Search results for: crop disease

Authors: Narayan Prasad Adhikari

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In Nepal, the crop residues have often been considered as one of the potential sources of energy to cope with prevailing energy crisis. However, the lack of systematic studies about production and various other competent uses of crop production is the main obstacle to evaluate net potential of the residues for energy production. Under this background, this study aims to assess the net annual availability of crop residues for energy production by undertaking three different districts with the representation of country’s three major regions of lowland, hill, and mountain. The five major cereal crops of paddy, wheat, maize, millet, and barley are considered for the analysis. The analysis is based upon two modes of household surveys. The first mode of survey is conducted to total of 240 households to obtain key information about crop harvesting and livestock management throughout a year. Similarly, the quantification of main crops along with the respective residues on fixed land is carried out to 45 households during second mode. The range of area of such fixed land is varied from 50 to 100 m2. The measurements have been done in air dry basis. The quantity for competitive uses of respective crop residues is measured on the basis of respondents’ feedback. There are four major competitive uses of crop residues at household which are building material, burning, selling, and livestock fodder. The results reveal that the net annual available crop residues per household are 4663 kg, 2513 kg, and 1731 kg in lowland, hill, and mountain respectively. Of total production of crop residues, the shares of dedicated fodder crop residues (except maize stalk and maize cob) are 94 %, 62 %, and 89 % in lowland, hill, and mountain respectively and of which the corresponding shares of fodder are 87 %, 91 %, and 82 %. The annual percapita energy equivalent from net available crop residues in lowland, hill, and mountain are 2.49 GJ, 3.42 GJ, and 0.44 GJ which represent 30 %, 33 %, and 3 % of total annual energy consumption respectively whereas the corresponding current shares of crop residues are only 23 %, 8 %, and 1 %. Hence, even utmost exploitation of available crop residues can hardly contribute to one third of energy consumption at household level in lowland, and hill whereas this is limited to particularly negligible in mountain. Moreover, further analysis has also been done to evaluate district wise supply-demand context of dedicated fodder crop residues on the basis of presence of livestock. The high deficit of fodder crop residues in hill and mountain is observed where the issue of energy generation from these residues will be ludicrous. As a contrary, the annual production of such residues for livestock fodder in lowland meets annual demand with modest surplus even if entire fodder to be derived from the residues throughout a year and thus there seems to be further potential to utilize the surplus residues for energy generation.

Keywords: crop residues, hill, lowland, mountain

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Authors: Luleka Dlamini, Olivier Crespo, Jos van Dam

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Accurately estimating crop growth and yield is pivotal for timely sustainable agricultural management and ensuring food security. Crop models and remote sensing can complement each other and form a robust analysis tool to improve crop growth and yield estimations when combined. This study thus aims to systematically evaluate how research that exclusively focuses on assimilating RS data into crop models varies among countries, crops, data assimilation methods, and farming conditions. A strict search string was applied in the Scopus and Web of Science databases, and 497 potential publications were obtained. After screening for relevance with predefined inclusion/exclusion criteria, 123 publications were considered in the final review. Results indicate that over 81% of the studies were conducted in countries associated with high socio-economic and technological advancement, mainly China, the United States of America, France, Germany, and Italy. Many of these studies integrated MODIS or Landsat data into WOFOST to improve crop growth and yield estimation of staple crops at the field and regional scales. Most studies use recalibration or updating methods alongside various algorithms to assimilate remotely sensed leaf area index into crop models. However, these methods cannot account for the uncertainties in remote sensing observations and the crop model itself. l. Over 85% of the studies were based on commercial and irrigated farming systems. Despite a great global interest in data assimilation into crop models, limited research has been conducted in resource- and data-limited regions like Africa. We foresee a great potential for such application in those conditions. Hence facilitating and expanding the use of such an approach, from which developing farming communities could benefit.

Keywords: crop models, remote sensing, data assimilation, crop yield estimation

Procedia PDF Downloads 92

Authors: Luleka Dlamini, Olivier Crespo, Jos van Dam

Abstract:

Accurately estimating crop growth and yield is pivotal for timely sustainable agricultural management and ensuring food security. Crop models and remote sensing can complement each other and form a robust analysis tool to improve crop growth and yield estimations when combined. This study thus aims to systematically evaluate how research that exclusively focuses on assimilating RS data into crop models varies among countries, crops, data assimilation methods, and farming conditions. A strict search string was applied in the Scopus and Web of Science databases, and 497 potential publications were obtained. After screening for relevance with predefined inclusion/exclusion criteria, 123 publications were considered in the final review. Results indicate that over 81% of the studies were conducted in countries associated with high socio-economic and technological advancement, mainly China, the United States of America, France, Germany, and Italy. Many of these studies integrated MODIS or Landsat data into WOFOST to improve crop growth and yield estimation of staple crops at the field and regional scales. Most studies use recalibration or updating methods alongside various algorithms to assimilate remotely sensed leaf area index into crop models. However, these methods cannot account for the uncertainties in remote sensing observations and the crop model itself. l. Over 85% of the studies were based on commercial and irrigated farming systems. Despite a great global interest in data assimilation into crop models, limited research has been conducted in resource- and data-limited regions like Africa. We foresee a great potential for such application in those conditions. Hence facilitating and expanding the use of such an approach, from which developing farming communities could benefit.

