Quantity Of Agricultural Products Research Articles

Safety assessment of agricultural products and the pesticide regulation trend in China

The sustainable development of Chinese agriculture needs to coordinate the quality and quantity of agricultural products. To verify whether government regulation can promote agricultural development by controlling pesticides, the indices of government regulation, quantity and quality of agricultural products, and pesticide use per area of cropland were calculated, and a comprehensive evaluation index and the coupling degree and coordination degree of agricultural products were analyzed by coupling function. The results showed that the coupling and coordination degree of the quality and quantity of agricultural products and the comprehensive index are improving. The regulation of pesticide use per area of cropland is a key mechanism in promoting the coordinated development of agricultural product safety. The regulation trend of agricultural development in China is to reduce pesticide usage appropriately and expand the production-possibility frontier of agricultural products.Graphical abstract

Microbial forensics: are we going on right path for management of crops biosecurity in Pakistan?

In any country biological terrorism outbreaks on crops could reduce the quality and quantity of agricultural products, which in turn decreases the consumer’s confidence, nutrition loss, resulting in worse impacts on the nation’s economy, international souks and is subsequently harmful for the environment. Awareness for a crop bioterror incident begins with the start of the threat symptoms, which must lead to the progress of a plan to thwart. However, most of Pakistani scientists and crop producers have not focused on the option of deliberative plant pathogen introduction but instead they use their expertise for the prevention of natural introductions and the improvement of cost-effective strategies for disease management. It is also an interesting fact that under the mask of genetically modified feeds, high yield varieties and hybrids; we are also importing bio terrorism. Are we going on the right path? So, it is time that we should review the global microbial knowledge and should apply it according to our needs. In ongoing topics of present article, we will review the microbial forensics status globally in comparison with Pakistan. We will also suggest how to fill these gaps. Keywords: Biological terrorism; Microbial forensics; Pathogen; Plants; Crops; Biosecurity

Sosialisasi Konsep Pertanian Berkelanjutan Di Kampung Napua Distrik Napua Kabupaten Jayawijaya

Traditional agriculture implemented in Napua Village, Napua, Jayawijaya indirectly has a negative impact on the environment and the sustainability of food production. Socialization and assistance regarding the concept of sustainable agriculture is important to increase farmers' awareness in implementing more environmentally friendly and sustainable agricultural practices. This service activity aims to provide farmers with an understanding of the concept of sustainable agriculture. The implementation method is socialization in the form of delivering material about sustainable agriculture and assistance to farmer groups in practicing the concept of sustainable agriculture. The results of this socialization activity are the emergence of farmer awareness about the factors causing the decline in the quality and quantity of agricultural products in Napua Village and increased knowledge about the concept of sustainable agriculture as a solution to the problems.

Application of M‐RCNN for prompt segmentation between infected tomato leaves and healthy tomato leaves

AbstractPlant diseases have become a problem, as both the quality and quantity of agricultural products can be significantly reduced. The goal of the research is to detect the infection in the plant leaf so that it can be cured before spreading of disease to other plants. The aim of the research is to find out the severity of the leaf disease so that it can be cured based on the level of severity. Also, crop loss can be predicted by using the severity loss. For object localization, we utilize 10,640 tomato leaf images of various classes from the PlantVillage standard repository. As a baseline for future work, we propose a model based on the Mask R‐CNN architecture with ResNet‐50 as the backbone that effectively performs instance segmentation for these six diseases. The dataset is annotated by using the VGG annotator tool and this annotated dataset would have been used to train the ‘Mask R‐CNN model’ and the ResNet50 backbone, fine‐tuning the network's weights to accurately detect and segment diseased regions on leaves. The outcomes of the suggested model achieved an average accuracy of 91.3% by using multiple performance indicators like accuracy, precision and F1 score and Recall. Based on the outcome, the severity of the disease is being identified on a scale of 0, 1, 2 and 3.

