Search results for: processing tomato crop

Authors: K. C. Sony

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This paper investigates the coping strategies of households confronting disease in large cardamom (Amomum Subulatum Roxb.) in eastern Nepal. Cardamom farmers draw on various coping strategies to reduce the impact of crop disease in their livelihoods. Yet farmers face tremendous decline in production with a constant effort for revival. Past evidences provides dearth of information about coping strategies employed by farmers and institutional intervention to combat disease. Using factual data from Ilam district, and conducting a political economic analysis, this research addresses the gap by 1) understanding the impact of crop disease in farmers’ livelihoods, 2) identifying the coping strategies adopted by farmers and, 3) examining the existing institutional arrangements to address the disease. Coping strategies vary by household’s status defined by size of land, alternative income, and access to supporting institutions. Measures adopted are burning the cardamom field, changing land use pattern, diversifying crops, and visiting institutions for support. The local government’s support is limited to providing trainings and producing new varieties of cardamom. During crisis, farmers expect institutions to help revive the cardamom production, despite customary practice to combat disease. To retain and improve the livelihoods of farmers, there needs to be institutional innovation at the community level and policies that endorse immediate and sustainable support during hazards.

Keywords: cardamom, coping strategy, disease, institutions, Nepal

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Authors: Hooman Torabifard

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In the last few years, with the progress of technology and computers and artificial intelligence entry into all kinds of scientific and industrial fields, the lifestyles of human life have changed and in general, the way of humans live on earth has many changes and development. Until now, some of the changes has occurred in the context of digital images and image processing and still continues. However, besides all the benefits, there have been disadvantages. One of these disadvantages is the multiplicity of images with high volume and data; the focus of this paper is on improving and developing a method for summarizing and enhancing the productivity of these images. The general method used for this purpose in this paper consists of a set of methods based on data obtained from image processing and using the PSO (Particle swarm optimization) algorithm. In the remainder of this paper, the method used is elaborated in detail.

Keywords: image summarization, particle swarm optimization, image threshold, image processing

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Authors: Abraham Castro-Alvarez, Luisaldo Sandate-Flores, Roberto Parra-Saldivar

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The losing of crops during the whole production process is a problem that is affecting farmers in the whole world, as climate change affects the weather behavior. Stenocereus spp. is a tropical, exotic and endemic columnar cacti, it produces a colored and expensive fruit known how “pitaya”. The quality and value of the fruit, these species represent an attractive option for economical development in arid and semi-arid regions. This fruits are produced in Mexico, mainly in 4 regions, Mixteca Oaxaca-Puebla, Michoacan, Sinaloa-Sonora, Jalisco-Zacatecas. Pitaya can be an option to try mixed crop in this states due to the resistance to hard weather conditions. And also because of the marginalization problems that exist in these townships. As defined by the Population National Council it consists in the absence of development opportunities and the lack of capacity to get them. According to an analysis done in EsriPress ArcGis 10.1 the potential area in the country is almost the half of the territory being the total area of Mexico 1,965,249 km2 and the area with potential to produce pitaya 960,527 km2. This area covers part of the most affected townships that also have a few options of maize varieties making even harder the production of maize and exposing farmers to crop losing if conditions are good enough. Making pitaya a good option for these farmers to have an economic backup in their productions.

Keywords: maize, pitaya, rain fed, Stenocereus

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Authors: A. Shakoor, M. Arshad