Keywords: crop models, remote sensing, data assimilation, crop yield estimation

Procedia PDF Downloads 56

Authors: A. L. Qureshi, A. A. Mahessar, R. K. Dashti, S. M. Yasin

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In this paper, effect of marginal quality groundwater on yield of cotton crop and soil salinity was studied. In this connection, three irrigation treatments each with four replications were applied. These treatments were use of canal water, use of marginal quality groundwater from tube well, and conjunctive use by mixing with the ratio of 1:1 of canal water and marginal quality tubewell water. Water was applied to the crop cultivated in Kharif season 2011; its quantity has been measured using cut-throat flume. Total 11 watering each of 50 mm depth have been applied from 20th April to 20th July, 2011. Further, irrigations were stopped from last week of July, 2011 due to monsoon rainfall. Maximum crop yield (seed cotton) was observed under T1 which was 1,516.8 kg/ha followed by T3 (mixed canal and tube well water) having 1009 kg/ha and 709 kg/ha for T2 i.e. marginal quality groundwater. This concludes that crop yield in T2 and T3 with in comparison to T1was reduced by about 53 and 30% respectively. It has been observed that yield of cotton crop is below potential limit for three treatments due to unexpected rainfall at the time of full flowering season; thus the yield was adversely affected. However, salt deposition in soil profiles was not observed that is due to leaching effect of heavy rainfall occurred during monsoon season.

Keywords: conjunctive use, cotton crop, groundwater, soil salinity status, water use efficiency

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Authors: P. S. Akami, H. Nahunnaro, A. Zubainatu

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Cercospora leaf spot (Cercospora sesami. Zimm) has been identified as one of the most prevalent diseases, posing serious constraints to sesame production in producing areas. Two sets of experiments were carried out. The first and second experiments were conducted in the Modibbo Adama University of Technology Yola at the Crop Production and Horticulture and Plant Science Departments, respectively. The field experiment was carried out using a Randomized Complete Block Design and was replicated three times on a plot size of 4m x 5m with four sesame varieties and three Mancob-M fungicide levels (0g, 2g and 4g) to give a total of Twelve treatments. The laboratory experiment involved the isolation of the pathogens from diseased leaves with symptoms of Cercospora leaf spot, which was identified as Cercospora sesami. Data collected were subjected to analysis of variance for a randomized complete block design using SAS (1999) statistical package. The treatment means that are significantly different were separated using the Least Significant Difference at P=0.05. The result revealed that 4g Mancob M recorded the lowest mean value for disease incidence and severity at 8WAS, which was 90.30% and 35.60%, respectively, while the control (0g) recorded the highest mean value for disease incidence and severity at 90.30% and 59.80% respectively. Ex-Sudan recorded the lowest value of 720 kg/ha, while NCRIBEN 03 recorded the highest yield of 834 kg/ha-¹. For the concentrations, 2g recorded a higher yield of 843 kg/ha-¹ followed by 0g, which recorded 765 kg/ha-¹. Conclusively, Cercospora leaf spot of sesame was found to be prevalent. E8 has a higher resistance to the disease, while NCRIBEN 03 tends to be more susceptible. It is therefore recommended that further trials should be carried out using different varieties in different locations.

Keywords: disease, evaluation, prevalence, treatment, resistance

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

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Authors: Mirza Waseem Abbas, Abdul Qayyum, Muhammad Islam

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Climate change has emerged as a significant threat to global food security, affecting crop production systems worldwide. This research paper aims to examine the specific impacts of climate change on wheat production in Pakistan, Punjab in particular, a country highly dependent on wheat as a staple food crop. Through a comprehensive review of scientific literature, field observations, and data analysis, this study assesses the key climatic factors influencing wheat cultivation and the subsequent implications for food security in the region. A comparison of two subsequent Wheat seasons in Punjab was examined through climatic conditions, area, yield, and production data. From the analysis, it is observed that despite a decrease in the area under cultivation in the Punjab during the Wheat 2023 season, the production and average yield increased due to favorable weather conditions. These uncertain climatic conditions have a direct impact on crop yields. Last year due to heat waves, Wheat crop in Punjab suffered a significant loss. Through crop insurance, Wheat growers were provided with yield loss protection keeping in view the devastating heat wave and floods last year. Under crop insurance by the Government of the Punjab, 534,587 Wheat growers were insured with a $1.6 million premium subsidy. However, due to better climatic conditions, no loss in the yield was recorded in the insured areas. Crop Insurance is one of the suitable options for policymakers to protect farmers against climatic losses in the future as well.