Adaptation Strategies Through Mining Compensation in Mabayi Commune, Burundi

One of main effects of mining on rural agriculture is the loss of farmland by households living near mining sites. In return, these households should receive compensation. This compensation, if well invested, may lead to improved livelihoods for these farming households. If not, these households may find their livelihoods deteriorating if the compensation is not properly managed. This paper aims to analyze household compensation investment strategies in Mabayi commune (Burundi) and their effects on the livelihoods of households affected by mining activities. A survey of 140 households, interviews with key informants, and observations were conducted in July and August 2022 on Gahoma and Ruhororo hills where foreign company ‘‘Tanganyika Mining Burundi (TMB)’’ and local cooperative ‘‘Dukorere Hamwe Dusoze Ikivi (DHDI)’’ were carrying out their activities respectively since December 2018, in Mabayi commune. Results showed that 17 out of 20 households (85%) and 13 out of 17 households (76.5%) had invested their compensation well, in Gahoma and Ruhororo hills respectively. They had improved or maintained their overall quantity of agricultural production, and improved their livelihoods in general. On other hand, 3 households (15%) and 4 households (23.5%) had invested their compensation inappropriately, in Gahoma and Ruhororo respectively. They had suffered reduction in their overall quantity of agricultural production, and experienced deterioration of their livelihoods in general. Fair and up-front compensation for households, assistance in how to invest compensation, capacity-building in agriculture and alternative activities, should maximize opportunities for improved livelihoods. The mining company and cooperative must also comply with environmental regulations.

Assessment of the Economic Consequences of Riverbank Erosion: The Case of the South Morava River, Serbia

Landscape transformation, degradation and destruction are caused by fluvial processes as the predominant erosive processes in Serbia. The loss of arable land due to riverbank erosion is permanent, and the economic consequences are, therefore, especially pronounced. The primary aim of this study was to quantify the intensity of riverbank erosion in the lower part of the South Morava River (Serbia) during period 1924–2020, evaluate its economic consequences, and conduct a cost benefit analysis of revetment investments. The economic effects of riverbank erosion were analyzed by means of land loss and reduction in the quantity of agricultural production. An interdisciplinary research approach was applied using specific methodological procedures to calculate the riverbank erosion and soil (land) loss intensity (geographic information system-GIS), the economic consequences of riverbank erosion (ECRE), and the results of an investment decision-making model. The results showed that 202.6[Formula: see text]ha of arable land was lost during the observed period, the value of arable land loss was almost 622,000[Formula: see text]USD, and the loss in agricultural production was 7.5 million USD (discount rate 3.7%). The model is seen as the main research output and can be used for the assessment of long-term capital-intensive infrastructure projects in developing countries. The analysis identified the river segments that are economically viable for investments in riverbank revetments to preserve the largest area of fertile agricultural land. The results are especially valuable for river channel management, environmental planners and policy-makers, who deal with decisions regarding planning and the protection of bank erosion in areas of particular interest.

IMPLEMENTASI ZAKAT PERTANIAN PADI DI DESA HALABAN JATI KABUPATEN LANGKAT

Zakat is one of the pillars of religion. Zakat is divided into zakat nafs (fitrah) and zakat maal (treasure). Agricultural products are goods for which zakat must be paid, which is usually called agricultural zakat. The majority of the people of Halaban Jati Village are Muslim farmers. As devout Muslims, farmers in Halaban Jati Village have the obligation to pay zakat on their agricultural products. This research aims to determine the implementation of rice farming zakat in Halaban Jati Village. The research method used is a qualitative method with descriptive analysis of data collection carried out by researchers, both document data and field data. The results of the research show that the collection and distribution of agricultural zakat in Halaban Jati Village is in accordance with Islamic law, but there are still farmers who have insufficient knowledge regarding agricultural zakat, they only pay agricultural zakat according to the customs carried out by farmers in Halaban Jati Village, not based on clarity on the quantity of agricultural products, so that the percentage of zakat maal can be known clearly. However, the awareness of farmers in Halaban Jati Village to pay agricultural zakat is an extraordinary awareness of their obligation to pay zakat.

Effects of Complex Fertilizers on the Properties of Grey Forest Heavy Loamy Soil.

The study's main aim was to evaluate the effects of complex mineral fertilizers on the complex properties of heavy loam soils in the grey forests of Russia in terms of applying individual soil nutrition components from experiments with fodder beets. This study employed a rigorous and systematic approach to accomplish the defined goal. Specifically, the research was conducted within a seven-field crop rotation system, with fodder beets serving as the primary experimental crop. In addition, a model experiment resembling a vegetation trial was undertaken, incorporating seven distinct schemes involving various types of fertilizers. This design facilitated the evaluation of the effectiveness of each fertilizer type. The study results demonstrate that complex fertilizers impact the soil's chemical and biophysical parameters. Soil acidity decreases through the use of complex, high-nitrogen fertilizers. Major chemical nutrients (nitrogen, phosphorus, and potassium) in plant biomass and soil also have a high degree of transition. It is explained by the effects of combining elements on the destruction intensity of the crystalline lattice in the basic structures of potassium, phosphorus, and nitrogen. There is also evidence that complex fertilizers can improve humus quality and replenish its reserves. All the aforementioned impacts of complex fertilizers on the crop contribute to the high productivity and yield of forage beet. The results of the study may help optimize the fertilization process, improve the quality and quantity of agricultural products, as well as increase soil fertility, and reduce the negative impact of agrochemicals on the environment.

