Search results for: crop residues

Authors: Kesavan Markkandan, Ha Young Park, Seung-Il Yoo, Sin-Gi Park, Junhyung Park

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For genetic identification of crop cultivars, insertions/deletions (InDel) markers have been preferred currently because they are easy to use, PCR based, co-dominant and relatively abundant. However, new InDels need to be developed for genetic studies of new varieties due to the difference of allele frequencies in InDels among the population groups. These new varieties are evolved with low levels of genetic diversity in specific genome loci with high recombination rate. In this study, we described soybean barcode system approach based on InDel makers, each of which is specific to a variation block (VB), where the genomes split by all assumed recombination sites. Firstly, VBs in crop cultivars were mined for transferability to VB-specific InDel markers. Secondly, putative InDels in the VB regions were identified for the development of barcode system by analyzing particular cultivar’s whole genome data. Thirdly, common VB-specific InDels from all cultivars were selected by gel electrophoresis, which were converted as 2D barcode types according to comparing amplicon polymorphisms in the five cultivars to the reference cultivar. Finally, the polymorphism of the selected markers was assessed with other cultivars, and the barcode system that allows a clear distinction among those cultivars is described. The same approach can be applicable for other commercial crops. Hence, VB-based genetic identification not only minimize the molecular markers but also useful for assessing cultivars and for marker-assisted breeding in other crop species.

Keywords: variation block, polymorphism, InDel marker, genetic identification

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Asiya Rezzouq, Mehdi El Bouchti, Omar Cherkaoui, Sanaa Majid, Souad Zyade

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In recent years, there has been a steady increase in the exploration of new renewable and non-conventional sources for the production of biodegradable nanomaterials. Nature harbours valuable cellulose-rich materials that have so far been under-exploited and can be used to create cellulose derivatives such as cellulose microfibres (CMFs) and cellulose nanocrystals (CNCs). These unconventional sources have considerable potential as alternatives to conventional sources such as wood and cotton. By using agricultural waste to produce these cellulose derivatives, we are responding to the global call for sustainable solutions to environmental and economic challenges. Responsible management of agricultural waste is increasingly crucial to reducing the environmental consequences of its disposal, including soil and water pollution, while making efficient use of these untapped resources. In this study, the main objective was to extract cellulose nanocrystals (CNC) from melon plant residues using methods that are both efficient and sustainable. To achieve this high-quality extraction, we followed a well-defined protocol involving several key steps: pre-treatment of the residues by grinding, filtration and chemical purification to obtain high-quality (CMF) with a yield of 52% relative to the initial mass of the melon plant residue. Acid hydrolysis was then carried out using phosphoric acid and sulphuric acid to convert (CMF) into cellulose nanocrystals. The extracted cellulose nanocrystals were subjected to in-depth characterization using advanced techniques such as transmission electron microscopy (TEM), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction. The resulting cellulose nanocrystals have exceptional properties, including a large specific surface area, high thermal stability and high mechanical strength, making them suitable for a variety of applications, including as reinforcements for composite materials. In summary, the study highlights the potential for recovering agricultural melon waste to produce high-quality cellulose nanocrystals with promising applications in industry, nanotechnology, and biotechnology, thereby contributing to environmental and economic sustainability.

Keywords: cellulose, melon plant residues, cellulose nanocrystals, properties, applications, composite materials

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: W. A. M. Abdel Kawy, Kh. M. Darwish

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Adequate land use selection is an essential step towards achieving sustainable development. The main object of this study is to develop a new scale for land suitability system, which can be compatible with the local conditions. Furthermore, it aims to adapt the conventional land suitability systems to match the actual environmental status in term of soil types, climate and other conditions to evaluate land suitability for newly reclaimed areas. The new system suggests calculation of land suitability considering 20 factors affecting crop selection grouping into five categories; crop-agronomic, land management, development, environmental conditions and socio – economic status. Each factor is summed by each other to calculate the total points. The highest rating for each factor indicates the highest preference for the evaluated crop. The highest rated crops for each group are those with the highest points for the actual suitability. This study was conducted to assess the application efficiency of the new land suitability scale in recently reclaimed sites in Egypt. Moreover, 35 representative soil profiles were examined, and soil samples were subjected to some physical and chemical analysis. Actual and potential suitabilities were calculated by using the new land suitability scale. Finally, the obtained results confirmed the applicability of a new land suitability system to recommend the most promising crop rotation that can be applied in the study areas. The outputs of this research revealed that the integration of different aspects for modeling and adapting a proposed model provides an effective and flexible technique, which contribute to improve land suitability assessment for several crops to be more accurate and reliable.

