Search results for: tillage and crop establishment

Authors: Aziz Larbi, Widad Sadok

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In Morocco, the mountainous regions extend over about 26% of the national territory where 30% of the total population live. They contain opportunities for agriculture, forestry, pastureland and mining. The production systems in these zones are characterised by crop diversification. However, these areas have become vulnerable to the effects of climate change. To understand these effects in relation to the population living in these areas, a study was carried out in the zone of Taliouine, in the Anti-Atlas. The vulnerability of crop productions to climate change was analysed and the different ways of adaptation adopted by farmers were identified. The work was done on saffron, the most profitable crop in the target area even though it requires much water. Our results show that the majority of the farmers surveyed had noticed variations in the climate of the region: irregularity of precipitation leading to a decrease in quantity and an uneven distribution throughout the year; rise in temperature; reduction in the cold period and less snow. These variations had impacts on the cropping system of saffron and its productivity. To cope with these effects, the farmers adopted various strategies: better management and use of water; diversification of agricultural activities; increase in the contribution of non-agricultural activities to their gross income; and seasonal migration.

Keywords: climate change, Taliouine, saffron, perceptions, adaptation strategies

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

Procedia PDF Downloads 45

Authors: Jason West

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Low profitability in agriculture production along with increasing scrutiny over environmental effects is limiting food production at scale. In contrast, the mining sector offers access to resources including energy, water, transport and chemicals for food production at low marginal cost. Scalable agricultural production can benefit from the nexus of resources (water, energy, transport) offered by mining activity in remote locations. A decision support bioeconomic model for controlled environment vertical farms was used. Four submodels were used: crop structure, nutrient requirements, resource-crop integration, and economic. They escalate to a macro mathematical model. A demonstrable dynamic systems framework is needed to prove productive outcomes are feasible. We demonstrate a generalized bioeconomic macro model for controlled environment production systems in minesites using systems dynamics modeling methodology. Despite the complexity of bioeconomic modelling of resource-agricultural dynamic processes and interactions, the economic potential greater than general economic models would assume. Scalability of production as an input becomes a key success feature.

Keywords: crop production systems, mathematical model, mining, agriculture, dynamic systems

Procedia PDF Downloads 49

Authors: E. Kharaishvili

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The paper shows the necessity of farm diversification in accordance with the current trends in agricultural sector of Georgia. The possibilities for the diversification and the corresponding economic policy are suggested. The causes that hinder diversification of farms are revealed, possibilities of diversification are suggested and the ability of increasing employment through diversification is proved. Index of harvest diversification is calculated based on the areas used for cereals and legumes, potatoes and vegetables and other food crops. Crop and livestock production indexes are analyzed, correlation between crop capacity index and value-added per one worker and one ha is studied. Based on the research farm diversification strategies and priorities of corresponding economic policy are presented. Based on the conclusions relevant recommendations are suggested.

Keywords: farm diversification, diversification index, agricultural development policy

Procedia PDF Downloads 431

Authors: Hafsat Iyabo Sa'adu

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A salient feature of the Nigerian Tax Law is the right of the taxpayer to demand for a refund where excess tax is paid. Section 23 of the Federal Inland Revenue Service (Establishment) Act, 2007 vests Federal Inland Revenue Services with the power to make tax refund as well as set guidelines and requirements for refund process from time to time. In addition, Section 61 of the Federal Inland Revenue Service (Establishment) Act, 2007, empowers the Federal Inland Revenue Services to issue information circular to acquaint stakeholders with the policy on the refund process. A Circular was issued to that effect to correct the position that until after the annual audit of the Service before such excess can be paid to the claimant/taxpayer. But it is amazing that such circular issuance does not feature under the states’ laws. Hence, there is an inconsistencies in the tax paying system in Nigeria. This study, therefore, sets an objective, to examine the trending concept of tax refund in Nigeria. In order to achieve this set objective, a doctrinal study went under way, wherein both federal and states laws were consulted including journals and textbooks. At the end of the research, it was revealed that the law should be specific as to the time frame within which to make the refund. It further revealed that it is essential to put up a legal framework for the tax system to recognize excess payment as debt due from the state. This would provide a foundational framework for the relationship between taxpayers and Federal Inland Revenue Service as well as promote effective tax administration in all the states of the federation. Several Recommendations were made especially relating to legislative passage of ‘’Refund Circular Bill at the states levels’ pursuant to the Federal Inland Revenue Service (Establishment) Act, 2007.

