The adoption of computer vision techniques for disease detection is crucial, benefiting both technological advancement and the agricultural sector. Plant diseases and pest infestations significantly reduce crop yield and quality. The unpredictability of seasonal weather patterns, particularly due to frequent weather depressions, further complicates the farmer's ability to sustain the plant's growth and achieve optimal yield. For short-duration crops, timely monitoring of diseases is essential for effective crop management. Early and accurate disease detection reduces excessive pesticide use, thereby preserving soil fertility. This study contributes to the development of YolovAM, a custom object detection model designed to predict and identify leaf miner and pest infestation in Mangalore cucumber and Wax gourd. This is commonly caused by Liriomyza sativae, various beetle species, including cucumber beetles and red pumpkin beetles. The study was conducted using a dataset comprising 1670 images and nearly 10,230 granular annotations of Wax gourd and Mangalore cucumber plants. The dataset captured at various stages of leaf miner and pest infestation, ranging from early to advanced phases, across diverse farm conditions. The dataset presents a high level of complexity due to background noise, including soil, shadows, weeds, partially visible diseased leaf portions, and human interference. These factors pose significant challenges for conventional Yolo models in accurately detecting diseased areas, and YolovAM directly targets this problem. Experimental results indicate that YolovAM outperforms other object detection models by achieving 0.92 accuracy, 0.97 recall, 0.95 F1 score, and a mAP of 0.95.
P. V. D. N. N. T. Kumarasena, W. H. Dinesha Udayangani Pushpakumari, Jayathunga Arachchige Surani Chathurika
et al.
Optimizing light conditions has become crucial for enhancing crop yield, especially in controlled environments like vertical farming. Lettuce (Lactuca sativa L.), highly responsive to light variations, presents an ideal model for studying the influence of light quality on growth. Main objective was to evaluate the effects of light quality on the vegetative growth and yield of two lettuce varieties, ‘Green Coral’ and ‘Red Coral,’ in a home-based vertical drip fertigation system. Completely Randomized Design (CRD) was applied with five replicates and three treatments of T1: Control (no artificial light), T2: two horizontally arranged full spectrum LED light strips, and T3: three horizontally arranged full spectrum LED light strips. Number of leaves (NL), plant height (PH), and fresh weight (FW) were recorded across two growing seasons. Statistical analysis was conducted in one-way ANOVA and Tukey's test revealed that T2 significantly increased NL and PH in both varieties compared to T1 (P<0.05). The variety ‘Green Coral’ showed a significant increase in PH (6.7±0.72 cm) under T2. Wet weight was also significantly higher in T2 for both varieties, with 'Green Coral' yielding 6.2±0.54 g and 'Red Coral' 6.6±0.38 g. These results reported the positive impact of light quality on vegetative growth, suggesting the potential for improved yield in vertical farming.
Active carbons obtained from various carbon-containing materials are highly porous carbon adsorbents with a developed internal surface. Particular attention should be paid to large-tonnage waste from the wood-chemical industry and agriculture, as well as wood processing. Such waste includes charcoal, lignin, sawdust and chips, pieces of bark, straw and husks from the processing of finished products, nut shells, fruit pits, and leaves of fruit trees. The porous substance obtained from wood raw materials has a high adsorption capacity, as well as a large specific surface area. In the course of the deep processing of brown algae at the Arkhangelsk Seaweed Factory, a large amount of organic waste is generated. The aim of the work has been to obtain active carbons from alginate waste consisting of 70 % wood flour. For this purpose, the method of thermochemical activation with sodium hydroxide as an activating agent has been used. The initial raw material has had a moisture content of 76 % and a diverse composition of mineral and organic substances. The research has been carried out as a planned experiment. The design chosen has been a 2nd-order central composite rotatable one for 3 factors. The independent variables have been the sodium hydroxide dosage, pyrolisis temperature and its duration. Based on the results of the study, the optimal values of these factors for obtaining active carbons from algal waste have been determined, as well as the optimal parameters affecting the sorption capacity and porous structure of active carbons. The work is of practical importance, since active carbon in powder and granular forms is actively used in various industries, including pharmaceutical, food, distillery, gas purification, wastewater treatment, biomedicine, and can also be used in agriculture as agricultural sorbents and soil improvement components. Based on the results of the research, it can be concluded that the use of organic waste as a raw material for the synthesis of active carbon by thermochemical activation with sodium hydroxide is of great interest.