Keywords: analytic hierarchy process, land suitability, multi-criteria analysis, new reclaimed areas, soil parameters

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Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: S. K. Kakraliya, H. S. Jat, Manish Kakraliya, P. C. Sharma, M. L. Jat

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The biggest challenge in agriculture is to produce more food for the continually increasing world population with in the limited land and water resources. Serious water deficits and reducing natural resources are some of the major threats to the agricultural sustainability in many regions of South Asia. Food and water security may be gained by bringing improvement in the crop water productivity and the amount produced per unit of water consumed. Improvement in the crop water productivity may be achieved by pursuing alternative modern agronomics approaches, which are more friendly and efficient in utilizing natural resources. Therefore, a research trial on conservation agriculture (CA) and precision water management (PWM) was conducted in 2018-19 at Karnal, India to evaluate the effect on crop productivity and irrigation in sodic soils under rice-wheat (RW) systems of Indo-Gangetic Plains (IGP). Eight scenarios were compared varied in the tillage, crop establishment, residue and irrigarion management i.e., {First four scenarios irrigated with flood irrigation method;Sc1-Conventional tillage (CT) without residue, Sc2-CT with residue, Sc3- Zero tillage (ZT) without residue, Sc4-ZT with residue}, and {last four scenarios irrigated with sub-surface drip irrigation method; Sc5-ZT without residue, Sc6- ZT with residue, Sc7-ZT inclusion legume without residue and Sc8- ZT inclusion legume with residue}. Results revealed that CA-flood irrigation (S3, Sc4) and CA-PWM system (Sc5, Sc6, Sc7 and Sc8) recorded about ~5% and ~15% higher wheat yield, respectively compared to Sc1. Similar, CA-PWM saved ~40% irrigation water compared to Sc1. Rice yield was not different under different scenarios in the first year (kharif 2019) but almost half irrigation water saved under CA-PWM system. Therefore, results of our study on modern agronomic practices including CA and precision water management (subsurface drip irrigation) for RW rotation would be addressed the existing and future challenges in the RW system.

Keywords: Sub-surface drip, Crop residue, Crop yield , Zero tillage

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Ying Liang, Na Li

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Lipo-alkaloid is a kind of C19-norditerpenoid alkaloids existed in Aconitum species, which usually contains an aconitane skeleton and one or two fatty acid residues. The structures are very similar to that of diester-type alkaloids, which are considered as the main bioactive components in Aconitum carmichaelii. They have anti-inflammatory, anti-nociceptive, and anti-proliferative activities. So far, more than 200 lipo-alkaloids were reported from plants, semisynthesis, and biotransformations. In our research, by the combination of ultra-high performance liquid chromatography-quadruple-time of flight mass spectrometry (UHPLC-Q-TOF-MS) and an in-house database, 148 lipo-alkaloids were identified from A. carmichaelii, including 93 potential new compounds and 38 compounds with oxygenated fatty acid moieties. To our knowledge, this is the first time of the reporting of the oxygenated fatty acids as the side chains in naturally-occurring lipo-alkaloids. Considering the fatty acid residues in lipo-alkaloids should come from the free acids in the plant, the fatty acids and their relationship with lipo-alkaloids were further investigated by GC-MS and LC-MS. Among 17 fatty acids identified by GC-MS, 12 were detected as the side chains of lipo-alkaloids, which accounted for about 1/3 of total lipo-alkaloids, while these fatty acid residues were less than 1/4 of total fatty acid residues. And, total of 37 fatty acids were determined by UHPCL-Q-TOF-MS, including 18 oxidized fatty acids firstly identified from A. carmichaelii. These fatty acids were observed as the side chains of lipo-alkaloids. In addition, although over 140 lipo-alkaloids were identified, six lipo-alkaloids, 8-O-linoleoyl-14-benzoylmesaconine (1), 8-O-linoleoyl-14-benzoylaconine (2), 8-O-palmitoyl-14-benzoylmesaconine (3), 8-O-oleoyl-14-benzoylmesaconine (4), 8-O-pal-benzoylaconine (5), and 8-O-ole-Benzoylaconine (6), were found to be the main components, which accounted for over 90% content of total lipo-alkaloids. Therefore, using these six components as standards, a UHPLC-Triple Quadrupole-MS (UHPLC-QQQ-MS) approach was established to investigate the influence of processing on the contents of lipo-alkaloids. Although it was commonly supposed that the contents of lipo-alkaloids increased after processing, our research showed that no significant change was observed before and after processing. Using the same methods, the lipo-alkaloids in the lateral roots of A. carmichaelii and the roots of A. kusnezoffii were determined and quantified. The contents of lipo-alkaloids in A. kusnezoffii were close to that of the parent roots of A. carmichaelii, while the lateral roots had less lipo-alkaloids than the parent roots. This work was supported by Macao Science and Technology Development Fund (086/2013/A3 and 003/2016/A1).