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The utilization of groundwater resources in irrigation has significantly increased during the last two decades due to constrained canal water supplies. More than 70% of the farmers in the Punjab, Pakistan, depend directly or indirectly on groundwater to meet their crop water demands and hence, an unchecked paradigm shift has resulted in aquifer depletion and deterioration. Therefore, a comprehensive research was carried at central Punjab-Pakistan, regarding spatiotemporal variation in groundwater level and quality. Processing MODFLOW for window (PMWIN) and MT3D (solute transport model) models were used for existing and future prediction of groundwater level and quality till 2030. The comprehensive data set of aquifer lithology, canal network, groundwater level, groundwater salinity, evapotranspiration, groundwater abstraction, recharge etc. were used in PMWIN model development. The model was thus, successfully calibrated and validated with respect to groundwater level for the periods of 2003 to 2007 and 2008 to 2012, respectively. The coefficient of determination (R2) and model efficiency (MEF) for calibration and validation period were calculated as 0.89 and 0.98, respectively, which argued a high level of correlation between the calculated and measured data. For solute transport model (MT3D), the values of advection and dispersion parameters were used. The model used for future scenario up to 2030, by assuming that there would be no uncertain change in climate and groundwater abstraction rate would increase gradually. The model predicted results revealed that the groundwater would decline from 0.0131 to 1.68m/year during 2013 to 2030 and the maximum decline would be on the lower side of the study area, where infrastructure of canal system is very less. This lowering of groundwater level might cause an increase in the tubewell installation and pumping cost. Similarly, the predicted total dissolved solids (TDS) of the groundwater would increase from 6.88 to 69.88mg/L/year during 2013 to 2030 and the maximum increase would be on lower side. It was found that in 2030, the good quality would reduce by 21.4%, while marginal and hazardous quality water increased by 19.28 and 2%, respectively. It was found from the simulated results that the salinity of the study area had increased due to the intrusion of salts. The deterioration of groundwater quality would cause soil salinity and ultimately the reduction in crop productivity. It was concluded from the predicted results of groundwater model that the groundwater deteriorated with the depth of water table i.e. TDS increased with declining groundwater level. It is recommended that agronomic and engineering practices i.e. land leveling, rainwater harvesting, skimming well, ASR (Aquifer Storage and Recovery Wells) etc. should be integrated to meliorate management of groundwater for higher crop production in salt affected soils.

Keywords: groundwater quality, groundwater management, PMWIN, MT3D model

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Authors: Okwara O. S., Osunsina I. O. O., Pitan O. R., Afolabi C. G.

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Rice (Oryza sativa L.) belongs to the family poaceae and has become the most popular food. Globally, this crop is been faced with the menace of vertebrate pests, of which birds and rodents are the most implicated. The study avian and rodents’ infestations and the evaluation of attributable losses was carried out in 2020 and 2021 with the objectives of identifying the types of bird and rodent species associated with lowland rice and to determine the infestation levels, damage intensity, and the crop loss induced by these pests. The experiment was laid out in a split plot arrangement fitted into a Randomized Complete Block Design (RCBD), with the main plots being protected and unprotected groups and the sub-plots being four rice varieties, Ofada, WITA-4, NERICA L-34, and Arica-3. Data collection was done over a 16-week period, and the data obtained were transformed using square root transformation model before Analysis of Variance (ANOVA) was done at 5% probability level. The results showed the infestation levels of both birds and rodents across all the treatment means of thevarieties as not significantly different (p > 0.05) in both seasons. The damage intensity by these pests in both years were also not significantly different (p > 0.05) among the means of the varieties, which explains the diverse feeding nature of birds and rodents when it comes to infestations. The infestation level under the protected group was significantly lower (p < 0.05) than the infestation level recorded under the unprotected group.Consequently, an estimated crop loss of 91.94 % and 90.75 % were recorded in 2020 and 2021, respectively, andthe identified pest birds were Ploceus melanocephalus, Ploceus cuculatus, and Spermestes cucullatus. Conclusively, vertebrates pest cause damage to lowland rice which could result to a high percentage crop loss if left uncontrolled.