Keywords: claim, Nigeria, refund, right

Procedia PDF Downloads 90

Authors: Gobena D. Bayisa, A. Mekonen, Megersa O. Dinka, Tilahun H. Nebi, M. Boja

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Crop production in arid and semi-arid regions of Ethiopia is largely limited by water availability. Changing climate conditions and declining water resources increase the need for appropriate approaches to improve water use and find ways to increase production through reduced and more reliable water supply. In the years 2021/22 and 2022/23, a field experiment was conducted to evaluate the effect of limited irrigation water use on bread wheat (Triticum aestivum L.) production, water use efficiency, and financial benefits. Five irrigation treatments, i.e., full irrigation (100% ETc/ control), 85% ETc, 70% ETc, 55% ETc, and 40% ETc, were evaluated using a randomized complete block design (RCBD) with four replicates in the semi-arid climate condition of Awash basin of Ethiopia. Statistical analysis showed a significant effect of irrigation levels on wheat grain yield, water use efficiency, crop water response factor, economic profit, wheat grain quality, aboveground biomass, and yield index. The highest grain yield (5085 kg ha⁻¹) was obtained with 100% ETc irrigation (417.2 mm), and the lowest grain yield with 40% ETc (223.7 mm). Of the treatments, 70% ETc produced the higher wheat grain yield (4555 kg ha⁻¹), the highest water use efficiency (1.42 kg m⁻³), and the highest yield index (0.43). Using the saved water, wheat could be produced 23.4% more with a 70% ETc deficit than full irrigation on 1.38 ha of land, and it could get the highest profit (US$2563.9) and higher MRR (137%). The yield response factor and crop-water production function showed potential reductions associated with increased irrigation deficits. However, a 70% ETc deficit is optimal for increasing wheat grain yield, water use efficiency, and economic benefits of irrigated wheat production. The result indicates that deficit irrigation of wheat under the typical arid and semi-arid climatic conditions of the Awash Basin can be a viable irrigation management approach for enhancing water use efficiency while minimizing the decrease in crop yield could be considered effective.

Keywords: crop-water response factor, deficit irrigation, water use efficiency, wheat production

Procedia PDF Downloads 39

Authors: Hassan Kian

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The future of millions of people and consequently, the future of societies and humanity is threatened by a great threat which is called wasted human resources. Perhaps Pasteur, Beethoven and Avicenna, Lavoisier and Einstein and millions of genius individuals and thinkers may have never been discovered and could not found a chance of being known due to various reasons such as poverty or social status, and other problems. So without being able to serve humanity, their talents are fully wasted. While, if a global mechanism exists to discover their talents in different countries and provide to them the right direction, during less than a generation, human society will face to a profound transformation and sustainable social justice will be formed as the basis of sustainable development of human resources. Therefore, the situation of the institution which organizes the affair of discovering and guiding talents was vacant at the level of the international community and its necessity has been felt. So in this plan, the establishment and development of such an organization have been suggested in the international context.

Keywords: talent identification, comparative advantage, sustainable justice, sustainable development

Procedia PDF Downloads 200

Authors: Vijay Shankar

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In the era of water scarcity, effective use of water via irrigation requires good methods for determining crop water needs. Implementation of irrigation scheduling programs requires an accurate estimate of water use by the crop. Moisture depletion from the root zone represents the consequent crop evapotranspiration (ET). A numerical model for simulating soil water depletion in the root zone has been developed by taking into consideration soil physical properties, crop and climatic parameters. The governing differential equation for unsaturated flow of water in the soil is solved numerically using the fully implicit finite difference technique. The water uptake by plants is simulated by using three different sink functions. The non-linear model predictions are in good agreement with field data and thus it is possible to schedule irrigations more effectively. The present paper describes irrigation scheduling based on moisture depletion from the different layers of the root zone, obtained using different sink functions for three cash, oil and forage crops: cotton, safflower and barley, respectively. The soil is considered at a moisture level equal to field capacity prior to planting. Two soil moisture regimes are then imposed for irrigated treatment, one wherein irrigation is applied whenever soil moisture content is reduced to 50% of available soil water; and other wherein irrigation is applied whenever soil moisture content is reduced to 75% of available soil water. For both the soil moisture regimes it has been found that the model incorporating a non-linear sink function which provides best agreement of computed root zone moisture depletion with field data, is most effective in scheduling irrigations. Simulation runs with this moisture uptake function result in saving 27.3 to 45.5% & 18.7 to 37.5%, 12.5 to 25% % &16.7 to 33.3% and 16.7 to 33.3% & 20 to 40% irrigation water for cotton, safflower and barley respectively, under 50 & 75% moisture depletion regimes over other moisture uptake functions considered in the study. Simulation developed can be used for an optimized irrigation planning for different crops, choosing a suitable soil moisture regime depending upon the irrigation water availability and crop requirements.