Keywords: Aconitum carmichaelii, fatty acids, GC-MS, LC-MS, lipo-alkaloids

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Authors: Pratap Sing, Chaman. K. Jadon, H. P. Meena, D. L.yadav, S. L. Yadav, Uditi Dhakad

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The experiment was conducted at Agricultural Research Station, Agriculture University, Kota, Rajasthan, India during kharif and rabi 2020-21 and 2021-22 to study the biofficacy of diclosulam and its residual effect on succeeding wheat crop. The treatments comprised of Diclosulam 84 % WDG viz. 6.25, 12.50, 25.00 and 37.50 g/ha as pre emergence (PE), Pendimethalin 30% EC 3.33 l/ha, Sulfentrazon 48% SC 750 g/ha, hand weeding at 30 and 45 DAS and weedy check, were evaluated in randomized block design in three replications. The experimental soil was clay in texture and non-calcareous. Experimental field was mainly dominated by grasses-Echinochloa colonum, E.crusgalli,Cynodon dactylon, Sedges-Cyperus rotundus and broad leaved weeds Celosia argentea and Digera arvensis.The result revealed that application of Diclosulam 84 % WDG 25 g/ha PE was found effective in controlling mostly weed species and registered higher weed control efficiency 81.2, 74.3, 69.6 per cent at 30, 45 days after sowing and at harvest. Diclosulam 84 % WDG (6.25-25.0 g/ha) was found selective to the soybean crop as no any phytotoxicity symptoms were observed. Among the herbicidal treatments, Diclosulam 84 % WDG 25 g/ha registered maximum and significantly higher soybean seed yield (1889 and 1431 kg/ha during kharif 2020 and 2021, respectively and was at par with Sulfentrazone 48% SC 750 g/ha and over weedy check( 1027 and 667 kg/ha).The wheat crop growth, yield attributes and seed yield were not influenced due to carry over effect of the Diclosulam 84 % WDG( 6.25-25.0 g/ha) and no any phytotoxicity symptoms were observed. Henceforth, the Diclosulam 84 % WDG 25.0 g/ha as pre emergence may be used in the soybean for effective weed control without carry over effect on succeeding wheat crop.

Keywords: Diclosulam, soybean, carry over effect, succeeding wheat

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Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

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Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

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Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

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Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

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Authors: Srinivasa Reddy Mallampati, Chi-Hyeon Lee, Nguyen Thi Thanh Truc, Byeong-Kyu Lee

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In the present study, feasibility of the selective surface hydrophilization of polyvinyl chloride (PVC) by microwave treatment was evaluated to facilitate the separation from automotive shredder residue (ASR), by the froth flotation. The combination of 60 sec microwave treatment with PAC, a sharp and significant decrease about 16.5° contact angle of PVC was observed in ASR plastic compared with other plastics. The microwave treatment with the addition of PAC resulted in a synergetic effect for the froth flotation, which may be a result of the 90% selective separation of PVC from ASR plastics, with 82% purity. While, simple mixing with a nanometallic Ca/CaO/PO4 dispersion mixture immobilized 95-100% of heavy metals in ASR soil/residues. The quantity of heavy metals leached from thermal residues after treatment by nanometallic Ca/CaO/PO4 was lower than the Korean standard regulatory limit for hazardous waste landfills. Microwave treatment can be a simple and effective method for PVC separation from ASR plastics.