Keywords: pests, infestations, evaluation, losses, rodents, avian

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Authors: Antonietta Maoloni, Federica Cardinali, Vesna Milanović, Andrea Osimani, Ilario Ferrocino, Maria Rita Corvaglia, Luca Cocolin, Lucia Aquilanti

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Table olives (Olea europaea L.) are among the most important fermented vegetables all over the world, while sea fennel (Crithmum maritimum L.) is an emerging food crop with interesting nutritional and sensory traits. Both of them are characterized by the presence of several bioactive compounds with potential beneficial health effects, thus representing two valuable substrates for the manufacture of innovative vegetable-based preserves. Given these premises, the present study was aimed at exploring the co-fermentation of table olives and sea fennel to produce new high-value preserves. Spanish style or Greek style processing method and the use of a multiple strain starter were explored. The preserves were evaluated for their microbial dynamics and key sensory traits. During the fermentation, a progressive pH reduction was observed. Mesophilic lactobacilli, mesophilic lactococci, and yeasts were the main microbial groups at the end of the fermentation, whereas Enterobacteriaceae decreased during fermentation. An evolution of the microbiota was revealed by metataxonomic analysis, with Lactiplantibacillus plantarum dominating in the late stage of fermentation, irrespective of processing method and use of the starter. Greek style preserves resulted in more crunchy and less fibrous than Spanish style one and were preferred by trained panelists.

Keywords: lactic acid bacteria, Lactiplantibacillus plantarum, metataxonomy, panel test, rock samphire

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Authors: Ashkan Asgari, Korous Khoshbakht, Saeid Soufizadeh

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Various factors including land lots can affect biodiversity indices in Agricultural systems. Field study conducted to evaluate factors affecting crop diversity in Sarpolzahab in 2012. Required data were collected through direct observation of farms and filling questionnaires. Total numbers of 140 questionnaires were filled, SAS Software was used to analyse data and Ecological Methodology Program was applied to calculate Shannon-Winner index, subsequently. Results of study indicated that average number of land lots for each farmer was 2.78 and various from 2.2 in Rikhak Olia Village to 4.31 in Golam Kaboud Olia Village which shows small size of land lots due to separating larger lots by children of deceased farmers. The correlation between number of land lots and species biodiversity (0.308**) was significant and Shannon-Winner index was (0.262**). Therefore, according to the mentioned results one can assume that increase in number of land lots results in improving of the target index. Multiple land lots allow farmers to cultivate various crops which results in increasing biodiversity of crops in agro ecosystem. Subsequently, this increase will facilitate economic sustainability of the farmers and distribution of work force in the region throughout the year. The correlation of seasonal workers with biodiversity of crop species (0.256**) and Shannon-Winner (0.286**) was statistically significant and increasing number of seasonal work forces had resulted in improving crop biodiversity and decreasing dominant species or single crop farming systems. Vegetable farms which have a significant diversity, require a significant number of work forces which describes correlation between number of workers and diversity of species.

Keywords: agricultural systems, biodiversity indices, Shannon-Winner index, sustainability, rural

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Authors: Sánchez Acuña, Juan Camilo, Granados Gómez, Mildred Magaly, Navarrete Rodríguez, Luisa Fernanda

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Nowadays, the main biofuels source production as bioethanol is food crops. This means a high competition between foods and energy production. For this reason, it is necessary to take into account the use of new raw materials friendly to the environment. The main objective of this paper is to evaluate the potential of the agro-industrial banana crop residues in the production of bioethanol. A factorial design of 2⁴ was used, the design has variables such as pH, time and concentration of hydrolysis, another variable is the time of fermentation that is of 7 or 15 days. In the hydrolysis phase, the pH is acidic (H₂SO₄) or basic (NaOH), the time is 30 or 15 minutes and the concentration is 0.1 or 0.5 M. It was observed that basic media, low concentrations, fermentation, and higher pretreatment times produced better performance in terms of biofuel obtained.

