S. Alkire, Ruth S. Meinzen-Dick, Amber Peterman
et al.
The Women’s Empowerment in Agriculture Index (WEAI) measures the empowerment, agency, and inclusion of women in the agricultural sector and comprises two subindexes. The first assesses empowerment of women in five domains, including (1) decisions about agricultural production, (2) access to and decisionmaking power about productive resources, (3) control of use of income, (4) leadership in the community, and (5) time allocation. The second subindex measures the percentage of women whose achievements are at least as high as men in their households and, for women lacking parity, the relative empowerment gap with respect to the male in their household. This article documents the development of the WEAI and presents pilot findings from Bangladesh, Guatemala, and Uganda.
Agriculture is one of the economic sectors that affect climate change contributing to greenhouse gas emissions directly and indirectly. There is a trend of agricultural greenhouse gas emissions reduction, but any practice in this direction should not affect negatively farm productivity and economics because this would limit its implementation, due to the high global food and feed demand and the competitive environment in this sector. Precision agriculture practices using high-tech equipment has the ability to reduce agricultural inputs by site-specific applications, as it better target inputs to spatial and temporal needs of the fields, which can result in lower greenhouse gas emissions. Precision agriculture can also have a positive impact on farm productivity and economics, as it provides higher or equal yields with lower production cost than conventional practices. In this work, precision agriculture technologies that have the potential to mitigate greenhouse gas emissions are presented providing a short description of the technology and the impacts that have been reported in literature on greenhouse gases reduction and the associated impacts on farm productivity and economics. The technologies presented span all agricultural practices, including variable rate sowing/planting, fertilizing, spraying, weeding and irrigation.
Greenhouse cultivation has evolved from simple covered rows of open-fields crops to highly sophisticated controlled environment agriculture (CEA) facilities that projected the image of plant factories for urban agriculture. The advances and improvements in CEA have promoted the scientific solutions for the efficient production of plants in populated cities and multi-story buildings. Successful deployment of CEA for urban agriculture requires many components and subsystems, as well as the understanding of the external influencing factors that should be systematically considered and integrated. This review is an attempt to highlight some of the most recent advances in greenhouse technology and CEA in order to raise the awareness for technology transfer and adaptation, which is necessary for a successful transition to urban agriculture. This study reviewed several aspects of a high-tech CEA system including improvements in the frame and covering materials, environment perception and data sharing, and advanced microclimate control and energy optimization models. This research highlighted urban agriculture and its derivatives, including vertical farming, rooftop greenhouses and plant factories which are the extensions of CEA and have emerged as a response to the growing population, environmental degradation, and urbanization that are threatening food security. Finally, several opportunities and challenges have been identified in implementing the integrated CEA and vertical farming for urban agriculture. Keywords: smart agriculture, greenhouse modelling, urban agriculture, vertical farming, automation, internet of things (IoT), wireless sensor network, plant factories DOI: 10.25165/j.ijabe.20181101.3210 Citation: Shamshiri R R, Kalantari F, Ting K C, Thorp K R, Hameed I A, Weltzien C, et al. Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. Int J Agric & Biol Eng, 2018; 11(1): 1–22.
KabitaKumariShah, HariPrasadPandey, ArjunSubedi
et al.
Diversified crop rotation (DCR) improves the efficiency of farming systems all over the world. It has the potentiality to improve soil condition and boost system productivity. Improved soil attributes such as increased soil water uptake and storage, and a greater number of beneficial soil organisms, may improve yield tolerance to drought and other hard growing conditions in a variety of crop rotations. Crop rotations with a variety of crops benefit the farmers,reduce production risk and uncertainty, and enhance soil and ecological sustainability. Farmers may be able to diversify their sources of income by adopting diversified crop rotations. Furthermore, because of the distinct structure, function, and relationship of plant community with soil in DCR, it contributes to the long-term development of soil health by decreasing insect, weed, and disease incidence and increasing the physical and chemical structure of the soil. DCR is becoming more popular approach for maintaining sustainable crop production. This review provides the evidence of the significance of DCR, challenges to adapt it, and possible way out to overcome the challenges.