Keywords: climate change, crop insurance, heatwave, wheat yield punjab

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Authors: H. Kishor, G. Prabhuling, D. S. Ambika, D. P. Prakash

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The chemical mutagens have become important tool to enhance agronomic traits of banana crop. It is being used to develop fusarium resistance lines in various susceptible banana cultivars. There are several mutagens like EMS and NaN3 available for banana crop improvement and each mutagen has its own important role as positive or negative effects on growth and development of banana plants. Explants from shoot tip culture were treated with various EMS (0.30, 0.60, 0.90 and 0.12%) and NaN3 (0.01, 0.02 and 0.03%) concentrations. The putative mutants obtained after in vitro rooting were subjected for artificial inoculation of Fusarium oxysporum f.sp. cubense. Screening putative mutants resistance to Panama disease was carried out by using syringe method of inoculation. It was observed that, EMS treated mutants were more susceptible compared to NaN3 treatment. Among the NaN3 doses 0.01% found to produce 3 resistant lines during preliminary screening under greenhouse conditions.

Keywords: Nanjangud rasabale, EMS, NaN3, putative mutants

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Authors: Ying Chen

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Conservation Agriculture in a sustainable way of farming, as it brings many benefits, such as preventing soil from erosion and degradation, improving soil health, conserving energy, and sequestrating carbon. However, adoption of conservation agriculture has been progressing slowly in some part of the world due to some challenges. Among them, seeding in heavy crop residue is challenging, especially in corn production systems. Weed control is also challenging in conservation agriculture. This research aimed to investigate some technologies that can address these challenges. For crop residue management, vertical tillage and vertical seeding have been studied in multiple research projects. Results showed that vertical tillage and seeding were able to deal with crop residue through cutting residue into small segments, which would not plug seeder in the sub-sequent seeding. Vertical tillage is a conservation tillage system, as it leaves more than 30% crop residue on soil surface while incorporating some residue into the shallow soil layer for fast residue decomposition. For weed control, mechanical weeding can reduce chemical inputs in crop production. A tine weeder was studied for weed control during the early growing season of several field crops (corn, soybean, flax, and pea). Detail results of these studies will be shared at the conference.

Keywords: tillage, seeding, mechanical weeding, crop residue

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Authors: Necati Içer

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Crop-hail insurance plays a vital role in managing risks and reducing the financial consequences of hail damage on crop production. Predicting insurance premium rates with short-term data is a major difficulty in numerous nations because of the unique characteristics of hailstorms. This study aims to suggest a feasible approach for establishing equitable premium rates in crop-hail insurance for nations with short-term insurance data. The primary goal of the rate-making process is to determine premium rates for high and zero loss costs of villages and enhance their credibility. To do this, a technique was created using the author's practical knowledge of crop-hail insurance. With this approach, the rate-making method was developed using a range of temporal and spatial factor combinations with both hypothetical and real data, including extreme cases. This article aims to show how to incorporate the temporal and spatial elements into determining fair premium rates using short-term insurance data. The article ends with a suggestion on the ultimate premium rates for insurance contracts.

Keywords: crop-hail insurance, premium rate, short-term insurance data, spatial and temporal parameters

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Authors: M. Barsa

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This paper argues that current liberal trade regimes have had the unfortunate effect of concentrating food production by area and by crop. While such hyper-specialization and standardization might be efficient under ordinary climate conditions, the increasing severity of climate shocks makes such a food production system especially vulnerable. Examining domestic US crop production, and the fact that similar patterns are evident worldwide, this paper explores the vulnerabilities of several major crops and suggests that the academic arguments surrounding increasing liberalization of trade are ill-suited to the climate challenges to come. Indeed, a case can be made that protectionist measures—especially by developing countries whose agricultural sectors are vulnerable to the cheap US and European exports—are increasingly necessary to scatter food production geographically and to retain a resilient diversity of crop varieties.

Keywords: climate change, crop resilience, diversity, international trade

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Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad

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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.