Keywords: bioethanol, biofuels, banana waste, hydrolysis

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Deepak Loura

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Climate change is considered one of the major environmental problems of the 21st century and a lasting change in the statistical distribution of weather patterns over periods ranging from decades to millions of years. Agriculture and climate change are internally correlated with each other in various aspects, as the threat of varying global climate has greatly driven the attention of scientists, as these variations are imparting a negative impact on global crop production and compromising food security worldwide. The fast pace of development and industrialization and indiscriminate destruction of the natural environment, more so in the last century, have altered the concentration of atmospheric gases that lead to global warming. Carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (NO) are important biogenic greenhouse gases (GHGs) from the agricultural sector contributing to global warming and their concentration is increasing alarmingly. Agricultural productivity can be affected by climate change in 2 ways: first, directly, by affecting plant growth development and yield due to changes in rainfall/precipitation and temperature and/or CO₂ levels, and second, indirectly, there may be considerable impact on agricultural land use due to snow melt, availability of irrigation, frequency and intensity of inter- and intra-seasonal droughts and floods, soil organic matter transformations, soil erosion, distribution and frequency of infestation by insect pests, diseases or weeds, the decline in arable areas (due to submergence of coastal lands), and availability of energy. An increase in atmospheric CO₂ promotes the growth and productivity of C3 plants. On the other hand, an increase in temperature, can reduce crop duration, increase crop respiration rates, affect the equilibrium between crops and pests, hasten nutrient mineralization in soils, decrease fertilizer- use efficiencies, and increase evapotranspiration among others. All these could considerably affect crop yield in long run. Climate resilient agriculture consisting of adaptation, mitigation, and other agriculture practices can potentially enhance the capacity of the system to withstand climate-related disturbances by resisting damage and recovering quickly. Climate resilient agriculture turns the climate change threats that have to be tackled into new business opportunities for the sector in different regions and therefore provides a triple win: mitigation, adaptation, and economic growth. Improving the soil organic carbon stock of soil is integral to any strategy towards adapting to and mitigating the abrupt climate change, advancing food security, and improving the environment. Soil carbon sequestration is one of the major mitigation strategies to achieve climate-resilient agriculture. Climate-smart agriculture is the only way to lower the negative impact of climate variations on crop adaptation before it might affect global crop production drastically. To cope with these extreme changes, future development needs to make adjustments in technology, management practices, and legislation. Adaptation and mitigation are twin approaches to bringing resilience to climate change in agriculture.

Keywords: climate change, global warming, crop production, climate resilient agriculture

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Authors: Mauricio Quintero Angel, Andrés A. Duque Nivia, Carlos H. Fajardo Toro

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This paper analyzes two approaches of sustainability, the weak and strong, considering a case of study of oil palm production for an industry of biodegradable detergent. In this case, a company demand the oil palm as the active element for washing and through its trademark aims to supply 10% of the Colombian market of washing powders. Under each approach the economic and ecological implications of the palm oil production and especially the implications for crop management are described. The crop production under the weak sustainability implies plantations, intensive use of agrochemicals and the inclusion of new areas of cultivation as the market grows. Under the strong sustainability the production system is limited by the productive vocation of the ecosystem, so that new approaches and creativity for making viable the nature conservancy and the business development are require.

Keywords: agriculture, environmental impacts, oil palm, strong sustainability, weak sustainability

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Muhammet Dursun Kaya, Hasan Asil

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In recent years, different methods have been proposed to optimize question processing in database. Although different methods have been proposed to optimize the query, but the problem which exists here is that most of these methods destroy the query execution plan after executing the query. This research attempts to solve the above problem by using a combination of methods of communicating with the database (the present questions in the programming code and using store procedures) and making query processing adaptive in database, and proposing a new approach for optimization of query processing by introducing the idea of dynamic store procedures. This research creates dynamic store procedures in the database according to the proposed algorithm. This method has been tested on applied software and results shows a significant improvement in reducing the query processing time and also reducing the workload of DBMS. Other advantages of this algorithm include: making the programming environment a single environment, eliminating the parametric limitations of the stored procedures in the database, making the stored procedures in the database dynamic, etc.