Achieving the Rewards of Smart Agriculture

From connected sensors in soils, on animals or crops, and on drones, to various software and services that are available, “smart” technologies are changing the way farming is carried out. These technologies allow producers to look beyond what the eye can see by collecting non-traditional data and then using analytics tools to improve both food sustainability and profitability. “Smart Agriculture/farming” (SA) or “Digital Agriculture” (DA), often used interchangeably, refer to precision agriculture that is thus connected in a network of sensing and acting. It is a concept that employs modern information technologies, precision climate information, and crop/livestock developmental information to connect production variables to increase the quantity and quality of agricultural and food products. This is achieved by measuring and analyzing variables accurately, feeding the information into the cloud from edge devices, extracting trends from the various data, and subsequently providing information back to the producer in a timely manner. Smart agriculture covers many disciplines, including biology, mechanical engineering, automation, machine learning, artificial intelligence, and information technology-digital platforms. Minimum standards have been proposed for stakeholders with the aim to move toward this highly anticipated and ever-changing revolution. These foundational standards encompass the following general categories, including precise articulation of objectives, and baseline standards for the Internet of Things (IoT), including network infrastructure (e.g., stable 4G or 5G networks or a wireless local area network (WLAN) are available to end users). To sum up, SA aims to improve production efficiency, enhance the quality and quantity of agricultural products, reduce costs, and improve the environmental footprint of the industry. SA’s ecosystem should be industry self-governed and collaboratively financed. SA stakeholders and end-users’ facilities should meet standard equipment requirements, such as sensor accuracy, end data collectors, relevant industry compliant software, and trusted data analytics. The SA user is willing to be part of the SA ecosystem. This short perspective aims to summarize digital/smart agriculture concept in plain language.

A study of integrated pest management models with instantaneous and non-instantaneous impulse effects.

The occurrence of pests and diseases during agricultural production affects the quality and quantity of agricultural products. It is important to evaluate the impact of various factors on pests to achieve optimal results of integrated pest management (IPM) during its implementation. In this paper, we considered the transient and non-transient effects of chemical control on pests and the effects on natural enemies at different times, and developed a corresponding pest control model. Detailed studies and comparisons were conducted for spraying pesticides either more or less frequently as compared to strategies for releasing natural enemies. The threshold conditions for global asymptotic stabilization of the pest extinction period solution was obtained. Using two-parameter and sensitivity analysis techniques, the parameters affecting the variation of the threshold were discussed. By comparing these two pest control strategies, we found the existence of optimal application and release frequencies. Finally, in order to control pests below the economic threshold level, the state-dependent pest model was numerically investigated. The results show that the presence or absence of chemical control of pests can depend on the values taken for the parameters in the model. Based on this information, pest control experts can make decisions about the best spraying time and the best release rate.

Wireless sensor network deployment optimization for a smart farming application: comparison of two Multi-Objective Evolutionary Algorithms

As it is one of the main means of insuring food security, agriculture has employed different technologies such as the Internet of Things and wireless sensor networks (WSN), to improve the quality and quantity of agricultural products, while preserving natural resources. But unfortunately, in agricultural plots where we have large surfaces of interest, the optimization of node deployment in a WSN remains among the major problems to be solved. In this work, we proposed a WSN node deployment optimization model for an agricultural application according to classical constraints of coverage, over-coverage, connectivity and nodes number, in addition to the nodes separating distance constraint which affects the quality of physical parameters models. We have applied two variants of Multi-Objective Genetic Algorithms, the Non Sorting Genetic Algorithm II (NS-GA II) and the Strength Pareto Evolutionary Algorithm II (SPEA II). As a result, for a 100 m2 plot, both algorithms ensured a communication rate of 100% while SPEA 2 presented a lower sensor number and over-coverage rates with a smaller separating distance, and the execution time of NSGA II was shorter with 11 s. Besides, both of them were greedy in terms of computation time with the increase in the size of the plots.