Keywords: Landsat NDVI, panel models, temperature, rainfall

Procedia PDF Downloads 176

Authors: S. A. Salau, I. F. Ayanda, I. Afe, M. O. Adesina, N. B. Nofiu

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Food insecurity is still a critical challenge among rural and urban households in Nigeria. The country’s food insecurity situation became more pronounced due to frequent conflict between pastoralist and crop farmers. Thus, this study assesses pastoralist-crop farmers’ conflict and food security of farming households in Kwara state, Nigeria. The specific objectives are to measure the food security status of the respondents, quantify pastoralist- crop farmers’ conflict, determine the effect of pastoralist- crop farmers conflict on food security and describe the effective coping strategies adopted by the respondents to reduce the effect of food insecurity. A combination of purposive and simple random sampling techniques will be used to select 250 farming households for the study. The analytical tools include descriptive statistics, Likert-scale, logistic regression, and food security index. Using the food security index approach, the percentage of households that were food secure and insecure will be known. Pastoralist- crop farmers’ conflict will be measured empirically by quantifying loses due to the conflict. The logistic regression will indicate if pastoralist- crop farmers’ conflict is a critical determinant of food security among farming households in the study area. The coping strategies employed by the respondents in cushioning the effects of food insecurity will also be revealed. Empirical studies on the effect of pastoralist- crop farmers’ conflict on food security are rare in the literature. This study will quantify conflict and reveal the direction as well as the extent of the relationship between conflict and food security. It could contribute to the identification and formulation of strategies for the minimization of conflict among pastoralist and crop farmers in an attempt to reduce food insecurity. Moreover, this study could serve as valuable reference material for future researches and open up new areas for further researches.

Keywords: agriculture, conflict, coping strategies, food security, logistic regression

Procedia PDF Downloads 147

Authors: Catalina Albornoz, Giacomo Barbieri

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Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

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Authors: Jiemiao Chen, Shuoxun Xu

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The main goal of our research is to apply the Vine copula measuring dependency between price, temperature, and precipitation indices to calculate a fair crop insurance premium. This research is focused on Worth, Iowa, United States, over the period from 2000 to 2020, where the farmers are dependent on precipitation and average temperature during the growth period of corn. Our proposed insurance considers both the natural risk and the price risk in agricultural production. We first estimate the distributions of crops using parametric methods based on Goodness of Fit tests, and then Vine Copula is applied to model dependence between yield price, crop yield, and weather indices. Once the vine structure and its parameters are determined based on AIC/BIC criteria and forecasting price and yield are obtained from the ARIMA model, we calculate this crop insurance premium using the simulation data generated from the vine copula by the Monte Carlo Simulation method. It is shown that, compared with traditional crop insurance, our proposed insurance is more fair and thus less costly for the farmers and government.

Keywords: vine copula, weather index, crop insurance premium, insurance risk management, Monte Carlo simulation

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Authors: Rafia Hassan, Ali Rizwan, Sadaf Farhan, Bushra Sabir

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The purpose of this study is to compare the conventional crop monitoring system with the satellite based crop monitoring system in Pakistan. This study is conducted for SUPARCO (Space and Upper Atmosphere Research Commission). The study focused on the wheat crop, as it is the main cash crop of Pakistan and province of Punjab. This study will answer the following: Which system is better in terms of cost, time and man power? The man power calculated for Punjab CRS is: 1,418 personnel and for SUPARCO: 26 personnel. The total cost calculated for SUPARCO is almost 13.35 million and CRS is 47.705 million. The man hours calculated for CRS (Crop Reporting Service) are 1,543,200 hrs (136 days) and man hours for SUPARCO are 8, 320hrs (40 days). It means that SUPARCO workers finish their work 96 days earlier than CRS workers. The results show that the satellite based crop monitoring system is efficient in terms of manpower, cost and time as compared to the conventional system, and also generates early crop forecasts and estimations. The research instruments used included: Interviews, physical visits, group discussions, questionnaires, study of reports and work flows. A total of 93 employees were selected using Yamane’s formula for data collection, which is done with the help questionnaires and interviews. Comparative graphing is used for the analysis of data to formulate the results of the research. The research findings also demonstrate that although conventional methods have a strong impact still in Pakistan (for crop monitoring) but it is the time to bring a change through technology, so that our agriculture will also be developed along modern lines.