[Objective] The relationship between farming and herding households’ livelihood capital and livelihood strategies was studied, and the spatial differences of farming and herding households’ livelihood capital and the transformation between livelihood strategies were analyzed in order to provide a theoretical basis for reducing farming and herding households’ livelihood vulnerability and ultimately achieving sustainable development. [Methods] Starting from the theoretical framework of sustainable livelihood analysis, a household questionnaire survey was used to analyze the key factors of livelihood capital and livelihood strategy transformation for farming and herding households in the national sandy land enclosed reserves in Maqu, Minqin, Shandan County, and Liangzhou District in Gansu Province, which were approved to be established in 2017, by combining a Logistic regression model and one-way analysis of variance (ANOVA). [Results] Financial capital was the most abundant form of livelihood capital, while natural capital was the least abundant form of livelihood capital for the farmers and herdsmen in the enclosed reserves of desertified land. There were significant differences in the distribution of livelihood capital among farmers and herdsmen with different livelihood strategies, and the livelihood capital of non-agricultural farmers and herdsmen was better than that of purely farming households. Cultivated (or grassland) area, cultivated (or grassland) quality, and production tools had significant positive effects on the choice of purely farming households. The size of the family labor force, the education level and the total household income had a significant negative impact on the choice of purely farming livelihood strategy. [Conclusion] The following countermesures should be promoted in the future. Those are increasing the publicity of ecological environmental protection in enclosed protected areas, strengthening the awareness of ecological protection among farmers and herdsmen, accelerating the development of agricultural mechanization, and encouraging the transformation of the remaining labor force to non-agricultural industries, thereby achieving diversification of livelihoods.
Environmental sciences, General. Including nature conservation, geographical distribution
Introduction
The market and the conditions governing it, especially the food industry, are always important issues for policymakers, decision makers and planners in the public and private sectors. Because market conditions are important in terms of the level of competition or monopoly on access to goods from the point of view of government decision-makers and the price from the point of view of production and private sector suppliers. In addition, both access and price factors greatly impact the amount of consumption and, consequently, the level of consumer’s welfare. Dairy products, especially milk and cheese, from the consumer's point of view, in addition to being good for health, from the point of view of agricultural producers, it is a strategic product, and from the point of view of government decision-makers, it is a factor in changing the level of social welfare. Of course, the market behavior has an important effect on the price and the motivation to produce and finally consume milk and cheese. However, factors such as encouraging consumption through public advertising can have a great effect on consumption motivation (Shahbazi, 2015). But the lack of competitive conditions in the production of products can reduce the consumption of milk and cheese and, as a result, create lost welfare for consumers and society. In other words, having a large share of the milk market by a small number of companies and production companies has made the market of dairy products a monopoly market and the existence of a monopoly in the market is considered one of the most important factors that cause lost welfare for consumers. (Gisser, 1982; Shahbazi, et al., 2009).
Materials and Methods
In this research, an attempt has been made to provide a structural framework for examining the performance of the dairy industry, especially milk and cheese (in terms of measuring the level of competition or monopoly). Based on the theory of NEIO, it is possible to quantify firms' market behavior in the absence of marginal cost data. The choice of demand model is of key importance in this type of analysis, since modeling a firm’s market behavior relies on correct representation of consumer preferences (Hovhannisyan & Bozic, 2013). In explaining consumer behavior, the functions selected for demand should be compatible with consumer theory, satisfy its theoretical characteristics, be easy to estimate, and have high predictive power. If, as the research shows, there is a non-linear relationship between demand and income, using a linear expenditure model will lead to an error and provide incorrect parameters. Recently, discrete choice demand models, such as the Logit specification, have increased in popularity in applied industrial organization research (Werden & Froeb, 1994). The random coefficient logit demand model is of particular interest, which allows for product differentiation and consumer heterogeneity. Finally, in this study, like some leading studies in the field of estimating the demand function of goods such as Hovhannisyan and Bozic (2013), uses an inverse demand system to create a structural framework of market behavior. In this approach, prices are endogenous. To model the inverse demand function and supply function, Leunberger's profit function approach (Luenberger, 1992) is used. Also, using the CV approach based on the study of Hovhannisyan & Bozic (2013), the amount of markup due to the existence of market power at the retail level is estimated for the years 2015-2021 in 7 selected provinces.