Abstract Blockchain quickly became an important technology in many applications of precision agriculture discipline. The need to develop smart P2P systems capable of verifying, securing, monitoring, and analyzing agricultural data is leading to thinking about building blockchain-based IoT systems in precision agriculture. Blockchain plays the role of pivotal in replacing the classical methods of storing, sorting and sharing agricultural data into a more reliable, immutable, transparent and decentralized manner. In precision farming, the combination of the Internet of Things and the blockchain will move us from only smart farms only to the internet of smart farms and add more control in supply-chains networks. The result of this combination will lead to more autonomy and intelligence in managing precision agriculture in more efficient and optimized ways. This paper exhibits a comprehensive survey on the importance of integrating both blockchain and IoT in developing smart applications in precision agriculture. The paper also proposed novel blockchain models that can be used as important solutions for major challenges in IoT-based precision agricultural systems. In addition, the study reviewed and clearly discussed the main functions and strengths of the common blockchain platforms used in managing various sub-sectors in precision agriculture such as crops, livestock grazing, and food supply chain. Finally, the paper discussed some of the security and privacy challenges, and blockchain-open issues that obstacles developing blockchain-IoT systems in precision agriculture.
Conventional agriculture often relies on bulky doses of fertilizers and pesticides that have adversely affected the living beings as well as the ecosystems. As a basic tenet of sustainable agriculture, minimum agrochemicals should be used so that the environment can be protected and various species can be conserved. Further, sustainable agriculture should be a low input system, where the production costs are lower and net returns are higher. The application of nanotechnology in agriculture can significantly enhance the efficiency of agricultural inputs and thus it offers a significant way to maintain sustainable development of agroecosystems via nanoparticles. In this regard, nano-plant growth promoters, nanopesticides, nanofertilizers, nano-herbicides, agrochemical encapsulated nanocarrier systems etc. have been developed for the potential applications in agriculture. These can have great benefits for agriculture, including higher production of crops, inhibition of plant pathogens, removal of unwanted weeds and insects with lesser cost, energy and waste production. However, there are several concerns related to the use of nanoparticles in agriculture. These include the approaches for synthesis, their mechanisms of penetration to applied surfaces and the risks involved. Though, advent of new technologies has significantly improved the synthesis and application of nanomaterials in agriculture, there are many uncertainties regarding nano-synthesis, their way of utilization, uptake and internalization inside the crop cells. Therefore, an elaborate investigation is required for deciphering the engineered nanomaterials, assessing their mechanistic application and agroecological toxicity. Hence, this review is aimed to critically highlight the NPs material application and points towards the vital gaps in the use of nanotechnology for sustainable agriculture.
Isabel Cisternas, Ignacio Velásquez, Angélica Caro
et al.
Abstract Agriculture production highly depends on water and soil factors which increasingly need to be utilized efficiently. Precision agriculture, through the set of information technologies that it uses, allows to effectively manage these resources. This work aims to gather the existing knowledge on technologies used in precision agriculture and ways to discern the most appropriate one for different contexts in agricultural processes. A systematic literature review is performed to identify precision agriculture implementations and to answer questions such as the type of technologies used, criteria for their comparison and selection, and the existence of frameworks that help to decide what technologies to implement. A total of 3,949 publications were reviewed, of which 259 addressed the posed research questions. The findings are that remote sensors are the most used technology, the required knowledge is an important criterion for deciding to implement precision agriculture, and no framework was found that guides its implementation.
The ability to manage fields not as a single unit but by dividing them into separate areas distinguishes precision farming from traditional agriculture. Technologies and techniques used to improve the crop farming is the main domain we are working under precision agriculture.Optical sensors that use the reflectivity of light placed on growing plants to monitor and record the data about soil and crops in real time are available. Electrochemical sensors,are those that monitor plant, soil, and external factors that have a direct impact on plant growth.. A prototype of an intelligent Agriculture Robot tailored exclusively for seed sowing tasks is exhibited. It is a four-wheeled vehicle driven by an LPC2148 microcontroller. Its operation is based on precision agriculture, which allows for effective seed planting at appropriate depths and distances within crops and rows that are specific to each crop species.This work presents a system for diagnosing cotton leaf diseases in India using image processing. The system uses SVM to classify diseases based on color and texture of images obtained from cotton fields using a digital camera. The images undergo pre-processing, including segmentation and feature extraction. The goal is to reduce loss of yield and productivity by early disease identification.