Keywords: relational database, agent, query processing, adaptable, communication with the database

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Authors: Reza Rezaeipour Honarmandzad

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Wavelet analysis is an exciting method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, signal processing, image processing, pattern recognition, etc. Wavelets allow complex information such as signals, images and patterns to be decomposed into elementary forms at different positions and scales and subsequently reconstructed with high precision. In this paper a wavelet-based signal processing algorithm for airplane cable fault location is proposed. An orthogonal discrete wavelet decomposition and reconstruction algorithm is used to eliminate the noise in the aircraft cable fault signal. The experiment result has shown that the character of emission pulse and reflect pulse used to test the aircraft cable fault point are reserved and the high-frequency noise are eliminated by means of the proposed algorithm in this paper.

Keywords: wavelet analysis, signal processing, orthogonal discrete wavelet, noise, aircraft cable fault signal

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Authors: G. Chipili, J. Msuya

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The Central Province of Zambia contains the majority of the nation’s malnourished children, despite being the most productive province in terms of Agriculture. Most studies in the province have not paid attention to the linkages between agriculture performance and nutrition outcomes of the population. In light of this knowledge gap, this study focused on the linkage between nutrition and agriculture. In 2010 the Ministry of Agriculture in the Central Province while working with Non-Governmental Organizations (NGOs), the Ministry of Health and the Ministry of Education started a pilot project in Kapiri-Mponshi on Orange-fleshed Sweet Potatoes and Orange Maize and educating farmers on the importance of crop diversity. The study assessed the extent to which the small scale farmers are implementing the best practices of nutrition-sensitive agriculture in the Central Province. This study sought to determine the association of crop diversity and nutritional status of children aged 6-59 months in Kapiri-Mposhi district in the Central Province of Zambia. A cross-sectional descriptive study was conducted using a structured questionnaire. A total of 365 households were randomly sampled and the nutritional status of one child from each household assessed using anthropometric measurements. A total of 100 children were included in the study. Up to 21% of the children were stunted; 2% were wasted; and 9% underweight. There was a significant relationship between crops grown in households (ground nuts, maize and mangoes) and Z-scores for stunting (HAZ) and underweight (WAZ) (p< 0.05). This study has established that farmers may not diversify if they have high market demands on the staple.

Keywords: agriculture, crop diversity, children, nutrition

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Authors: Basave Gowda, Lokesh K., Prasanth S. M., Bellad S. B., Radha J., Lokesh G. Y., Patil S. B., Vijayakumar D. K., Ganigar B. S., Rakesh C. Mathad

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Quality seed plays an important role in enhancing the crop productivity. It was reported and confirmed by large scale verification research trials that by use of quality seeds alone, the crop yield can be enhanced by 15 to 20 per cent. At present, the quality seed production and distribution through organised sectors comprising both public and private seed sector was only 20-25% of the requirement and the remaining quantity is met through unorganised sector which include the farmer to farmers saved seeds. With an objective of developing an alternative seed system, the University of Agricultural Sciences, Raichur in Karnataka state has implemented Seed Village Programme in more than 100 villages covering around 5000 farmers every year since 2009-10 and in the selected seed villages, a group of 50-150 farmers were supplied the foundation seeds of new varieties to an extent of 0.4 ha at 50 % subsidy. And two to three training programmes were conducted in the targeted villages for quality seed production and the seed produced in the target group was processed locally in the university seed processing units and arranged for distribution in the local villages by the seed growers themselves. By this new innovative and modified seed system, the university can able to replace old varieties of pigeon pea and green gram by producing 1482, 2978, 2729, 2560, and 4581 tonnes of seeds of new varieties on large scale under farmers and scientists participatory seed village programmes respectively during 2009-10, 2010-11, 2011-12, 2012-13 and 2013-14. From this new alternate model of seed system, there should be large scale promotion of regional seed system involving farmers, NGO and voluntary organisation for quick and effective replacement of old, low yielding, disease susceptible varieties with new high yielding, disease resistant for enhanced food production and food security.

