adoption increases by 10 per cent, net return increases by 39 per cent and 28 per cent in tomato and brinjal cultivation. Lack of finance and credit facilities have been identified as the major constrains in non-adoption of precision farming. The study has suggested that providing of subsidies for water-soluble fertilizers and pump-sets will increase adoption of precision farming.

Precision farming refers to the latest trends in agriculture that use technology to improve quality, quantity, and productivity, thereby ensuring profitability, sustainability, betterment, and preservation of the environment. The paper discusses the development and needs for precision agriculture in India with its existing problems and opportunities. The challenges in the future cannot be resolved with ancient methods. In order to make agriculture efficient and sustainable, investment in new technologies accompanied by research and development is required. Agronomics is the highest contributor to national income. More than 70% of the total workforce is dependent on it. The agriculture industry needs top priority because the government and the nation both would fail to succeed in this sector. The paper identifies various challenges associated with the adoption of precision farming in India and the technologies that could be used for better results and the betterment of both farmers and the Agri industry of India.

The report presents the results of a survey conducted on 700 wheat farmers in France and Hungary. The survey aimed to single out the most critical elements at the base of wheat productivity, collecting information for the growing seasons 2010/2011, 2011/2012 and 2012/2013. Two types of data are obtained: farmers’ opinions on the determinants of wheat productivity; quantitative data on wheat output, production factors, marketing strategies, damages, and field and risk management practices. Through descriptive statistics, the report revealed important and significant differences between the countries. According to French farmers' opinion, the most important wheat yield determinants at national level are seasonal weather and soil quality; while Hungarians addressed climate change and seasonal weather. At the farm level, the high prices of inputs and the low wheat market prices are considered the most constraining factors in both countries. Wheat yields are positively correlated to higher agro-chemicals use in Hungary and to additional days of labour in France. The adoption of precision farming provides 7-12% higher yields in both countries, while yield gains from conservation agriculture and IPM are found in partial adopters. In both countries, the most frequently adopted innovation to increase wheat yields and grains' quality are new wheat varieties, however farmers’ willingness to adopt genetically modified wheat varieties is opposite: positive in France and negative in Hungary. Finally, both farmers perceive market risks as more detrimental than natural disasters. While crop insurance is the most adopted tool to deal with natural risks in both countries, French farmers adopt diversification strategies more frequently than Hungarians to deal with market risks.

Mobile internet is considered one of the most important developments in information and communication technology due to its considerable effect on both the economy and our daily lives. Furthermore, mobile internet is an essential tool for overcoming the rural–urban digital divide. With respect to agriculture, mobile internet can play a central role in information gathering as well as the implementation of precision and smart farming technologies. Yet, no study has identified the determinants of mobile internet adoption in agriculture. Using a bivariate probit model with a sample selection and a representative data set from 815 German farmers, this study showed that, among other characteristics, the age of the farmer, farm size and location, as well as familiarity with internet risks is associated with mobile internet adoption in agriculture. These results may be of interest to policy makers, who deal with internet infrastructure, and providers of farm equipment that rely on mobile internet connection. [EconLit citations: Q16].

Precision Agriculture (PA) is an all-encompassing term given to the use of a suite of technologies that promote improved management of agricultural production through recognition that the potential productivity of agricultural land can vary considerably, even over very short distances (a few m). It can be regarded as a means of increasing the chance that the right crop management strategies are implemented in the right place at the right time. Numerous examples exist of the successful application of PA to various cropping systems around the world, in many cases supported by a burgeoning PA literature. However, the rate of adoption by growers of many crops remains low and, in some industries, is negligible. One such example is the Australian sugar industry, in spite of its relatively high rate of adoption of controlled traffic and the ready access that growers have to supporting infrastructure such as local GPS base stations. However, the Australian sugar industry is now seeking an informed basis from which to make decisions as to appropriate investment in PA, whether these be in terms of pragmatic application by growers, the level of involvement (if any) by millers, or with respect to research to facilitate such adoption. A part of acquiring this informed view of PA is to look at its application in other cropping systems. This review therefore examines PA research and application in a range of cropping systems from around the world and considers the key drivers of variability in these production systems. Constraints to the adoption of PA and its likely economic benefits are also considered in light of experiences from around the world. It is concluded that sugarcane production is ideally suited to the adoption of PA. Like other broadacre systems, such as cereal production, the opportunity exists to target the management of inputs to production. However, the vertically integrated nature of the sugar industry and existence of a potentially significant crop quality imperative also present opportunities for targeted strategies such as selective harvesting, as used in the wine industry. Thus, to get the best result from adoption of PA, the sugar industry will need to consider it as a tool for optimising management of the production of sugar, as opposed to solely an avenue for improving the agronomic management of sugarcane. Several recommendations are made as to how this adoption might be supported.