Results and Discussion
The choice of demand specification may significantly affect the estimation of structural coefficients. Therefore, several demand determination tests are performed using the Bewley likelihood ratio test (Bewley, 1986). The results show that there are quadratic utility effects in inverse demand functions. By using this feature, it is shown that the regional heterogeneity, i.e., , is the same as the lagged quantity, i.e., , the lagged price, i.e., and non-linear time effects, i.e., , are significant effects regarding the demand for milk and cheese. But seasonality, i.e., , has a negligible effect on the market for milk and cheese. The final demand relationship is estimated based on the results of the tests of various constraints on the model. The estimation of the complete model is done using the FIML method. Based on Hovhannisyan and Gould (2012), the constraint is applied. The estimation results indicate the presence of nonlinearity effects (effects) in utility function. Also, regional heterogeneity ( ), and the lagged quantity ( ), lagged price ( ) and nonlinear time effects ( ) have essential effects on milk and cheese demand. The results show that in the case of the milk industry, retailers have received the most mark up in B1 brand milk (milk produced by Iranian Dairy Industries Co.-IDIC) during the studied years. In such a way that on average they have received a markup equal to 4.8%, while this markup for milk produced by other brands is equal to 3.9%. Regarding the cheese industry, retailers receive a higher price markup for B2 cheese compared to cheese produced by competing companies of IDIC, averaging at 4.0%. However, the price markup for cheese produced by IDIC is only slightly lower, averaging at 3.9%. Also, the results show that there is a lot of regional heterogeneity among the provinces of the country (the studied provinces) in the dairy products industry that the variation in the degree of advancement of dairy industries across various provinces may be regarded as the foremost contributing factor. So that the surcharge at the retail level is different in different provinces. The price increase in B1 brand milk has changed from 3.3% in East Azarbaijan province to 7% in Razavi Khorasan province. But the retailers have received markup for milk produced by other brands, i.e. B2, from 3% in West Azarbaijan province to 6.9% in Isfahan province. In the case of cheese, the surcharge received by competing companies of IDIC has changed from 2% in Fars province to 6.5% in East Azarbaijan province. However, the retailers have received additional price from 1.5% in East Azarbaijan province to 6.7% in Fars province for the cheese produced in IDIC.
Conclusion
As anticipated, the market dynamics have exerted a significant influence on pricing, thereby shaping the incentives for milk and cheese production and, ultimately, consumption. The lack of competitive conditions in the production of milk and cheese (which has been mentioned in some studies such as Shahbazi et al., 2009 and Shahbazi & Faryadras, 2018 can reduce the consumption of milk and cheese and in the result of creating lost welfare for consumers and society. In other words, the possession of a large share of the milk market by a small number of companies (especially IDIC) and production companies makes the milk market a monopoly market, and the existence of a monopoly in the market is considered one of the most important factors that cause lost welfare for consumers. One of the processes that create competition is the development of the industry in terms of increasing the number of production companies by encouraging people to create dairy companies by providing incentive facilities from the government. Planning and investing in product advertising, especially in brands with a small market size, can help increase competition and transparency in the market. Acknowledging regional disparities in the branding and marketing of milk and cheese commodities is a crucial factor that demands attention. Additionally, factoring in market share dynamics and evolving consumer presumptions can provide valuable insights for making informed decisions regarding production and management strategies.
Anna Kowalska, Anna Olszańska, Joanna Szymańska
et al.
The research aimed to assess the changes that have occurred in the Polish export and import of poultry and the industry’s competitiveness. The analysis covered the years 2003 and 2022 and was carried out based on Eurostat data. The analysis included, among others, the value and balance of turnover, geographical structure, and selected competitiveness indicators. The leading importers of Polish poultry are the European Union countries. Poland has a comparative advantage mainly in the case of the EU market, which is confirmed by the increasing values of the TC and SI indicators and the decreasing HHI indicator. The obtained SI index values show that Poland had an apparent specialization in the export of poultry sector products to the markets of Great Britain, Bulgaria, Ireland, and Malta. The downward trend of the HHI index indicates the diversification of exports, which is a positive phenomenon as it provides the Polish poultry sector with stable revenues despite emerging turbulence. The reason for such a large increase in exports to EU countries was essentially the abolition of customs duties, attractive prices, and good quality of Polish products. Despite the substantial price advantages of Polish products and the favorable structure of comparative advantage indexes, poultry producers in Poland should constantly monitor the market environment. Attractively priced products offered by Ukraine, Brazil, and Thailand may harm the Polish export of these products in the coming years.