Keywords: automotive shredder residue, chlorinated plastics, hazardous waste, heavy metals, immobilization, separation

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: Suprehatin Suprehatin

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Improving the participation of smallholder farmers in horticultural value chains to benefit from the rapidly growing demand for high-value agricultural products is one strategy for raising farm income. However, smallholder farmer participation in Indonesian horticultural value chains is under-researched. To address this knowledge gap, this study aims to describe the current status of horticultural crop adoption in Indonesia and analyze the motivations and dynamics of smallholder farmer participation in horticultural value chains: why some small farmers join these new and potentially profitable chains and continue their participation. This study also examines the characteristics of farmers who adopted and those who did not adopt a new horticultural crop with respect to the household (farmer), farm and institutional characteristics. The analysis was conducted using unique data from a 2013 survey of 960 Indonesian farmers on Java Island that produce a variety of agricultural products. Basic statistical analysis showed relatively low adoption rates (10%) of new horticultural crops amongst 960 selected Indonesian farmers with different decisions made in terms of number and timing of new horticultural crop adoption. Adopters were motivated mainly by higher profit, higher yield, and more cash opportunities. The result also showed that current low rates of horticultural crop adoption are associated with a variety of factors, such as lower levels of education among farmers, resource constraints, lack of information on horticultural crop production and low participation in farmer groups. These findings will be helpful for policymakers when designing policies and programs to promote greater participation of Indonesian smallholder farmers in horticultural value chains. In other words, a revitalisation of agricultural policy beyond staple food is important to seize potential benefits from the ongoing agricultural food market transformation.

Keywords: farmer adoption, high value, horticultural crops, Indonesia

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Authors: Nayara Torres B. Acioli, José Fernando T. Jucá

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The uncontrolled emission of gases in urban residues' embankment located near urban areas is a social and environmental problem, common in Brazilian cities. Several environmental impacts in the local and global scope may be generated by atmospheric air contamination by the biogas resulted from the decomposition of solid urban materials. In Brazil, the cities of small size figure mostly with 90% of all cities, with the population smaller than 50,000 inhabitants, according to the 2011 IBGE' census, most of the landfill covering layer is composed of clayey, pure soil. The embankments undertaken with pure soil may reach up to 60% of retention of methane, for the other 40% it may be dispersed into the atmosphere. In face of this figures the oxidative covering layer is granted some space of study, envisaging to reduce this perceptual available in the atmosphere, releasing, in spite of methane, carbonic gas which is almost 20 times as less polluting than Methane. This paper exposes the results of studies on the characteristics of the soil used for the oxidative coverage layer of the experimental embankment of Solid Urban Residues (SUR), built in Muribeca-PE, Brazil, supported of the Group of Solid Residues (GSR), located at Federal University of Pernambuco, through laboratory vacuum experiments (determining the characteristics curve), granularity, and permeability, that in soil with saturation over 85% offers dramatic drops in the test of permeability to the air, by little increments of water, based in the existing Brazilian norm for this procedure. The suction was studied, as in the other tests, from the division of prospection of an oxidative coverage layer of 60cm, in the upper half (0.1 m to 0.3 m) and lower half (0.4 m to 0.6 m). Therefore, the consequences to be presented from the lixiviation of the fine materials after 5 years of finalization of the embankment, what made its permeability increase. Concerning its humidity, it is most retained in the upper part, that comprises the compound, with a difference in the order of 8 percent the superior half to inferior half, retaining the least suction from the surface. These results reveal the efficiency of the oxidative coverage layer in retaining the rain water, it has a lower cost when compared to the other types of layer, offering larger availability of this layer as an alternative for a solution for the appropriate disposal of residues.