Precision agriculture technologies (PATs) are reshaping modern crop production by promoting efficient and sustainable farming practices. Core components of precision agriculture include remote sensing, GPS-enabled machinery, variable rate technology (VRT), and Internet of Things (IoT)-based systems. Remote sensing tools and unmanned aerial vehicles provide high-resolution data that support accurate assessment of crop health, soil variability, and pest incidence. GPS-guided equipment improves the precision of field operations such as sowing, fertilizer application, and harvesting, leading to reduced input losses and higher operational efficiency. VRT allows site-specific application of water, fertilizers, and pesticides according to crop demand and real-time field conditions, thereby minimizing excessive input use, nutrient runoff, and greenhouse gas emissions. The adoption of precision agriculture significantly enhances environmental sustainability by conserving water, lowering chemical inputs, and improving soil health. By reducing the ecological footprint of farming while increasing yields and profitability, PATs offer a viable solution for meeting the growing global food demand and ensuring long-term agricultural and environmental sustainability. Precision agriculture integrates advanced technologies to enhance farm productivity, efficiency, and sustainability. Precision farming, defined by the strategic application of data analytics and advanced technologies, has emerged as a transformative approach for achieving sustainable agriculture. precision agriculture provides an effective pathway for building sustainable and resilient agricultural systems by improving resource-use efficiency, while simultaneously supporting food security and environmental sustainability.

An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques

Adoption of Precision Agriculture (PA) technologies has apparent benefits for agricultural production management, cost savings, and environmental sustainability. However, these technologies are also extremely complicated and influenced by various social and economic forces, which impact their adoption rate, particularly in developing nations. Demographic and agricultural characteristics also play an important role in determining willingness to adopt PA. This study is a survey aimed at establishing the willingness indices of farmers and other relevant personnel to embrace precision farming technologies in Gombe and Bauchi states of Nigeria. The survey included individuals of varied ages; but an average age of 28.5 years for Gombe and 36.5 years for Bauchi, educational levels, and employment statuses, as well as agricultural and operational features. The willingness to adopt PA is high in both states, with 92% in Gombe and 96% in Bauchi. The findings suggest that, while high costs and a lack of technical know-how had a negative impact on readiness to adopt PA in both states, the level of complexity was rated higher by the older generation in Bauchi state, which had a comparatively high mean farmer age. The size of the farm and the number of employees had no direct influence on the adoption of PA technology. Other criteria, such as age and number of years of operation, indicate overlap between the various stages of internet and digital technology adoption, mechanization, and PA. The high willingness rating indicates that farmers are willing to adopt PA technologies if made accessible. It is therefore advised that legislative tools, training programs, and necessary access to financing facilities be employed to make these technologies available and cheap for farmers.

Agriculture is undergoing a profound change related to Agriculture 4.0 development and Precision Agriculture adoption, which is occurring at a slower pace than expected despite the abundant literature on the factors explaining this adoption. This work explores the factors related to agricultural Operations Management, farmer behavior, and the farmer mental model, topics little explored in the literature, by applying the Theory of Planned Behavior. Considering the exploratory nature of this work, an exploratory multi-method is applied, consisting of expert interviews, case studies, and modeling. This study’s contributions are a list of factors that can affect this adoption, which complements previous studies, theoretical propositions on the relationships between these factors and this adoption, and a model of irrigation Operations Management built based on these factors and these propositions. This model provides a theoretical framework to study the identified factors, the relationships between them, the theoretical propositions, and the adoption of Precision Agriculture. Furthermore, the results of case studies allow us to explore the relationships between adoption, educational level, and training. The identified factors and the model contribute to broadening the understanding of Precision Agriculture adoption, adding Operations Management and the farmer mental model to previous studies. A future research agenda is formulated to direct future studies.

Chapter 3 - Crop nitrogen use efficiency for sustainable food security and climate change mitigation

Chapter 11 - Where do we stand with digitalization? An assessment of digital transformation in Hungarian agriculture

Abstract. The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy) on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI), and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ13C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing. The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW) during the growing season differed considerably between the vineyards and increased significantly along the three positions on slope in both vineyards. The water accumulation along slope occurred in every year, even during the very dry 2006. The installation of indicators of reduction in soils (IRIS) tubes allowed confirmation of the occurrence of reductive processes in the most shallow soil. Both Sangiovese grape yield and quality of wine were influenced by the interaction between TSW content and salinity, sometimes contrary to expectations. Therefore, the studied hydropedological models were not relevant to predict grape yield and wine quality in all the hydrological functional units. The diffusion of hydropedological models in precision viticulture could be boosted considering salinity along with topography and soil hydrological characteristics.