Assessing the impacts of both climate and land use changes on hydrologic variables is crucial for sustainable development of water resources and natural ecosystems. We conducted a case study of a catchment in southwestern Australia to assess the impacts of future climate and land use changes, both separately and in combination, on water resource availability. For this evaluation, the Soil and Water Assessment Tool (SWAT) model was first calibrated and then forced by 34 global climate models (GCMs), under two Representative Concentration Pathways (RCP4.5 and RCP8.5) and five land use scenarios (LU0–4). Our results suggested that SWAT reproduced the observed monthly streamflow well. Land use changes have impacts on all hydrologic variables, especially on runoff at the annual scale. Future runoff was projected to decrease in all seasons, especially winter and spring. For the combined effects of climate and land use changes, the results of LU1–4 were only slightly different from the response of LU0. An uncertainty analysis shows that GCMs had the greatest contribution to hydrologic variables, followed by RCPs and land use scenarios. Hence, it is advisable for impacts analysis to use an ensemble of GCMs under different RCPs to minimize the uncertainty of projected future hydrologic variables.
The innovation performance of the manufacturing industry in the Wuhan city circle is evaluated based on the relevant data from 2018 to 2020 in 9 cities of Hubei Province within the Wuhan city circle using the DEA-BCC model, the DEA-Malmquist index method, and the location quotient method. This article measures the agglomeration level of innovation elements in the Wuhan city circle, constructs a performance evaluation index system including two input indicators: R&D expenditure and R&D personnel, and two output indicators: new product sales revenue and number of patent applications; evaluates the innovation performance of 27 manufacturing industries in the Wuhan city circle from five aspects: technical efficiency change (effch), technical progress change (techch), pure technical efficiency change (pech), scale efficiency change (sech), and total factor productivity change (tfpch), and compares and analyzes the innovation performance of Wuhan, Xianning, Xiantao, and Tianmen using the DEA-BCC model and DEAP 2.1. The results show that the agglomeration level of talent elements in the Wuhan city circle is between 0.24 and 1.75, and the agglomeration level of capital elements is between 0.23 and 1.52. The differences between regions are obvious, the degree of coordination is low, and the radiation effect of Wuhan is insufficient. The average value of technological progress is 1.274, which is vital to enhance the innovation performance of the Wuhan manufacturing industry. The technical efficiency dropped by 65%, but the total factor productivity fell only 13%, indicating that the technical efficiency value is not the main factor affecting the innovation performance of Wuhan. The innovation performance of high-tech and high-value-added industries such as computer, communication, and other electronic equipment manufacturing industries is relatively high, while the innovation performance of low-tech and low-value-added industries such as agricultural and sideline food processing industry and textile industry is relatively low. The innovation performance of Xianning, Xiantao, and Tianmen is higher, while the relative technological inefficiency caused by the low-scale efficiency value adversely affects the innovation performance of Wuhan. The results indicate that increasing the scale of manufacturing innovation investment can effectively enhance the innovation performance of the Wuhan city circle manufacturing industry.
Rubby Aworka, Lontsi Saadio Cedric, Wilfried Yves Hamilton Adoni
et al.
Food security has become a real challenge for some organizations in charge of the food program and for the majority of countries, especially African countries. The United Nations Organizations’ has recently defined the end of hunger and the improvement of food security in 2030 as its primary goal. Improving food security could also pass through the handling of agricultural yield. Agricultural yield is affected by climate changes since this latest decade. Climate change is considered one of the major threats to agricultural development in Africa. Decision-making level and farmers need efficient analytical tools to help them in decision making. Machine learning has become an impressive predictive analytical tool for large volume of data. It has been used in many domains such as medicine, finance, sport, and recently in agriculture. In this work, we propose three crop prediction models : Crop Random Forest, Crop Gradient Boosting Machine and Crop Support Vector Machine. We combine climate data, crop production data, and pesticides data to develop a decision system based on advanced machine learning models. Despite the poor availability of data related to agriculture in Africa, we were able to propose a decision system able to predict the crop yield at the country level in fourteen East African countries. Our experimental results show that the three proposed machine learning models fit well the crop data with a high accuracy R2. The Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) associated to our models are very minimal because the agricultural prediction values are very close to reality. Our proposed models are reliable and generalize well the agricultural predictions in East Africa.