Keywords: seed system, seed village, seed replacement, varietal replacement

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Authors: Charles Iledun Oyewole, Harira Shuaib

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While fulfilling the food security of an increasing population like Nigeria remains a major global concern, more than one-third of crop harvested is lost or wasted during harvesting or in postharvest operations. Reducing the harvest and postharvest losses, especially in developing countries, could be a sustainable solution to increase food availability, eliminate hunger and improve farmers’ livelihoods. Nigeria is one of the countries in sub-Saharan Africa with insufficient food production and high food import bill, which has had debilitating effects on the country’s economy. One of the goals of Nigeria’s agricultural development policy is to ensure that, the nation produces enough food and be less dependent on importation so as to ensure adequate and affordable food for all. Maize could fill the food gap in Nigeria’s effort to beat hunger and food insecurity. Maize is the most important cereal after rice and its production contributes immensely to food availability on the tables of many Nigerians. Maize grains constitute primary source of food for large percentage of the Nigerian populace, thus a considerable waste of this valuable food pre and post-harvest constitutes such a major agricultural bottleneck; that the reduction of pre and post-harvest losses is now a common food security strategy. In surveys conducted, as much as 60% maize outputs can be lost on the field and during the storage stage due to technical inefficiency. Field losses due to rodent damage alone can account for between 10% - 60% grain losses depending on the location. While the use of scientific storage methods can reduce losses below 2% in storage, timely harvesting of crop can check losses on the fields resulting from rodent damage or pest infestation. A push for increased crop production must be complemented by available and affordable post-harvest technologies that will reduce losses on farmers’ fields as well as in storage.

Keywords: government policy, maize, population increase, storage, sustainable food production, yield, yield losses

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Authors: Diana Karina Baigts Allende, Mariana Gonzalez Diaz, Luis Antonio Chel Guerrero, Mukthar Sandoval Peraza

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Poverty and food insecurity are still incident problems in the developing countries, where population´s diet is based on cereals which are lack in protein content. Nevertheless, during last years the use of native plants has been studied as an alternative source of protein in order to improve the nutritional intake. Chaya crop also called Spinach tree, is a prehispanic plant native from Central America and South of Mexico (Mayan culture), which has been especially valued due to its high nutritional content particularly protein and some medicinal properties. The aim of this work was to study the effect of protein isolation processing from Chaya leaf harvest in Yucatan, Mexico on its structure quality in order: i) to valorize the Chaya crop and ii) to produce low-cost and high-quality protein. Chaya leaf was extruded, clarified and recovered using: a) acid precipitation by decreasing the pH value until reach the isoelectric point (3.5) and b) thermal coagulation, by heating the protein solution at 80 °C during 30 min. Solubilized protein was re-dissolved in water and spray dried. The presence of Fraction I protein, known as RuBisCO (Rubilose-1,5-biphosfate carboxylase/oxygenase) was confirmed by gel electrophoresis (SDS-PAGE) where molecular weight bands of 55 KDa and 12 KDa were observed. The infrared spectrum showed changes in protein structure due to the isolation method. The use of high temperatures (thermal coagulation) highly decreased protein solubility in comparison to isoelectric precipitated protein, the nutritional properties according to amino acid profile was also disturbed, showing minor amounts of overall essential amino acids from 435.9 to 367.8 mg/g. Chaya protein isolate obtained by acid precipitation showed higher protein quality according to essential amino acid score compared to FAO recommendations, which could represent an important sustainable source of protein for human consumption.

Keywords: chaya leaf, nutritional properties, protein isolate, protein structure

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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Authors: M. Kustyawati, F. Pratama, D. Saputra, A. Wijaya

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Tempe composes of not only molds but also bacteria and yeasts. The structure of microorganisms needs to be in balance number in order the tempe to be an acceptable quality for an extended time. Sub supercritical carbon dioxide can be a promising preservation method for tempe as it induces microbial inactivation avoiding alterations of its quality attributes. Fresh tempe were processed using supercritical and sub supercritical CO2 for a defined holding times, then the growth ability of molds and bacteria were analyzed. The results showed that the supercritical CO2 processing for 5 minutes reduced the number of bacteria and molds to 0.30 log cycle and 1.17 log cycles, respectively. In addition, sub supercritical CO2 processing for 20 minutes had fungicidal effect against mold tempe; whereas, the sub supercritical CO2 for 10 minutes had reducing effect against bacteria tempe, and had fungistatic affect against mold tempe. It suggested that sub-supercritical CO2 processing for 10 min could be useful alternative technique for preservation of tempe.