The multi-level perspective (MLP) is a prominent transition framework. The MLP posits that transitions come about through interaction processes within and among three analytical levels: niches, socio-technical regimes and a socio-technical landscape. This systematic review provides an overview on the use of the MLP in research on agro-food sustainability transitions. In particular, it analyses the understanding, conceptualisation and operationalisation of niches, regimes and landscapes. Niches considered in the selected papers include agro-ecology, organic agriculture, permaculture, conservation agriculture, integrated farming, and alternative food networks. Regime refers to industrial, conventional agriculture. The researched regime is often not clearly described and its operationalisation is a matter of deliberation. Landscape level is generally overlooked; when it is considered it refers to international trends and developments. Many scholars highlight the inadequacy of transition pathways in the MLP for the agro-food sector. Moreover, transition impacts are rarely addressed and the research field generally overlooks the analysis of the sustainability of niches and, consequently, of transitions. Research on transitions in the agro-food sector borrows from the MLP its generalizability and poor empirical operationalisation of niche, regime and landscape concepts. Therefore, integrative conceptualisation and operationalisation of the MLP elements is required to accommodate the complexity of sustainability transition processes and the peculiarities of the agro-food system.
The rapid population growth has driven the demand for more food, fiber, energy, and water, which is associated to an increase in the need to use natural resources in a more sustainable way. The use of precision agriculture machinery and equipment since the 1990s has provided important productive gains and maximized the use of agricultural inputs. The growing connectivity in the rural environment, in addition to its greater integration with data from sensor systems, remote sensors, equipment, and smartphones have paved the way for new concepts from the so-called Agriculture 4.0 or Digital Agriculture. This article presents the results of a survey carried out with 504 Brazilian farmers about the digital technologies in use, as well as current and future applications, perceived benefits, and challenges. The questionnaire was prepared, organized, and made available to the public through the online platform LimeSurvey and was available from 17 April to 2 June 2020. The primary data obtained for each question previously defined were consolidated and analyzed statistically. The results indicate that 84% of the interviewed farmers use at least one digital technology in their production system that differs according to technological complexity level. The main perceived benefit refers to the perception of increased productivity and the main challenges are the acquisition costs of machines, equipment, software, and connectivity. It is also noteworthy that 95% of farmers would like to learn more about new technologies to strengthen the agricultural development in their properties.
Omar H. Khater, Abdul Jabbar Siddiqui, M. Shamim Hossain
et al.
Sustainable agriculture plays a crucial role in ensuring world food security for consumers. A critical challenge faced by sustainable precision agriculture is weed growth, as weeds compete for essential resources with crops, such as water, soil nutrients, and sunlight, which notably affect crop yields. The adoption of automated computer vision technologies and ground agricultural consumer electronic vehicles in precision agriculture offers sustainable, low-carbon solutions. However, prior works suffer from issues such as low accuracy and precision, as well as high computational expense. This work proposes EcoWeedNet, a novel model that enhances weed detection performance without introducing significant computational complexity, aligning with the goals of low-carbon agricultural practices. The effectiveness of the proposed model is demonstrated through comprehensive experiments on the CottonWeedDet12 benchmark dataset, which reflects real-world scenarios. EcoWeedNet achieves performance comparable to that of large models (mAP@0.5 = 95.2%), yet with significantly fewer parameters (approximately 4.21% of the parameters of YOLOv4), lower computational complexity and better computational efficiency 6.59% of the GFLOPs of YOLOv4). These key findings indicate EcoWeedNet's deployability on low-power consumer hardware, lower energy consumption, and hence reduced carbon footprint, thereby emphasizing the application prospects of EcoWeedNet in next-generation sustainable agriculture. These findings provide the way forward for increased application of environmentally-friendly agricultural consumer technologies.