Eric N. Ponnampalam, Ali Kiani, Sarusha Santhiravel
et al.
The biological effects of oxidative stress and associated free radicals on farm animal performance, productivity, and product quality may be managed via dietary interventions—specifically, the provision of feeds, supplements, and forages rich in antioxidants. To optimize this approach, it is important first to understand the development of free radicals and their contributions to oxidative stress in tissue systems of farm animals or the human body. The interactions between prooxidants and antioxidants will impact redox homeostasis and, therefore, the well-being of farm animals. The impact of free radical formation on the oxidation of lipids, proteins, DNA, and biologically important macromolecules will likewise impact animal performance, meat and milk quality, nutritional value, and longevity. Dietary antioxidants, endogenous antioxidants, and metal-binding proteins contribute to the ‘antioxidant defenses’ that control free radical formation within the biological systems. Different bioactive compounds of varying antioxidant potential and bio-accessibility may be sourced from tailored feeding systems. Informed and successful provision of dietary antioxidants can help alleviate oxidative stress. However, knowledge pertaining to farm animals, their unique biological systems, and the applications of novel feeds, specialized forages, bioactive compounds, etc., must be established. This review summarized current research to direct future studies towards more effective controls for free radical formation/oxidative stress in farm animals so that productivity and quality of meat and milk can be optimized.
XYZ is a company engaged in packaging, especially for pharmaceuticals. The company has recorded an overall defective product known as end to end waste. During 2019 the average end to end waste was 12.37%, while the target of company management was 9%. The objective of this research is to minimize defective products and to find out what types of defects occur in the production process. The method used in this research is FMECA (Failure Modes, Effects and Critically Analysis), which is the development of the FMEA (Failure Mode and Effect Analysis) method which functions to make analyzes from production tools or processes, types of defects to the effects that arise as a result. of the defect, but also to determine the critical point. The results of the analysis that has been carried out using the FMEA method with RPN (Risk Priority Number) calculations, then analysis with the Pareto diagram and criticality matrix, the researcher gets 10 priority failure modes, namely the machine often stops due to a lot of paper dust, too high piles, unstable colors because there is a change in ink, the non-stop feeder is damaged, the front lay and side lay are unstable from the printing process, the side lay sensor does not work, the actual chiller temperature with the display is not the same, the paper is untidy from the printing process, the paper is untidy from the calendering process, and the chiller is leaking. The researcher also gave recommendations, namely making a Standard Operation Procedure (SOP) for handling dusty paper, submitting complaints to suppliers regarding paper quality, providing a printing unit, and training for dusty paper handling.
Lista dos pareceristas que contribuiram avaliando artigos durante o período de elaboração desta edição da revista Estudos Sociedade e Agricultura (v. 28, n. 3, outubro de 2020 a janeiro de 2021).
- Alexandra Martins Silva – Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Rio de Janeiro, Brasil
- Ana Lúcia da Costa Silveira – Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropédica, Rio de Janeiro, Brasil
- Ana Paula Schervinski Villwock – Universidade Federal de Sergipe (UFS), São Cristóvão, Sergipe, Brasil
- Andréa Cristina Martins Pereira – Universidade Estadual de Montes Claros (Unimontes), Montes Claros, Minas Gerais, Brasil
- Ângelo Magalhães Silva – Universidade Federal Rural do Semi-Árido (UFERSA), Mossoró, Rio Grande do Norte, Brasil
- Antônio Fernando de Araújo Sá – Universidade Federal do Sergipe (UFS), São Cristóvão, Sergipe, Brasil
- Arlete Fonseca de Andrade – Pontifícia Universidade Católica de São Paulo (PUC-SP), São Paulo, São Paulo, Brasil
- Carmen Lucia Tavares Felgueiras – Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, Brasil