Keywords: irrigation water, evapotranspiration, root uptake models, water scarcity

Procedia PDF Downloads 303

Authors: Iyabode A. Kehinde, Joshua O. Oyekanmi, Jumoke T. Abimbola, Olajumoke E. Ayanda

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African yam bean (AYB), (Sphenostylis stenocarpa) is a leguminous crop that provides nutritionally rich seeds, tubers and leaves for human consumption. AYB potentials as an important food security crop is yet to be realized and thus classified as underutilized crop. Underutilization of the crop has been partly associated with scarce information on the incidence and characterization of fungal endophytes infecting vascular parts of AYB. Accurate and robust detection of these endophytic fungi is essential for diagnosis, modeling, surveillance and protection of germplasm (seed) health. This work aimed at isolating and identifying fungal endophytes associated with leaves, stems and roots of AYB in Ogun State, Nigeria. This study investigated both cultural and molecular properties of endophytic fungi in AYB for its characterization and diversity. Fungal endophytes were isolated and culturally identified. DNA extraction, PCR amplification using ITS primers and analyses of nucleotide sequences of ribosomal DNA fragments were conducted on selected isolates. BLAST analysis was conducted on consensus nucleotide sequences of 28 out of 30 isolates and results showed similar homology with genera of Rhizopus, Cunninghamella, Fusarium, Aspergillus, Penicillium, Alternaria, Diaporthe, Nigrospora, Purpureocillium, Corynespora, Magnaporthe, Macrophomina, Curvularia, Acrocalymma, Talaromyces and Simplicillium. Slight similarity was found with endophytes associated with soybean. Phylogenetic analysis by maximum likelihood method showed high diversity among the general. These organisms have high economic importance in crop improvement. For an instance, Purpureocillium lilacinum showed high potential in control of root rot caused by nematodes in tomatoes. Though some can be pathogens, but many of the fungal endophytes have beneficial attributes to plant in host health, uptake of nutrients, disease suppression, and host immunity.

Keywords: molecular characterization, African Yam Bean, fungal endophyte, plant parts

Procedia PDF Downloads 176

Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

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This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

Procedia PDF Downloads 41

Authors: R. S. Giraddi, C. M. Poleshi

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Organic cultivation of crops is gaining importance consumer awareness towards pesticide residue free foodstuffs is increasing globally. This is also because of high costs of synthetic fertilizers and pesticides, making the conventional farming non-remunerative. In India, organic manures (such as vermicompost) are an important input in organic agriculture.  Though vermicompost obtained through earthworm and microbe-mediated processes is known to comprise most of the crop nutrients, but they are in small amounts thus necessitating enrichment of nutrients so that crop nourishment is complete. Another characteristic of organic manures is that the pest infestations are kept under check due to induced resistance put up by the crop plants. In the present investigation, deoiled neem cake containing azadirachtin, copper ore tailings (COT), a source of micro-nutrients and microbial consortia were added for enrichment of vermicompost. Neem cake is a by-product obtained during the process of oil extraction from neem plant seeds. Three enriched vermicompost blends were prepared using vermicompost (at 70, 65 and 60%), deoiled neem cake (25, 30 and 35%), microbial consortia and COTwastes (5%). Enriched vermicompost was thoroughly mixed, moistened (25+5%), packed and incubated for 15 days at room temperature. In the crop response studies, the field trials on chili (Capsicum annum var. longum) and soybean, (Glycine max cv JS 335) were conducted during Kharif 2015 at the Main Agricultural Research Station, UAS, Dharwad-Karnataka, India. The vermicompost blend enriched with neem cake (known to possess higher amounts of nutrients) and vermicompost were applied to the crops and at two dosages and at two intervals of crop cycle (at sowing and 30 days after sowing) as per the treatment plan along with 50% recommended dose of fertilizer (RDF). 10 plants selected randomly in each plot were studied for pest density and plant damage. At maturity, crops were harvested, and the yields were recorded as per the treatments, and the data were analyzed using appropriate statistical tools and procedures. In the crops, chili and soybean, crop nourishment with neem enriched vermicompost reduced insect density and plant damage significantly compared to other treatments. These treatments registered as much yield (16.7 to 19.9 q/ha) as that realized in conventional chemical control (18.2 q/ha) in soybean, while 72 to 77 q/ha of green chili was harvested in the same treatments, being comparable to the chemical control (74 q/ha). The yield superiority of the treatments was of the order neem enriched vermicompost>conventional chemical control>neem cake>vermicompost>untreated control.  The significant features of the result are that it reduces use of inorganic manures by 50% and synthetic chemical insecticides by 100%.