A Literature Review and Statistical Analysis of Turkish Agricultural Data: Assessing Crop Dependence on Insect Pollinators in Türkiye

The study delves into the critical role of pollination in shaping the quality and quantity of agricultural products. Insect pollination, with a primary focus on Apis Mellifera L., is identified as an indispensable element in the development of a significant proportion of global agricultural crops. Moreover, the study underscores the multifaceted benefits of insect pollination, not only enhancing crop production but also elevating the overall quality of produce. Fruits and oilseeds are cited as beneficiaries of bee pollination, resulting in larger, higherquality crops with extended shelf lives. Commercial crop pollination relies mainly on managed honeybees. The study elucidates the versatility, cost-effectiveness, and adaptability of honeybee colonies for pollination purposes. However, it is noted that honey bee populations are dwindling due to factors such as parasites, pesticide usage, limited floral resources, and Nosema infection, which poses a potential risk to agricultural crop pollination. The research focuses on insect pollination due to its crucial role in the process. The goal of this study is to find out what percentage of Turkish crops depend on insects to pollinate them. Data on plants requiring insect pollination were obtained through a comprehensive literature review, while data on Turkish agricultural products were sourced from the Turkish Statistical Institute. This comprehensive study explores the vital role of insect pollinators in Turkish agriculture. This statement highlights the crucial role of plant and animal production in meeting the nutritional needs of societies, while emphasizing the importance of increasing the size of agricultural cultivation areas to enhance overall agricultural productivity.

Implementation of Plant Leaf Disease Detection using K-means Clustering and Neural Networks

Plants exist all over the place; we live, as well as places without us. Plant disease is one of the essential causes that reduces quantity and degrades quality of the agricultural merchandises. Plant diseases have turned into a terrible as it can cause significant reduction in both quality and quantity of agricultural products. Images form important data and information in biological sciences. Until recently photography was the only method to reproduce and report such data. It is difficult to quantify or treat the photographic data mathematically. This project, classifies the plant leaves and stems at hand into infected and non-infected classes. The developing software provides a fast and accurate method in which the leaf diseases are detected and classified using k-means based segmentation and neural networks-based classification. Most common diseases seen in the leaves of Tapioca and Mango are discussed here for this approach. In this paper, respectively, the applications of K-means clustering and Neural Networks (NNs) have been formulated for clustering and classification of diseases that effect on plant leaves. Recognizing the disease is mainly the purpose of the proposed approach. Thus, the proposed Algorithm was tested on five diseases which influence on the plants; they are: Early scorch, Cottony mold, ashen mold, late scorch, tiny whiteness. The experimental results indicate that the proposed approach is a valuable approach, which can significantly support an accurate detection of leaf diseases in a little computational effort. This project gives 95% of efficiency using MATLAB simulation results.

First report of leaf spot on sweet potato (Ipomoea batatas) caused by Alternaria alternata in Bulgaria

For the first time in Bulgaria, leaf spotting on sweet potatoes was investigated, and the causative agent, Alternaria alternata, was reported. The collected morphological data aimed to determine the identity of the fungus. According to Koch, the primary isolates from the damaged parts are identical to those produced from pathogenicity tests. In a laboratory we tested sixty-two leaves which had similar symptoms, with slight to medium-sized lesions with concentric circles and a yellowish halo. In general, the attack from Alt. alternate affected 7% of all plants and 32% of the examined leaves. The pathogen tests proved that the pathogen could also cause damage to tubers during storage. Knowing the etiology of diseases is essential for taking preventive measures and thus preserving the quality and quantity of agricultural production. Keywords: Alternaria alternata, sweet potato, leaf spots, pathogen, pathogenicity

Pelatihan Smart Farming Berbasis IoT Kepada Kelompok Tani Jamur Tiramu Dalam Peningkatan Ekonomi Di Kabupaten Kampar

Purpose - This community service activity aims to socialize Smart Farming as a new concept in agriculture by integrating technology as an innovation. Smart Farming makes it easy for farmers to increase the quality and quantity of agricultural products through technology. The technology used in this activity is IoT (Internet of Things), a mushroom media sprayer that can be controlled automatically and adjusted to the required temperature. Design/methodology/approach – The methodology used in this community service activity is mentoring and outreach. This activity is a training that concerns two activity themes, namely mentoring the installation of IoT on mushroom media and socializing the business management of oyster mushroom products. Assistance activities will be carried out by technology experts who will guide partners in assembling IoT circuits. In comparison, the socialization that will be carried out will involve resource persons who are experts in agribusiness and will provide debriefing on the management of oyster mushroom input supplies. Findings – Community service activities for Tiramu oyster mushroom partners that are carried out obtain the results of activities that bring significant benefits to partners. The benefit obtained from this activity is an automatic sprayer technology that can be adjusted to the room temperature conditions of the oyster mushroom required by the oyster mushroom. Partners' skills and knowledge also increase with socialization activities that equip partners with knowledge in improving the quality and quantity of oyster mushroom products produced. From some of the things mentioned above, community service activities with results in a series of IoT and partner skills can be said to have enormous benefits for Tiramu oyster mushroom partners. Originality/value – The implications of community service activities produce smart farming technology tools and the ability of Tiramu oyster mushroom partners to improve product quality and quantity.