Keywords: area frame, crop reporting service, CRS, sample frame, SRS/GIS, satellite remote sensing/ geographic information system

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Authors: Asim Abbasi, Amer Habib, Sajid Hussain, Muhammad Sufyan, Iqra, Hasnain Sajjad

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Except for few scattered cases, powdery mildew disease was not a big problem for watermelon in the past but with the outbreaks of its pathotypes, races 1W and 2W, this disease becomes a serious issue all around the globe. The severe outbreak of this disease also increased the rate of fungicide application for its proper management. Twelve varieties of watermelon were screened in Research Area of Department of Plant pathology, University of Agriculture, Faisalabad to check the incidence of powdery mildew disease. Disease inoculum was prepared and applied with the help of foliar spray method. Fungicides and plants extracts were also applied after the disease incidence. Percentage leaf surface area diseased was assessed visually with a modified Horsfall-Barratt scale. The results of the experiment revealed that among all varieties, WT2257 and Zcugma F1 were highly resistant showing less than 5% disease incidence while Anar Kali and Sugar baby were highly susceptible with disease incidence of more than 65%. Among botanicals neem extract gave best results with disease incidence of less than 20%. Besides neem, all other botanicals also gave significant control of powdery mildew disease than the untreated check. In case of fungicides, Gemstar showed least disease incidence i.e. < 10%, however besides control maximum disease incidence was observed in Curzate (> 30%).

Keywords: botanicals, fungicides, pathotypes, powdery mildew

Procedia PDF Downloads 262

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

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Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

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Authors: Mohsen Rezaei Aghdam

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Recombinant DNA technology has meaningfully augmented the conventional crop improvement and has a great possibility to contribution plant breeders to encounter the augmented food request foretold for the 21st century. Predictable changes in weather and its erraticism, chiefly extreme fevers and vicissitudes in rainfall are expected to brand crop upgrading even more vital for food manufacture. Tissue attitude has been downtrodden to create genetic erraticism from which harvest plants can be better, to improve the state of health of the recognized physical and to upsurge the number of wanted germplasms obtainable to the plant breeder. This appraisal delivers an impression of the chances obtainable by the integration of vegetable biotechnology into plant development efforts and increases some of the social subjects that need to be considered in their application. Public-private companies offer chances to catalyze new approaches and investment while accelerating integrated research and development and commercial supply chain-based solutions. Novel varieties derivative by encouraged mutatgenesis are used commonly: rice in Thailand. These paper combinations obtainable data about the influence of change breeding-derived crop changes around the world, traveler magnetism the possibility of mutation upbringing as a flexible and feasible approach appropriate to any crop if that suitable objectives and selection approaches are used.

Keywords: crop, improve, genetic, agricultural

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Authors: Syed Dawood M. Taimur

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Background: Peripheral arterial disease (PAD) is under diagnosed in primary care practices, yet the extent of unrecognized PAD in patients with coronary artery disease (CAD) is unknown. Objective: To assess the prevalence of previously unrecognized PAD in patients undergoing coronary angiogram and to determine the relationship between the presence of PAD and severity of CAD. Material & Methods: This five years retrospective study was conducted at an invasive lab of the department of Cardiology, Ibrahim Cardiac Hospital & Research Institute from January 2010 to December 2014. Total 77 patients were included in this study. Study variables were age, sex, risk factors like hypertension, diabetes mellitus, dyslipidaemia, smoking habit and positive family history for ischemic heart disease, coronary artery and peripheral artery profile. Results: Mean age was 56.83±13.64 years, Male mean age was 53.98±15.08 years and female mean age was 54.5±1.73years. Hypertension was detected in 55.8%, diabetes in 87%, dyslipidaemia in 81.8%, smoking habits in 79.2% and 58.4% had a positive family history. After catheterization 88.3% had peripheral arterial disease and 71.4% had coronary artery disease. Out of 77 patients, 52 had both coronary and peripheral arterial disease which was statistically significant (p < .014). Coronary angiogram revealed 28.6% (22) patients had triple vessel disease, 23.3% (18) had single vessel disease, 19.5% (15) had double vessel disease and 28.6% (22) were normal coronary arteries. The peripheral angiogram revealed 54.5% had superficial femoral artery disease, 26% had anterior tibial artery disease, 27.3% had posterior tibial artery disease, 20.8% had common iliac artery disease, 15.6% had common femoral artery disease and 2.6% had renal artery disease. Conclusion: There is a strong and definite correlation between coronary and peripheral arterial disease. We found that cardiovascular risk factors were in fact risk factors for both PAD and CAD.