Keywords: humic acid, azadirachtin, vermicompost, insect-pest

Procedia PDF Downloads 247

Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

Procedia PDF Downloads 118

Authors: Nour Elhouda Abed, Bedj Mimi, Wahid Slimani, Mourad Atif, Abdelhakim Ouzzane, Hocine Irekti, Abdelkader Bekki

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The most frequent system of cereal production in Algeria is fallow-wheat. This is an extensive system that meets only the half needs some cereals and fodder demand. Resorption of fallow has become a strategic necessity to ensure food security in response to the instability of supply and the persistence of higher food prices on the world market. Despite several attempts to replace the fallow by crop cultures, choosing the best crop remains. Today, the agronomic and economic interests of legumes are demonstrated. However, their crop culture remains marginalized because of the weakness and instability of their performance. In the context of improving legumes and cereals crops as well as fallow resorption, we undertook to test, in the field, the effect of rhizobial inoculation of Phaseolus vulgaris in association with Zea Mays. We firstly studied the genetic diversity of rhizobial strains that nodulate P.vulgaris isolated from fifteen (15) different regions. ARDRA had shown 18 different genetic profiles. Symbiotic characterization highlighted a strain that highly significantly improved the fresh and dry weight of the host plant, in comparison to the negative control (un-inoculated) and the positive control (inoculated with the reference strain CIAT 899). In the field, the selected strain increased significantly the growth and yield of P.vulgaris and Zea Mays comparing to the non-inoculated control. However, the mix inoculation (selected strain+ Ciat 899) had not given the best parameters showing, thus, no synergy between the strains. These results indicate the replacing fallow by a crop legume in intercropping with cereals crops.

Keywords: fallow, intercropping, inoculation, legumes-cereals

Procedia PDF Downloads 335

Authors: Mahmood Iqbal, Khalid Nawab, Tachibana Satoshi

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Farmer Field School (FFS) is constantly aims to assist farmers to determine and learn about field ecology and integrated crop management. The study was conducted to examine the change in productivity of tomato crop in the study area; to determine increase in per acre yield of the crop, and find out reduction in per acre input cost. A study of tomato crop was conducted in ten villages namely Jabban, Bijligar Colony, Palonow, Heroshah, Zara Maira, Deghar Ghar, Sidra Jour, Anar Thangi, Miangano Korona and Wartair of district Malakand. From each village 15 respondents were selected randomly on the basis of identical allocation making sample size of 150 respondents. The research was based on primary as well as secondary data. Primary data was collected from farmers while secondary data were taken from Agriculture Extension Department Dargai, District Malakand. Interview schedule was planned and each farmer was interviewed personally. The study was based on comparison of cost, yield and income of tomato before and after FFS. Paired t-test and Statistical Package for Social Sciences (SPSS) was used for analysis; outcome of the study show that integrated pest management project has brought a positive change in the attitude of farmers of the project area through FFS approach. In district Malakand 66.0% of the respondents were between the age group of 31-50 years, 11.3% of respondents had primary level of education, 12.7% of middle level, 28.7% metric level, 3.3% of intermediate level and 2.0% of graduate level of education while 42.0% of respondents were illiterate and have no education. Average land holding size of farmers was 6.47 acres, cost of seed, crop protection from insect pest and crop protection from diseases was reduced by Rs. 210.67, Rs. 2584.43 and Rs. 3044.16 respectively, the cost of fertilizers and cost of farm yard manure was increased by Rs.1548.87 and Rs. 1151.40 respectively while tomato yield was increased by 1585.03 kg/acre from 7663.87 to 9248.90 kg/acre. The role of FFS initiate by integrated pest management project through department of agriculture extension for the development of agriculture was worth mentioning. It has brought enhancement in crop yield of tomato and their income through FFS approach. On the basis of results of the research studies, integrated pest management project should spread their developmental activities for maximum participation of the complete rural masses through participatory FFS approach.