Keywords: oxidative coverage layer, permeability, suction, saturation

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Authors: C. Girometta, S. Babbini, R. M. Baiguera, D. S. Branciforti, M. Cartabia, D. Dondi, M. Pellegrini, A. M. Picco, E. Savino

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Interest on wood decay fungi (WDF) has been increasing in the last year's thanks to the potentiality of this kind of fungi; research on new WDF strains has increased as well thus pointing out the key role of the culture collections. One of the most recent biotechnological application of WDF is the development of novel materials from natural or recycled resources. Based on different combinations of fungal species, substrate, and processing treatment involved (e.g. heat pressing), it is possible to achieve a wide variety of materials with different features useful for many industrial applications: from packaging to thermal and acoustic insulation. In comparison with the conventional ones, these materials represent a 100% natural and compostable alternative involving low amounts of energy in the production process. The purpose of the present work was to isolate and select WDF strains able to colonize and degrade different plant wastes thus producing a fungal biomass shapeable to achieve bio-composite materials. Strains were selected within the mycological culture collection of Pavia University (MicUNIPV, over 300 strains of WDF). The selected strains have been investigated with regards their ability to colonize and degrade plant residues from the local major cultivations (e.g. poplar, alfalfa, maize, rice, and wheat) and produce the fungal biomass. The degradation of the substrate was assessed by Thermogravimetric analysis (TGA) and Fourier Transform Infrared Spectroscopy (FTIR). Chemical characterization confirmed that TGA and FTIR are complementary techniques able to provide quality-quantitative information on compositional and structural variation that occurs during the transformation from the substrate to the bio-composite material. This pilot study provides a fundamental step to tune further applications in fungus-residues composite biomaterials.

Keywords: bio-composite material, lignocellulosic residues, sustainable materials, wood decay fungi

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Authors: G. Disciglio, G. Gatta, F. Lops, A. Libutti, A. Tarantino, E. Tarantino

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The experimental trial was carried out in open field at Foggia district (Apulia Region, Southern Italy), during the spring-summer season 2014, in order to evaluate the effect of four biostimulant products (RadiconÒ, Viormon plusÒ, LysodinÒ and SiaptonÒ 10L), compared with a control (no biostimulant), on the infestation of processing tomato crop (cv Dres) by the chlorophyll-lacking root parasite Phelipanche ramosa. Biostimulants consist in different categories of products (microbial inoculants, humic and fulvic acids, hydrolyzed proteins and aminoacids, seaweed extracts) which play various roles in plant growing, including the improvement of crop resistance and quali-quantitative characteristics of yield. The experimental trial was arranged according to a complete randomized block design with five treatments, each of one replicated three times. The processing tomato seedlings were transplanted on 5 May 2014. Throughout the crop cycle, P. ramosa infestation was assessed according to the number of emerged shoots (branched plants) counted in each plot, at 66, 78 and 92 day after transplanting. The tomato fruits were harvested at full-stage of maturity on 8 August 2014. From each plot, the marketable yield was measured and the quali-quantitative yield parameters (mean weight, dry matter content, colour coordinate, colour index and soluble solids content of the fruits) were determined. The whole dataset was tested according to the basic assumptions for the analysis of variance (ANOVA) and the differences between the means were determined using Tukey’s tests at the 5% probability level. The results of the study showed that none of the applied biostimulants provided a whole control of Phelipanche, although some positive effects were obtained from their application. To this respect, the RadiconÒ appeared to be the most effective in reducing the infestation of this root-parasite in tomato crop. This treatment also gave the higher tomato yield.

Keywords: biostimulant, control methods, Phelipanche ramosa, tomato crop

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: Samita Sondhi, Sachin Kumar, Chirag Chopra