Keywords: coronary artery disease (CAD), peripheral artery disease(PVD), risk, factors, correlation, cathetarization

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Authors: Geeta Sharma, Suma Chandra

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Sugarcane is one of the major commercial crop playing roles in agriculture and industrial economy of India. Globally sugarcane is affected by approximately 240 diseases caused by various plant pathogenic organisms. Among them, red rot disease caused by the fungus Colletotrichum falcatum, is one of the most important diseases. In the present investigation, one fungal bioagent of Trichoderma harzianum, Pant Bioagent 1 and one bacterial bioagent Pseudomonas fluorescence, Pant Bioagent 2 (PBAT 1 and PBAT 2, respectively) were tested by dual culture method against the pathogen under laboratory conditions. The effectiveness of biocontrol agents was observed against four isolates of C. falcatum. In the case of PBAT1 maximum percent inhibition of pathogen was recorded in isolated Cf 0238 (61.05%), followed by Cf 09 (60.62%) whereas, minimum percent inhibition was recorded in Cf 3220 (48.55%) and in case of PBAT2 maximum mycelial growth inhibition percent was recorded in Cf 767 (50.50%) followed by Cf 088230(48.83%), whereas minimum percent inhibition was recorded in Cf 08 (40.16%) followed by Cf 0238 (41.83%). The present study showed that these biocontrol agents have the potential of controlling the pathogen and can further be used for the management of red rot disease in field.

Keywords: biocontrol agents, Colletotrichum falcatum, isolates, sugarcane

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Authors: Xin Wu, Yongfeng Zhao, Qingxiang Meng

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In China, quite low proportion of crop residues were used as feedstuff because of its poor palatability and low digestibility. Steam explosion is a physical and chemical feed processing technology which has great potential to improve sapidity and digestibility of crop residues. To investigate the effect of the steam explosion on chemical compositions and efficient energy values, crop residues (rice straw, wheat straw and maize stover) were processed by steam explosion (steam temperature 120-230°C, steam pressure 2-26kg/cm², 40min). Steam-exploded crop residues were regarded as treatment groups and untreated ones as control groups, nutritive compositions were analyzed and effective energy values were calculated by prediction model in INRA (1988, 2010) for both groups. Results indicated that the interaction between treatment and variety has a significant effect on chemical compositions of crop residues. Steam explosion treatment of crop residues decreased neutral detergent fiber (NDF) significantly (P < 0.01), and compared with untreated material, NDF content of rice straw, wheat straw, and maize stover lowered 21.46%, 32.11%, 28.34% respectively. Acid detergent lignin (ADL) of crop residues increased significantly after the steam explosion (P < 0.05). The content of crude protein (CP), ether extract (EE) and Ash increased significantly after steam explosion (P < 0.05). Moreover, predicted effective energy values of each steam-exploded residue were higher than that of untreated ones. The digestible energy (DE), metabolizable energy (ME), net energy for maintenance (NEm) and net energy for gain (NEg)of steam-exploded rice straw were 3.06, 2.48, 1.48and 0.29 MJ/kg respectively and increased 46.21%, 46.25%, 49.56% and 110.92% compared with untreated ones(P < 0.05). Correspondingly, the energy values of steam-exploded wheat straw were 2.18, 1.76, 1.03 and 0.15 MJ/kg, which were 261.78%, 261.29%, 274.59% and 1014.69% greater than that of wheat straw (P < 0.05). The above predicted energy values of steam exploded maize stover were 5.28, 4.30, 2.67 and 0.82 MJ/kg and raised 109.58%, 107.71%, 122.57% and 332.64% compared with the raw material(P < 0.05). In conclusion, steam explosion treatment could significantly decrease NDF content, increase ADL, CP, EE, Ash content and effective energy values of crop residues. The effect of steam explosion was much more obvious for wheat straw than the other two kinds of residues under the same condition.

Keywords: chemical compositions, crop residues, efficient energy values, steam explosion

Procedia PDF Downloads 222

Authors: Olena Kavats, Dmitry Khramov, Kateryna Sergieieva, Vladimir Vasyliev, Iurii Kavats

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Geoinformation technologies of space agromonitoring are a means of operative decision making support in the tasks of managing the agricultural sector of the economy. Existing technologies use satellite images in the optical range of electromagnetic spectrum. Time series of optical images often contain gaps due to the presence of clouds and haze. A geoinformation technology is created. It allows to fill gaps in time series of optical images (Sentinel-2, Landsat-8, PROBA-V, MODIS) with radar survey data (Sentinel-1) and use information about agrometeorological conditions of the growing season for individual monitoring years. The technology allows to perform crop classification and mapping for spring-summer (winter and spring crops) and autumn-winter (winter crops) periods of vegetation, monitoring the dynamics of crop state seasonal changes, crop yield forecasting. Crop classification is based on supervised classification algorithms, takes into account the peculiarities of crop growth at different vegetation stages (dates of sowing, emergence, active vegetation, and harvesting) and agriculture land state characteristics (row spacing, seedling density, etc.). A catalog of samples of the main agricultural crops (Ukraine) is created and crop spectral signatures are calculated with the preliminary removal of row spacing, cloud cover, and cloud shadows in order to construct time series of crop growth characteristics. The obtained data is used in grain crop growth tracking and in timely detection of growth trends deviations from reference samples of a given crop for a selected date. Statistical models of crop yield forecast are created in the forms of linear and nonlinear interconnections between crop yield indicators and crop state characteristics (temperature, precipitation, vegetation indices, etc.). Predicted values of grain crop yield are evaluated with an accuracy up to 95%. The developed technology was used for agricultural areas monitoring in a number of Great Britain and Ukraine regions using EOS Crop Monitoring Platform (https://crop-monitoring.eos.com). The obtained results allow to conclude that joint use of Sentinel-1 and Sentinel-2 images improve separation of winter crops (rapeseed, wheat, barley) in the early stages of vegetation (October-December). It allows to separate successfully the soybean, corn, and sunflower sowing areas that are quite similar in their spectral characteristics.