Keywords: agriculture, Farmers field schools, extension education, tomato

Procedia PDF Downloads 582

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

Procedia PDF Downloads 42

Authors: Bijan Nahavandi, Navid Jafarinejad, Somayeh Mehrafzad

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Strategy maps represent the way of value creation in in each organization. Nowadays, implementation of strategy is the main concern for all organizations. Strategy map establishment is the start-up point of strategy implementation and this shows the critical importance of this concept. After some years past since emergence of strategy map, there are some shortcomings in its methodology that frequently quoted by many of researchers. One of these shortcomings is the shortage of a mechanism for refinement of objectives candidate for entrance to map. Organizations in practice have obsession and avidity to determine more number of objectives in strategy map. This study wants to represent a step by step approach to help obviate this problem using quality function deployment (QFD) as a helpful tool and fuzzy screening method. Finally, represented approach applies in a practical case and conclusions have been explained.

Keywords: balanced scorecard, fuzzy screening, house of strategic objectives (HoSO), quality function deployment, strategy map

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Sanari Chalin Moriri, Kwabena Kingsley Ayisi, Alina Mofokeng

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Dryland smallholder farmers in South Africa are vulnerable to all kinds of risks, and it negatively affects crop productivity and profit. Pigeonpea is a leguminous and multipurpose crop that provides food, fodder, and wood for smallholder farmers. The majority of these farmers are still growing pigeonpea from traditional unimproved seeds, which comprise a mixture of genotypes. The objectives of the study were to identify the key risk factors that affect pigeonpea productivity and to develop management strategies on how to alleviate the risk factors in pigeonpea production. The study was conducted in two provinces (Limpopo and Mpumalanga) of South Africa in six municipalities during the 2020/2021 growing seasons. The non-probability sampling method using purposive and snowball sampling techniques were used to collect data from the farmers through a structured questionnaire. A total of 114 pigeonpea producers were interviewed individually using a questionnaire. Key stakeholders in each municipality were also identified, invited, and interviewed to verify the information given by farmers. Data collected were subjected to SPSS statistical software 25 version. The findings of the study were that majority of farmers affected by risk factors were women, subsistence, and old farmers resulted in low food production. Drought, unavailability of improved pigeonpea seeds for planting, access to information, and processing equipment were found to be the main risk factors contributing to low crop productivity in farmer’s fields. Above 80% of farmers lack knowledge on the improvement of the crop and also on the processing techniques to secure high prices during the crop off-season. Market availability, pricing, and incidence of pests and diseases were found to be minor risk factors which were triggered by the major risk factors. The minor risk factors can be corrected only if the major risk factors are first given the necessary attention. About 10% of the farmers found to use the crop as a mulch to reduce soil temperatures and to improve soil fertility. The study revealed that most of the farmers were unaware of its utilisation as fodder, much, medicinal, nitrogen fixation, and many more. The risk of frequent drought in dry areas of South Africa where farmers solely depend on rainfall poses a serious threat to crop productivity. The majority of these risk factors are caused by climate change due to unrealistic, low rainfall with extreme temperatures poses a threat to food security, water, and the environment. The use of drought-tolerant, multipurpose legume crops such as pigeonpea, access to new information, provision of processing equipment, and support from all stakeholders will help in addressing food security for smallholder farmers. Policies should be revisited to address the prevailing risk factors faced by farmers and involve them in addressing the risk factors. Awareness should be prioritized in promoting the crop to improve its production and commercialization in the dryland farming system of South Africa.

Keywords: management strategies, pigeonpea, risk factors, smallholder farmers

Procedia PDF Downloads 178

Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

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Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

Procedia PDF Downloads 377

Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Ezzat Abd El Lateef

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Agroforestry means combining the management of trees with productive agricultural activities, especially in semiarid regions where crop yield increases are limited in agroforestry systems due to the fertility and microclimate improvements and the large competitive effect of trees with crops for water and nutrients, in order to assess the effect of agroforestry of some field crops with citrus trees as an approach to establish biodiversity in fruit tree plantations. Three field crops, i.e., maize, soybean and sunflower, were inter-planted with seedless orange trees (4*4 m) or were planted as solid plantings. The results for the trees indicated a larger fruit yield was obtained when soybean and sunflowers were interplant with citrus. Statistically significant effects (P<0.05) were found for maize grain and biological yields, with increased yields when grown as solid planting. There were no differences in the yields of soya bean and sunflower, where the yields were very similar between the two cropping systems. It is evident from the trials that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Maize, unlike the other crops, was more sensitive to shade conditions under agroforestry practice and not preferred in the biodiversity system. The potential of agroforestry to improve or increase biodiversity is efficient as the understorey crops are usually C4 species, and the overstorey trees are invariably C3 species in agroforestry. Improvement in interplant species is most likely if the understorey crop is a C3 species, which are usually light saturated in the open, and partial shade may have little effect on assimilation or by a concurrent reduction in transpiration. It could be concluded that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Some field crops could be employed successfully, like soybean or sunflowers, while others like maize are sensitive to incorporate in agroforestry system.