- Cicero Nilton Moreira da Silva – Universidade do Estado do Rio Grande do Norte (UERN), Pau dos Ferros, Rio Grande do Norte, Brasil
- Cidonea Machado Deponti – Universidade de Santa Cruz do Sul (UNISC), Santa Cruz do Sul, Rio Grande do Sul, Brasil
- Clóvis Dorignon – Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina (Embrapa/SC), Florianópolis, Santa Catarina, Brasil
- Cristiano Desconsi – Universidade Federal de Santa Catarina (UFSC), Florianópolis, Santa Catarina, Brasil
- Delma Pessanha Neves – Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, Brasil
- Everton Lazzaretti Picolotto – Universidade Federal de Santa Maria (UFSM), Santa Maria, Rio de Grande do Sul, Brasil
- Fabiane Renata Borsato – Universidade Estadual Paulista Júlio de Mesquita Filho (Unesp), Araraquara, São Paulo, Brasil
- Fabiano de Souza Gontijo – Universidade Federal do Pará (UFPA), Belém, Pará, Brasil
- Fabiano Toni – Universidade de Brasília (UnB), Brasília, Distrito Federal, Brasil
- Flávio Sacco dos Anjos – Universidade Federal de Pelotas (UFPel), Pelotas, Rio Grande do Sul, Brasil
- Gilmar Rocha – Universidade Federal Fluminense (UFF), Rio das Ostras, Rio de Janeiro, Brasil
- Guélmer Júnior Almeida Faria – Universidade Federal de Viçosa (UFV), Viçosa, Minas Gerais, Brasil
- Haruf Salmen Espíndola – Universidade Vale do Rio Doce (Univale), Governador Valadares, Minas Gerais, Brasil
- Izabel Missagia de Mattos – Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropédica, Rio de Janeiro, Brasil
- Jairo Bezerra Silva – Universidade Estadual da Paraíba (UEPB), Campina Grande, Paraíba, Brasil
- Jean Pierre Passos Medaets – Universidade de Brasília (UnB), Brasília, Distrito Federal, Brasil
- João Paulo Macedo – Universidade Federal do Piauí (UFPI), Teresina, Piauí, Brasil
- Julia Silvia Guivant – Universidade Federal de Santa Catarina (UFSC), Florianópolis, Santa Catarina, Brasil
- Juliete Miranda Alves – Universidade Federal Rural da Amazônia (UFRA), Belém, Pará, Brasil
- Júlio Cezar Bastoni da Silva – Universidade Federal do Ceará (UFC), Fortaleza, Ceará, Brasil
- Larissa da Silva Ferreira Alves – Universidade do Estado do Rio Grande do Norte (UERN), Pau dos Ferros, Rio Grande do Norte, Brasil
- Lorena Cândido Fleury – Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul, Brasil
- Luiz Felipe Rocha Benites – Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropédica, Rio de Janeiro, Brasil
- Luiz Gonzaga Marchezan – Universidade Estadual Paulista Júlio de Mesquita Filho (Unesp), Araraquara, São Paulo, Brasil
- Maciel Cover – Universidade Federal do Tocantins (UFTO), Palmas, Tocantins, Brasil
- Marcelino de Souza – Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul, Brasil
- Márcio de Matos Caniello – Universidade Federal de Campina Grande (UFCG), Campina Grande, Paraíba, Brasil
- Maria Celia de Moraes Leonel – Universidade Estadual Paulista (Unesp), Araraquara, São Paulo, Brasil
- Maria Inês Gasparetto Higuchi – Universidade Federal do Amazonas (UFAM), Manaus, Amazonas, Brasil
- Mariana Vieira Galuch – Universidade Federal do Amazonas (UFAM), Manaus, Amazonas, Brasil
- Marilda Menezes – Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brasil
- Mário Lúcio de Avila – Universidade de Brasília (UnB), Brasília, Distrito Federal, Brasil
- Mylene Nogueira Teixeira – Universidade Estadual do Norte Fluminense (UENF) – Campos dos Goytacazes, Rio de Janeiro, Brasil
- Nelson Delgado – Universidade Federal Rural do Rio de Janeiro (UFRRJ), Rio de Janeiro, Rio de Janeiro, Brasil
- Patricia Eveline dos Santos Roncato – Universidade Federal do Pampa (Unipampa), Santana do - Livramento, Rio Grande do Sul, Brasil
- Ramonildes Alves Gomes – Universidade Federal de Campina Grande (UFCG), Campina Grande, Paraíba, Brasil
- Renato Sérgio Maluf – Universidade Federal Rural do Rio de Janeiro (UFRRJ), Rio de Janeiro, Rio de Janeiro, Brasil
- Roberto de Sousa Miranda – Universidade Federal do Agreste de Pernambuco (Ufape), Guaranhuns, Pernambuco, Brasil
- Rosani Marisa Spanevello – Universidade Federal de Santa Maria (UFSM), Palmeira das Missões, Rio de Grande do Sul, Brasil
- Rozane Marcia Triches – Universidade Federal da Fronteira Sul (UFFS), Chapecó, Santa Catarina, Brasil
- Silvio Cezar Arend – Universidade de Santa Cruz do Sul (UNISC), Santa Cruz do Sul, Rio Grande do Sul, Brasil