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The increase in population has resulted in an excessive feedstock production, which has in return lead to the accumulation of a large amount of waste from different resources as crop residues, industrial waste and solid municipal waste. This situation has raised the problem of waste disposal in present days. A parallel problem of depletion of natural fossil fuel resources has led to the formation of alternative sources of energy from the waste of different industries to concurrently resolve the two issues. The biogas is a carbon neutral fuel which has applications in transportation, heating and power generation. India is a nation that has an agriculture-based economy and agro-residues are a significant source of organic waste. Taking into account, the second largest agro-based industry that is sugarcane industry producing a high quantity of sugar and sugarcane waste byproducts such as Bagasse, Press Mud, Vinasse and Wastewater. Currently, there are not such efficient disposal methods adopted at large scales. According to manageability objectives, anaerobic digestion can be considered as a method to treat organic wastes. Press mud is lignocellulosic biomass and cannot be accumulated for Mono digestion because of its complexity. Prior investigations indicated that it has a potential for production of biogas. But because of its biological and elemental complexity, Mono-digestion was not successful. Due to the imbalance in the C/N ratio and presence of wax in it can be utilized with any other fibrous material hence will be digested properly under suitable conditions. In the first batch of Mono-digestion of Pressmud biogas production was low. Now, co-digestion of Pressmud with Bagasse which has desired C/N ratio will be performed to optimize the ratio for maximum biogas from Press mud. In addition, with respect to supportability, the main considerations are the monetary estimation of item result and ecological concerns. The work is designed in such a way that the waste from the sugar industry will be digested for maximum biogas generation and digestive after digestion will be characterized for its use as a bio-fertilizer for soil conditioning. Due to effectiveness demonstrated by studied setups of Mono-digestion and Co-digestion, this approach can be considered as a viable alternative for lignocellulosic waste disposal and in agricultural applications. Biogas produced from the Pressmud either can be used for Powerhouses or transportation. In addition, the work initiated towards the development of waste disposal for energy production will demonstrate balanced economy sustainability of the process development.

Keywords: anaerobic digestion, carbon neutral fuel, press mud, lignocellulosic biomass

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Authors: Kedibone Masenya, Memory Tekere, Jasper Rees

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Sorghum is an important cereal crop in the world. In particular, it has attracted breeders due to capacity to serve as food, feed, fiber and bioenergy crop. Like any other plant, sorghum hosts a variety of microbes, which can either, have a neutral, negative and positive influence on the plant. In the current study, regions (V3/V4) of 16 S rRNA were targeted to extensively assess bacterial multitrophic interactions in the phyllosphere of sorghum. The results demonstrated that the presence of a pathogen has a significant effect on the endophytic bacterial community. Understanding these interactions is key to develop new strategies for plant protection.

Keywords: bacteria, multitrophic, sorghum, target sequencing

Procedia PDF Downloads 254

Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 95

Authors: Binod Shrestha, Sandrine Hoppe, Thierry Ghislain, Phillipe Marchal, Nicolas Brosse, Anthony Dufour

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The thermochemical conversion of lignin has received an increasing interest in the frame of different biorefinery concepts for the production of chemicals or energy. It is needed to better understand the physical and chemical conversion of lignin for feeder and reactor designs. In-situ rheology reveals the viscoelastic behaviour of lignin upon thermal conversion. The softening, re-solidification (char formation), swelling and shrinking behaviours are quantified during pyrolysis in real-time [1]. The in-situ rheology of an alkali lignin (Protobind 1000) was conducted in high torque controlled strain rheometer from 35°C to 400°C with a heating rate of 5°C.min-1. The swelling, through glass phase transition overlapped with depolymerization, and solidification (crosslinking and “char” formation) are two main phenomena observed during lignin pyrolysis. The onset of temperatures for softening and solidification for this lignin has been found to be 141°C and 248°C respectively. An ex-situ characterization of lignin/char residues obtained at different temperatures after quenching in the rheometer gives a clear understanding of the pathway of lignin degradation. The lignin residues were sampled from the mid-point temperatures of the softening range and solidification range to study the chemical transformations undergoing. Elemental analysis, FTIR and solid state NMR were conducted after quenching the solid residues (lignin/char). The quenched solid was also extracted by suitable solvent and followed by acetylation and GPC-UV analysis. The combination of 13C NMR and GPC-UV reveals the depolymerization followed by crosslinking of lignin/char. NMR and FTIR provide the evolution of functional moieties upon temperature. Physical and chemical mechanisms occurring during lignin pyrolysis are accounted in this study. Thanks to all these complementary methods.