IoT-based Hydroponic Plant Monitoring System

The Industrial Revolution 4.0 has an impact in the form of changes in various fields of human civilization, one of which is the agricultural sector. By applying IoT technology, hydroponic plants will effectively be accurate. IoT has room for improvement in the quality and quantity of agricultural production because it facilitates the automation of monitoring various processes with high precision This research uses the prototype method. Which uses the concept of direct monitoring and allows iterative changes to be made until the desired results are achieved. So this prototype method makes it possible to display the display directly. The microcontroller used is ESP32 which is connected to 3 sensors, namely the TDS sensor, DHT11 sensor and HC-SR04 sensor which are directly updated in the blynk application. In making the software program used is the Arduino IDE. Implementation of the tool is carried out on a floating raft installation. This iot-based hydroponic plant monitoring system has been successfully made and is able to monitor well. Because the system made is related to water, it is necessary to design a tool that is safer and has more protection so that it can’t only run well but also safer for users and a high level of durability.

Natural abilities for Agricultural Development in Shaqlawa District

Shaqlawa District, one of the districts of Erbil Governorate, which plays an important role in the agricultural sector, as it possesses a range of important natural resources that have a direct impact on agricultural development in the district. The main objective of the research is to present the natural ability of the region and its role in development between 2010 and 2020 and to show its positive and negative role in the process In order to obtain the goal of the research, we relied on the data and statistics of the Directorate of Agriculture of Arbil and the Division of Agriculture (Shaqlawa, Harir and Balisan) and the researcher relied on the preparation of research maps on geographic information systems (GIS) and finally we reached the following conclusion, the natural capabilities authorized by the region have a direct impact on the production of a large quantity of agricultural products annually.

Evaluation of smart farm training for extension officers to support digitalizing era

Smart farming is an agricultural concept based on precision agriculture. It utilizes technology automation supported by big data management, machine learning or artificial intelligence, and the Internet of Things to improve the quality and quantity of agricultural production. In its implementation, extension workers play a vital role as the vanguard of this program escort. Therefore, increasing the capacity of extension workers in smart farming is very necessary. This paper evaluated several aspects of smart farming training for extension workers. This paper uses secondary data from the evaluation form of 30 participants collected from Batangkaluku Agricultural Training Centre. Results showed that male extension officers dominated the training participants (70%). The subjects/training modules can be mastered by participants with scores>3.4 out of 5. The training can increase participants’ comprehension of the material up to 2.75x higher. The satisfaction level was above 4 out of 5. The findings can help the organizing committee in improving related aspects. Increased capacity building of agriculture extension officers by such training was expected to overcome the gap in the information of technology innovation from researchers to farmers.

A SURVEY PAPER ON PLANT DISEASE IDENTIFICATION USING MACHINE LEARNING

Agriculture plays an important role in farmer’s life. Sometimes manual identification of disease is time consuming and need of labor is more. One of the most important facts that reduce the growth of plants is disease attack. Overall study about agriculture shows that quality and quantity of agricultural products may be reduced due to various factors of plant diseases. These diseases can be more easily identified by using machine learning approach as compared to manual method. Hence machine learning method can be used to identify the affected leaf images.Images captured by camera will be processed using different image processing technique. These techniques will help inidentifying plant diseases thereby increasing the yield of plants. This survey paper describes plant disease identificationusing Machine Learning Approach and study in detail about various techniques for disease identification and classification is also done. Keywords: Feature extraction, image processing techniques, SVM, PNN, ANN and GA

The Harmful Effects of Pesticides on the Environment and Human Health: A Review

The population inflation that countries are witnessing during this century, makes it imperative to provide sufficient quantities of agricultural products to meet their urgent needs. Therefore, it became very necessary to use pesticides to improve agricultural crop productivity and reduce losses resulting from agricultural pests. The indiscriminate use of pesticides causes severe risks not only on agricultural fields, but also workers in their manufacturing processes and individual use in homes and institutions. The main adverse effects of utilizing pesticides on human health, soil, microorganisms of soil, surface water and groundwater have been covered in this review. This investigation is aiming to elevate environmental awareness, highlight the serious harms of pesticides and provide guidance for implementing a serious solution from the people and authorities. In addition, the most important strategies to reduce the pesticides risks have been summarized.