Keywords: geoinformation technology, crop classification, crop yield prediction, agricultural monitoring, EOS Crop Monitoring Platform

Procedia PDF Downloads 402

Authors: W. Soufi, F. Boukli Hacene, S. Ghalem

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Alzheimer's disease (AD) is a neurodegenerative disease that leads to a progressive and permanent deterioration of nerve cells. This disease is progressively accompanied by an intellectual deterioration leading to psychological manifestations and behavioral disorders that lead to a loss of autonomy. It is the most frequent of degenerative dementia. Alzheimer's disease (AD), which affects a growing number of people, has become a major public health problem in a few years. In the context of the study of the mechanisms governing the evolution of AD disease, we have found that natural flavonoids are good acetylcholinesterase inhibitors that reduce the rate of ßA secretion in neurons. This work is to study the inhibition of acetylcholinesterase (AChE) which is an enzyme involved in Alzheimer's disease, by methods of molecular modeling. These results will probably help in the development of an effective therapeutic tool in the fight against the development of Alzheimer's disease. Our goal of the research is to study the inhibition of acetylcholinesterase (AChE) by molecular modeling methods.

Keywords: Alzheimer's disease, acetylcholinesterase, flavonoids, molecular modeling

Procedia PDF Downloads 73

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: Deepak Loura

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Production and productivity of several crops in the country continue to be adversely affected by biotic (e.g., Insect-pests and diseases) and abiotic (e.g., water temperature and salinity) stresses. Over-dependence on pesticides and other chemicals is economically non-viable for the resource-poor farmers of our country. Further, pesticides can potentially affect human and environmental safety. While traditional breeding techniques and proper- management strategies continue to play a vital role in crop improvement, we need to judiciously use biotechnology approaches for the development of genetically modified crops addressing critical problems in the improvement of crop plants for sustainable agriculture. Modern biotechnology can help to increase crop production, reduce farming costs, and improve food quality and the safety of the environment. Genetic engineering is a new technology which allows plant breeders to produce plants with new gene combinations by genetic transformation of crop plants for improvement of agronomic traits. Advances in recombinant DNA technology have made it possible to have genes between widely divergent species to develop genetically modified or genetically engineered plants. Plant genetic engineering provides the strength to harness useful genes and alleles from indigenous microorganisms to enrich the gene pool for developing genetically modified (GM) crops that will have inbuilt (inherent) resistance to insect pests, diseases, and abiotic stresses. Plant biotechnology has made significant contributions in the past 20 years in the development of genetically engineered or genetically modified crops with multiple benefits. A variety of traits have been introduced in genetically engineered crops which include (i) herbicide resistance. (ii) pest resistance, (iii) viral resistance, (iv) slow ripening of fruits and vegetables, (v) fungal and bacterial resistance, (vi) abiotic stress tolerance (drought, salinity, temperature, flooding, etc.). (vii) quality improvement (starch, protein, and oil), (viii) value addition (vitamins, micro, and macro elements), (ix) pharmaceutical and therapeutic proteins, and (x) edible vaccines, etc. Multiple genes in transgenic crops can be useful in developing durable disease resistance and a broad insect-control spectrum and could lead to potential cost-saving advantages for farmers. The development of transgenic to produce high-value pharmaceuticals and the edible vaccine is also under progress, which requires much more research and development work before commercially viable products will be available. In addition, molecular-aided selection (MAS) is now routinely used to enhance the speed and precision of plant breeding. Newer technologies need to be developed and deployed for enhancing and sustaining agricultural productivity. There is a need to optimize the use of biotechnology in conjunction with conventional technologies to achieve higher productivity with fewer resources. Therefore, genetic modification/ engineering of crop plants assumes greater importance, which demands the development and adoption of newer technology for the genetic improvement of crops for increasing crop productivity.