Keywords: agroforestry, field crops, C3 and C4 plants, yield

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Authors: S. Boonlertnirun, R. Suvannasara, K. Boonlertnirun

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Hypoxia has negative effects on growth and crop yield, its severity is so varied depending on crop growth stages, duration of hypoxia and crop species. The objective was to evaluate the sensitive growth stage and the duration of hypoxia negatively affecting growth and yield of waxy corn. Pot experiment was conducted using a split plot in randomized complete block with 3 growth stages: V3 (3-4 true leaves), V7 (7-8 true leaves), and R1 (silking stage), and three hypoxic durations: 6, 9, and 12 days, in an open–ended outdoor greenhouse during January to March 2013. The results revealed that different growth stages had significantly (p < 0.5) different responses to hypoxia, seeing that the sensitive growth stage affecting plant height, yield and yield components was mostly detected in V7 growth stage whereas leaf greenness and days to silking were sensitive to hypoxia at R1 growth stage. Different hypoxic durations significantly affected the yield and yield components, hypoxic duration of twelve days showed the most negative effect greater than the others. In this present study, it can be concluded that waxy corn plants were waterlogged at V7 growth stage for twelve days had the most negative effect on yield and yield components.

Keywords: hypoxia duration, waxy corn, growth stage, Zea mays L.

Procedia PDF Downloads 359

Authors: Shirin Ghatrehsamani

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Higher efficiency and lower environmental impact are the consequence of using advanced technology in farming. They also help to decrease yield variability by diminishing weather variability impact, optimizing nutrient and pest management as well as reducing competition from weeds. A better understanding of the pros and cons of applying technology and finding the main reason for preventing the utilization of the technology has a significant impact on developing technology adoption among farmers and producers in the digital agriculture era. The results from two surveys carried out in 2019 and 2021 were used to investigate whether the crop types had an impact on the willingness to utilize technology on the farms. The main focus of the questionnaire was on utilizing precision agriculture (PA) technologies among farmers in some parts of the united states. Collected data was analyzed to determine the practical application of various technologies. The survey results showed more similarities in the main reason not to use PA between the two crop types, but the present application of using technology in specialty crops is generally five times larger than in row crops. GPS receiver applications were reported similar for both types of crops. Lack of knowledge and high cost of data handling were cited as the main problems. The most significant difference was among using variable rate technology, which was 43% for specialty crops while was reported 0% for row crops. Pest scouting and mapping were commonly used for specialty crops, while they were rarely applied for row crops. Survey respondents found yield mapping, soil sampling map, and irrigation scheduling were more valuable for specialty crops than row crops in management decisions. About 50% of the respondents would like to share the PA data in both types of crops. Almost 50 % of respondents got their PA information from retailers in both categories, and as the second source, using extension agents were more common in specialty crops than row crops.

Keywords: precision agriculture, smart farming, digital agriculture, technology adoption

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Authors: Anis Eloud, Ben Salah Nahla, Sayed Chehaibi

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In order to improve and develop the Tunisian agriculture, the government has encouraged the introduction of modern technologies and has also promoted the adoption of innovative practices cultures. Indeed, the extensive use of mechanization can increase crop productivity but its inadequate application also has a negative impact on the ground caused by the phenomenon of compaction. Which will cause the loss of soil fertility and increased production costs. This problem is accentuated with increase the stress on contact wheel / ground. For this reason, the objective of this study is to simulate the footprint of the ground contact / tire two types of tractor after their passage. The method of this work is based on a simulation including passages from two different tractors on soil with similar characteristics. Simulation parameters were based on the choice of two tractors masses of 6500 kg and 4400 kg of soil and sandy loam in nature. The analysis was performed using specific software. The main results showed that the heaviest tractor caused a constraint wheel / rear floor exceeding 100 kPa. For cons, the second tractor has caused stress wheel / rear floor of 50 kPa. The comparison of the two results showed that 6500 kg tractor made a serious and excessive compaction which generated a negative impact on soil quality and crop yields.