Keywords: pyrolysis, bio-chemicals, valorization, mechanism, softening, solidification, cross linking, rheology, spectroscopic methods

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Authors: Ali Bolat, Ali Bayat, Mustafa Gullu

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Maize can be cultivated both under main and second crop conditions in Turkey. Main pests of maize under second crop conditions are Sesamia nonagrioides Lefebvre (Lepidoptera: Noctuidae) and Ostrinia nubilalis Hübner (Lepidoptera: Crambidae). Aerial spraying applications to control these two main maize pests can be carried out until 2006 in Turkey before it was banned due to environmental concerns like drifting of sprayed pestisides and low biological efficiency. In this context, pulverizers which can spray tall maize plants ( > 175 cm) from the ground have begun to be used. However, the biological efficiency of these sprayers is unknown. Some methods have been tested to increase the success of ground spraying in field experiments conducted in second crop maize in 2008 and 2009. For this aim, 6 spraying methods (air assisted spraying with TX cone jet, domestic cone nozzles, twinjet nozzles, air induction nozzles, standard domestic cone nozzles and tail booms) were used at two application rates (150 and 300 l.ha-1) by a sprayer. In the study, biological efficacy evaluations of each methods were measured in each parcel. Biological efficacy evaluations included counts of number of insect damaged plants, number of holes in stems and live larvae and pupa in stems of selected plants. As a result, the highest biological efficacy value (close to 70%) was obtained from Air Assisted Spraying method at 300 l / ha application volume.

Keywords: air assisted sprayer, drift nozzles, biological efficiency, maize plant

Procedia PDF Downloads 182

Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Michal Štros, Eva Polanská, Šárka Pospíšilová

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HMGB1 is an architectural protein in chromatin, acting also as a signaling molecule outside the cell. Recent reports from several laboratories provided evidence that a number of both the intracellular and extracellular functions of HMGB1 may depend on redox-sensitive cysteine residues of the protein. MALDI-TOF analysis revealed that mild oxidization of HMGB1 resulted in a conformational change of the protein due to formation of an intramolecular disulphide bond by opposing Cys23 and Cys45 residues. We have demonstrated that redox state of HMGB1 could significantly modulate the ability of the protein to bind and bend DNA. We have also shown that reduced HMGB1 could easily displace histone H1 from DNA, while oxidized HMGB1 had limited capacity for H1 displacement. Using microscale thermophoresis (MST) we have further studied mechanism of HMGB1 interaction with histone H1 in free solution or when histone H1 was bound to DNA. Our MST analysis indicated that reduced HMGB1 exhibited in free solution > 1000 higher affinity of for H1 (KD ~ 4.5 nM) than oxidized HMGB1 (KD <10 M). Finally, we present a novel mechanism for the HMGB1-mediated modulation of histone H1 binding to DNA.

Keywords: HMGB1, histone H1, redox state, interaction, cross-linking, DNA bending, DNA end-joining, microscale thermophoresis

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Authors: Rabin Paudel, Dambar Bahadur Mahato, Prabin Poudel, Bijaya Neupane, Sakar Jha

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Understanding Human-Elephant Conflict (HEC) is very important in countries like Nepal, where solutions to escalating conflicts are urgently required. However, most of the HEC mitigation measures implemented so far have been done on an ad hoc basis without the detailed understanding of nature and extent of the damage. This study aims to assess the current scenario of HEC in regards to crop and property damages by Wild Asian Elephant and people’s perception towards existing mitigating measures and elephant conservation in Buffer zone area of Bardia National Park. The methods used were a questionnaire survey (N= 178), key-informant interview (N= 18) and focal group discussions (N= 6). Descriptive statistics were used to determine the nature and extent of damage and to understand people’s perception towards HEC, its mitigation measures and elephant conservation. Chi-square test was applied to determine the significance of crop and property damages with respect to distance from the park boundary. Out of all types of damage, crop damage was found to be the highest (51%), followed by house damage (31%) and damage to stored grains (18%) with winter being the season with the greatest elephant damage. Among 178 respondents, the majority of them (82%) were positive towards elephant conservation despite the increment in HEC incidents as perceived by 88% of total respondents. Among the mitigation measures present, the most applied was electric fence (91%) followed by barbed wire fence (5%), reinforced concrete cement wall (3%) and gabion wall (1%). Most effective mitigation measures were reinforced concrete cement wall and gabion wall. To combat increasing crop damage, the insurance policy should be initiated. The efficiency of the mitigation measures should be timely monitored, and corrective measures should be applied as per the need.