- Tania Mara Antonietti Lopes – Universidade de São Paulo (USP), São Paulo, São Paulo, Brasil
- Thiago Araújo Santos – Universidade Federal de Mato Grosso do Sul (UFMS), Três Lagoas, Mato Grosso do Sul, Brasil
- William Héctor Gómez Soto – Universidade Federal de Pelotas (UFPel), Pelotas, Rio Grande do Sul, Brasil
- Wilma Martins de Mendonça – Universidade Federal da Paraíba (UFPB), João Pessoa, Paraíba, Brasil
he aim of this study was to determine the sustainability degree of local development for counties of the Mazowieckie (Mazovian) Voivodship in the years 2006-2015. Research was conducted on a population of 42 counties (territorial units at NUTS 4 level), including 5 town counties (towns possessing county status) and 37 land counties. Basing on data from the Local Data Bank of the Central Statistical Office, three dimensions of development were investigated: economic, social and ecological (environmental). The author’s conceptual approach, incorporating dimensional indexes of development and Euclidean distance analysis, was applied to capture the interactions between and balance across the three pillars of sustainability. Through the results of the study, it is observed that the highest degree of local development sustainability was achieved by counties located up to 50 kilometres from Poland’s capital city Warsaw (i.e. grodziski, grójecki, nowodworski, otwocki, sochaczewski, wołomiński and żyrardowski), while the lowest by towns with a county status (Ostrołęka, Płock and Warsaw) and by peripheral counties of the east and south part of the Mazovian Voivodship (siedlecki, przysuski, lipski and zwoleński). In the 2015 ranking, according to the sustainability degree of counties, the first three spots were taken by ciechanowski, przasnyski and sochaczewski counties. The following town counties took the last three positions: Ostrołęka, Płock and Warsaw.
Obstacles factor to get natural rubber raw materials is less efficient for latex processing into concentrated latex, because it need a long time that 2-3 weeks. Centrifugation method many used by concentrated latex factory because it can concentrate the latex with a short relatively time. While the weakness of the centrifugation method is more expensive if that compared with the curdling. With the weakness centrifugation method and curdling, in this research, making the concentrated latex are used vibration method, with the addition of curdle. The purpose of this research is to get the optimum vibrations speed for the concentrated latex manufactured, the speed of the vibrations are used 150 rpm, 175 rpm, 200 rpm, 225 rpm and 250 rpm. The design are used in this research is Randomized Block Design with 6 treatments was repeated 4 times, then obtained 24 units of the experiment, if there is a real difference, then used the BNT at the level of 5% and the data analysis process using Minitab version 16. the most optimum RPM are used in this research is 225 with a quality approaching the standard.
Saffron is one of the most important herbs and spices in the East of Iran and its production is affected by various pathogens. This study is aimed at isolation, identification and pathogenicity detection of <em>Alternaria alternata</em> isolates as leave spot and corm rot of saffron agents. Soil samples and infected plant tissues were collected from different areas of the Birjand plain (Birjand, Khusf and Sarbishe) during the years 2014-15. <em>Alternaria</em> species were isolated by potato dextrose agar medium and their morphological characteristics were studied on the potato carrot agar medium. For molecular studies, genomic DNA was extracted by the CTAB method and ribosomal subunits of fungal isolates were amplified using ITS1 and ITS4 primers. Based on morphological characteristics, 80 isolates of A. alternata were isolated. The ITS regions sequences of selected isolates had 100 similarities with <em>A. alternata</em> spices sequences in NCBI and MycoBank. These isolates caused chlorosis and necrosis on detached leaves, the inoculated corm was rotten and inoculated plants showed chlorosis and necrosis on leaves after 3-5 days. The results showed that <em>A. alternata</em> in the Birjand plain can cause corm rot and leaf chlorosis and necrosis is saffron. This study is the first report of the virulence of this fungus on saffron tissue in the East of Iran.