Keywords: compaction, soil, resistance to penetration, crop yields

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Authors: Alefsi D. Sanchez-Reinoso, Leonardo Lombardini, Hermann Restrepo

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Colombian coffee is recognized worldwide for its mild flavor and aroma. Its cultivation generates a large amount of waste, such as fresh pulp, which leads to environmental, health, and economic problems. Obtaining biochar (BC) by pyrolysis of coffee pulp and its incorporation to the soil can be a complement to the crop mineral nutrition. The objective was to evaluate the effect of the application of BC obtained from coffee pulp on the physiology and agronomic performance of the Castillo variety coffee crop (Coffea arabica L.). The research was developed in field condition experiment, using a three-year-old commercial coffee crop, carried out in Tolima. Four doses of BC (0, 4, 8 and 16 t ha-1) and four levels of chemical fertilization (CF) (0%, 33%, 66% and 100% of the nutritional requirements) were evaluated. Three groups of variables were recorded during the experiment: i) physiological parameters such as Gas exchange, the maximum quantum yield of PSII (Fv/Fm), biomass, and water status were measured; ii) physical and chemical characteristics of the soil in a commercial coffee crop, and iii) physiochemical and sensorial parameters of roasted beans and coffee beverages. The results indicated that a positive effect was found in plants with 8 t ha-1 BC and fertilization levels of 66 and 100%. Also, a positive effect was observed in coffee trees treated with 8 t ha-1 BC and 100%. In addition, the application of 16 t ha-1 BC increased the soil pHand microbial respiration; reduced the apparent density and state of aggregation of the soil compared to 0 t ha-1 BC. Applications of 8 and 16 t ha-1 BC and 66%-100% chemical fertilization registered greater sensitivity to the aromatic compounds of roasted coffee beans in the electronic nose. Amendments of BC between 8 and 16 t ha-1 and CF between 66% and 100% increased the content of total soluble solids (TSS), reduced the pH, and increased the titratable acidity in beverages of roasted coffee beans. In conclusion, 8 t ha-1 BC of the coffee pulp can be an alternative to supplement the nutrition of coffee seedlings and trees. Applications between 8 and 16 t ha-1 BC support coffee soil management strategies and help the use of solid waste. BC as a complement to chemical fertilization showed a positive effect on the aromatic profile obtained for roasted coffee beans and cup quality attributes.

Keywords: crop yield, cup quality, mineral nutrition, pyrolysis, soil amendment

Procedia PDF Downloads 77

Authors: Ákos Tótin

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In crop production the most modern hybrids are available for us, therefore the yield and yield stability is determined by the agro-technology. The purpose of the experiment is to adapt the modern agrotechnology to the new type of hybrids. The long-term experiment was set up in 2015-2016 on chernozem soil in the Hajdúság (eastern Hungary). The plots were set up in 75 thousand ha-1 plant density. We examined some mainly use hybrids of Hungary. The conducted studies are: germination dynamic, growing dynamic and the effect of annual weather for the yield. We use three different sowing date as early, average and late, and measure how many plant germinated during the germination process. In the experiment, we observed the germination dynamics in 6 hybrid in 4 replication. In each replication, we counted the germinated plants in 2m long 2 row wide area. Data will be shown in the average of the 6 hybrid and 4 replication. Growing dynamics were measured from the 10cm (4-6 leaf) plant highness. We measured 10 plants’ height in two weeks replication. The yield was measured buy a special plot harvester - the Sampo Rosenlew 2010 – what measured the weight of the harvested plot and also took a sample from it. We determined the water content of the samples for the water release dynamics. After it, we calculated the yield (t/ha) of each plot at 14% of moisture content to compare them. We evaluated the data using Microsoft Excel 2015. The annual weather in each crop year define the maize germination dynamics because the amount of heat is determinative for the plants. In cooler crop year the weather is prolonged the germination. At the 2015 crop year the weather was cold in the beginning what prolonged the first sowing germination. But the second and third sowing germinated faster. In the 2016 crop year the weather was much favorable for plants so the first sowing germinated faster than in the previous year. After it the weather cooled down, therefore the second and third sowing germinated slower than the last year. The statistical data analysis program determined that there is a significant difference between the early and late sowing date growing dynamics. In 2015 the first sowing date had the highest amount of yield. The second biggest yield was in the average sowing time. The late sowing date has lowest amount of yield.