Keywords: crop and property damage, elephant conflict, Asiatic wild elephant, mitigation measures

Procedia PDF Downloads 119

Authors: Xuewen Chen, Aizhen Liang, Xiaoping Zhang

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To better understand the spatial variability of soil penetration resistance (SPR) and soil water content (SWC) induced by different tillage and crop rotation in a Mollisol of Northeast China, the soil was sampled from the tillage experiment which was established in Dehui County, Jilin Province, Northeast China, in 2001. Effect of no-tillage (NT), moldboard plow (MP) and ridge tillage (RT) under corn-soybean rotation (C-S) and continuous corn (C-C) system on SPR and SWC were compared with horizontal and vertical variations. The results showed that SPR and SWC spatially varied across the ridge. SPR in the rows was higher than inter-rows, especially in topsoil (2.5-15 cm) of NT and RT plots. SPR of MP changed in the trend with the curve-shaped ridge. In contrast to MP, NT, and RT resulted in average increment of 166.3% and 152.3% at a depth of 2.5-17.5 cm in the row positions, respectively. The mean SPR in topsoil in the rows means soil compaction is not the main factor limiting plant growth and crop yield. SPR in the row of RT soil was lower than NT at a depth of 2.5-12.5 cm. The SWC in NT and RT soil was highest in the inter-rows and least in the rows or shoulders, respectively. However, the lateral variation trend of MP was opposite to NT. From the profile view of SWC, MP was greater than NT and RT in 0-20 cm of the rows. SWC in RT soil was higher than NT in the row of 0-20 cm. Crop rotation did not have a marked impact on SPR and SWC. In addition to the tillage practices, the factor which affects SPR greatly was depth but not position. These two factors have significant effects on SWC. These results indicated that the adoption of RT was a more suitable conservation tillage practices than NT in the black soil of Northeast China.

Keywords: row, soil penetration resistance, spatial variability, tillage practice

Procedia PDF Downloads 104

Authors: Meysam Abedinpour

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Water limitation is the main challenge for crop production in a semi-arid environment. Deficit irrigation is a strategy that allows a crop to sustain some degree of water deficit in order to reduce costs and potentially increase income. For this goal, a field experimental carried out at Asrieh fields of Gorgan city in the north of Iran, during summer season 2011. The treatments imposed were different irrigation water regimes (i.e. W1:70, W2:80, W3:90, and W4:100) percent of field capacity (FC). The results showed that there was Significant difference between the yield and (WUE) under different levels of irrigation, excepting of soil moisture content at field capacity (W4) and 90% of field capacity (W3) on yield and water use efficiency (WUE). The seasonal irrigation water applied were (i.e. 375, 338, 300, and 263 mm ha-1) under different irrigation water treatments (100, 90, 80, 80 and 70%) of FC, respectively. Grain yield productions under treatments were 4180, 3955, 3640, and 3355 (kg ha-1) respectively. Furthermore, the results showed that water use efficiency (WUE) at different treatments were 7.67, 7.79, 7.74, and 7.75 Kg mm ha-1 for (100, 90, 80, and 70) per cent of field capacity, therefore the 90 % of FC treatment (W3) is recommended for Soybean irrigation for water saving. Furthermore, the result showed that the treatment of 90 % of filed capacity (W3) seemed to be better adapted to product a high crop yield with acceptable yield coupling with water use efficiency in Golestan province.

Keywords: deficit irrigation, water use efficiency, yield, soybean

Procedia PDF Downloads 438

Authors: Saeed Yazdani, Shahrbanoo Bagheri, Sepideh Nikravesh

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Considering the importance and scarcity of water resources, the efficient management of water resources is of great importance. Adoption of modern irrigation technology is considered to be a key of increasing the efficiency of water used in agriculture. Policy makers have implemented several ways to induce the adoption of new irrigation technology. The empirical studies show that farmers are reluctant to utilize the use of new irrigation methods. This study aims to assess factors affecting on farmer’s decision on the application of water saving technologies with emphasize on crop price variation and water sources. A Logit model was employed to examine the impact of different variables on use of water saving technology. The required data gathered from a sample of 204 farmers in the year 2012. The results indicate that different variables such as crop price variability, water supply source, high-value crops, farm size, income, education, membership in cooperatives have a positive effect and variables such as age and number of plots have a negative impact on the probability of adopting modern water saving technologies.

Keywords: irrigation, water, water saving technology, scarcity

Procedia PDF Downloads 196