Keywords: biotechnology, plant genetic engineering, genetically modified, biotic, abiotic, disease resistance

Procedia PDF Downloads 46

Authors: Dharmendra Pratap

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Large Cardamom (Amomum subulatum), family Zingiberaceae is an aromatic spice crop and has rich medicinal value. Large Cardamom is as synonymous to Sikkim as Tea is to Darjeeling. Since Sikkim alone contributes up to 88% of India's large cardamom production which is the world leader by producing over 50% of the global yield. However, the production of large cardamom has declined almost to half since last two decade. The economic losses have been attributed to two viral diseases namely, chirke and Foorkey. Chirke disease is characterized by light and dark green streaks on leaves. The affected leaves exhibit streak mosaic, which gradually coalesce, turn brown and eventually dry up. Excessive sprouting and formation of bushy dwarf clumps at the base of mother plants that gradually die characterize the foorkey disease. In our surveys in Sikkim–Darjeeling hill area during 2012-14, 40-45% of plants were found to be affected with foorkey disease and 10-15% with chirke. Mechanical and aphid transmission study showed banana as an alternate host for both the disease. For molecular identification, total genomic DNA and RNA was isolated from the infected leaf tissues and subjected to Rolling circle amplification (RCA) and RT-PCR respectively. The DNA concatamers produced in the RCA reaction were monomerized by different restriction enzymes and the bands corresponding to ~1 kb genomes were purified and cloned in the respective sites. The nucleotide sequencing results revealed the association of Nanovirus with the foorkey disease of large cardamom. DNA1 showed 74% identity with Replicase gene of FBNYV, DNA2 showed 77% identity with the NSP gene of BBTV and DNA3 showed 74% identity with CP gene of BBTV. The finding suggests the presence of a new species of nanovirus associated with foorkey disease of large cardamom in Sikkim and Darjeeling hills. The details of their epidemiology and other factors would be discussed.

Keywords: RCA, nanovirus, large cardamom, molecular virology and microbiology

Procedia PDF Downloads 473

Authors: Aschalew Cherie Workneh, K. S. Hari Prasad, Chandra Shekhar Prasad Ojha

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Due to the increase in water scarcity, the crop water stress index (CWSI) is receiving significant attention these days, especially in arid and semiarid regions, for quantifying water stress and effective irrigation scheduling. Nowadays, machine learning techniques such as neural networks are being widely used to determine CWSI. In the present study, the performance of two artificial neural networks, namely, Self-Organizing Maps (SOM) and Feed Forward-Back Propagation Artificial Neural Networks (FF-BP-ANN), are compared while determining the CWSI of rice crop. Irrigation field experiments with varying degrees of irrigation were conducted at the irrigation field laboratory of the Indian Institute of Technology, Roorkee, during the growing season of the rice crop. The CWSI of rice was computed empirically by measuring key meteorological variables (relative humidity, air temperature, wind speed, and canopy temperature) and crop parameters (crop height and root depth). The empirically computed CWSI was compared with SOM and FF-BP-ANN predicted CWSI. The upper and lower CWSI baselines are computed using multiple regression analysis. The regression analysis showed that the lower CWSI baseline for rice is a function of crop height (h), air vapor pressure deficit (AVPD), and wind speed (u), whereas the upper CWSI baseline is a function of crop height (h) and wind speed (u). The performance of SOM and FF-BP-ANN were compared by computing Nash-Sutcliffe efficiency (NSE), index of agreement (d), root mean squared error (RMSE), and coefficient of correlation (R²). It is found that FF-BP-ANN performs better than SOM while predicting the CWSI of rice crops.

Keywords: artificial neural networks; crop water stress index; canopy temperature, prediction capability

Procedia PDF Downloads 82

Authors: Weishou Shen, Chunyan Yang, Zhongliang Li

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The crop climate productivity and the distribution of cropland reflect long-term adaption of agriculture to climate. In order to fully understand the impact of climate change on cropland ecosystem in Tibet, the spatiotemporal changes of crop climate productivity and cropland distribution were analyzed with the help of GIS and RS software. Results indicated that the climate change to the direction of wet and warm in Tibet in the recent 30 years, with a rate of 0.79℃/10 yr and 23.28 mm/10yr respectively. Correspondingly, the climate productivity increased gradually, with a rate of 346.3kg/(hm2•10a), of which, the fastest-growing rate of the crop climate productivity is in Southern Tibet Mountain- plain-valley. During the study period, the total cropland area increased from 32.54 million ha to 37.13 million ha, and cropland has expanded to higher altitude area and northward. Overall, increased cropland area and crop climate productivity due to climate change plays a positive role for agriculture in Tibet.

Keywords: climate change, productivity, cropland area, Tibet plateau

Procedia PDF Downloads 342

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

Procedia PDF Downloads 232