Keywords: germination, maize, sowing date, yield

Procedia PDF Downloads 206

Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

Procedia PDF Downloads 36

Authors: Fitih Ademe, Kibebew Kibret, Sheleme Beyene, Mezgebu Getnet, Gashaw Meteke

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Soil moisture and nutrient availability are the two key edaphic factors that affect crop yields and are directly or indirectly affected by climate variability and change. The study examined climate-induced yield level, yield variability and gap of maize during 1981-2010 main growing season in the Central Rift Valley (CRV) of Ethiopia. Pearson correlation test was employed to see the relationship between climate variables and yield. The coefficient of variation (CV) was used to analyze annual yield variability. Decision Support System for Agro-technology Transfer cropping system model (DSSAT-CSM) was used to simulate the growth and yield of maize for the study period. The result indicated that maize grain yield was strongly (P<0.01) and positively correlated with seasonal rainfall (r=0.67 at Melkassa and r = 0.69 at Ziway) in the CRV while day temperature affected grain yield negatively (r= -0.44) at Ziway (P<0.05) during the simulation period. Variations in total seasonal rainfall at Melkassa and Ziway explained 44.9 and 48.5% of the variation in yield, respectively, under optimum nutrition. Following variation in rainfall, high yield variability (CV=23.5%, Melkassa and CV=25.3%, Ziway) was observed for optimum nutrient simulation than the corresponding nutrient limited simulation (CV=16%, Melkassa and 24.1%, Ziway) in the study period. The observed farmers’ yield was 72, 52 and 43% of the researcher-managed, water-limited and potential yield of the crop, respectively, indicating a wide maize yield gap in the region. The study revealed rainfed crop production in the CRV is prone to yield variabilities due to its high dependence on seasonal rainfall and nutrient level. Moreover, the high coefficient of variation in the yield gap for the 30-year period also foretells the need for dependable water supply at both locations. Given the wide yield gap especially during lower rainfall years across the simulation periods, it signifies the requirement for a more dependable application of irrigation water and a potential shift to irrigated agriculture; hence, adopting options that can improve water availability and nutrient use efficiency would be crucial for crop production in the area.

Keywords: climate variability, crop model, water availability, yield gap, yield variability

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Authors: Zulkifli Yusop

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The severity of December 2014 flood on the east coast of Peninsular Malaysia has raised concern over the adequacy of existing land use practices and policies. This article assesses flood responses to selective logging, plantation establishment (oil palm and rubber) and their subsequent management regimes. The hydrological impacts were evaluated on two levels: on-site (mostly in the upstream) and off-site to reflect the cumulative impact at downstream. Results of experimental catchment studies suggest that on-site impact of flood could be kept to a minimum when selecting logging strictly adhere to the existing guidelines. However, increases in flood potential and sedimentation rate were observed with logging intensity and slope steepness. Forest conversion to plantation show the highest impacts. Except on the heavily compacted surfaces, the ground revegetation is usually rapid within two years upon the cessation of the logging operation. The hydrological impacts of plantation opening and replanting could be significantly reduced once the cover crop has fully established which normally takes between three to six months after sowing. However, as oil palms become taller and the canopy gets closer, the cover crop tends to die off due to light competition, and its protecting function gradually diminishes. The exposed soil is further compacted by harvesting machinery which subsequently leads to greater overland flow and erosion rates. As such, the hydrological properties of matured oil palm plantations are generally poorer than in young plantation. In hilly area, the undergrowth in rubber plantation is usually denser compared to under oil palm. The soil under rubber trees is also less compacted as latex collection is done manually. By considering the cumulative effects of land-use over space and time, selective logging seems to pose the least impact on flood potential, followed by planting rubber for latex, oil palm and Latex Timber Clone (LTC). The cumulative hydrological impact of LTC plantation is the most severe because of its shortest replanting rotation (12 to 15 years) compared to oil palm (25 years) and rubber for latex (35 years). Furthermore, the areas gazetted for LTC are mostly located on steeper slopes which are more susceptible to landslide and erosion. Forest has limited capability to store excess rainfall and is only effective in attenuating regular floods. Once the hydrologic storage is exceeded, the excess rainfall will appear as flood water. Therefore, for big floods, rainfall regime has a much bigger influence than land use.

Keywords: selective logging, plantation, extreme rainfall, debris flow

Procedia PDF Downloads 319

Authors: Sunita Singh, Rajani Srivastava

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For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.

Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices

Procedia PDF Downloads 327