Keywords: tempe, sub supercritical CO2, fungistatic effect, preservation

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Authors: Md. Samim Hossain Molla, Md. Mazharul Anwar, Md. Akkas Ali, Mian Sayeed Hassan

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Being detached about 68 years from the mainland, the previous enclaves’ (Chhitmohal) farmers were engaged only in subsistence farming with low agricultural productivity and restricted access to inputs technology. To increase crop productivity for attaining food security by addressing soil status, the experiments were undertaken in 2017 and 2018 in three previous enclaves of Northern Bangladesh i.e. Dasiarchhara of Kurigram district; Dahalakhagrabari of Panchagarh district and Banskata of Lalmonirhat district under On-Farm Research Division, Bangladesh Agricultural Research Institute, Rangpur. The Mustard (var. BARI Sarisha-14)-Boro rice (var. BRRI dhan58)-T. Aman rice (var. BRRI dhan49) cropping pattern using soil test based (STB) fertilizer with cowdung (T1) or recommended fertilizer dose (T2) were tested against existing cropping pattern Fallow-Boro rice (var. BRRI dhan28)-T. Aman rice (var. Swarna) using farmers’ practices fertilizer dose (T3) in six disperse replications at each location maintaining Randomized Complete Block design. Almost all crops yields were relatively higher in T1 followed by T2. Farmers existing pattern with local varieties and imbalance fertilizer (T3) use may be decreased the crop yield. The rice equivalent yield of T1 was 109, 103 and 95% higher than T3 and the gross margin was 164, 153 and 133% higher in T1 than T3 at Dasiarchhara, Dahalakhagrabari and Banskata, respectively. The Benefit Cost Ratio for T1, T2 and T3 were 1.99, 1.78 and 1.28 in Dasiarchhara; 1.93, 1.81 and 1.27 in Dahalakhagrabari and 1.78, 1.71 and 1.25 in Banskata, respectively. There was a remarkable decrease in mineral N, P and K in the topsoil (0–15 cm) of T3 and T2 treatments at Dasiarchhara and Dahalakhagrabari, and a generally less marked decline under the same treatments at Banskata. The same practices (T1) exhibited the greatest nutrients uptake by the test crops. The apparent balance of N, P and K was negative in most cases, where it was less negative in T1 treatment. However, from the experimentation, it is revealed that balanced fertilization (STB) and inclusion of National Agricultural Research Institutes developed improved crops varieties in cropping pattern may increase the crop productivity, farm efficiency and farmer’s income in a remarkable level.

Keywords: cropping pattern, fertilizer management, nutrient balance, previous enclaves

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Authors: Oluseun S. Oyelakin, Olalekan W. Olaniyi

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A field experiment was conducted at Ido town in Ido Local Government Area of Oyo state, Nigeria to determine the effects of intercropping maize (Zea mays L.) with Jack bean (Canavalia ensiformis L.) at different spacing and weeding regimes on crops productivity. The treatments were 2 x 2 x 3 factorial arrangement involving two spatial crop arrangements. Spacing of 75 cm x 50 cm and 90 cm x 42 cm (41.667 cm) with two plants per stand resulted in plant population of approximately 53,000 plants/hectare. Also, Randomized Complete Block Design (RCBD) with two cropping patterns (sole and intercrop), three weeding regimes (weedy check, weeds once, and weed twice) with three replicates was used. Data were analyzed with SAS (Statistical Analysis System) and statistical means separated using Least Significant Difference (LSD) (P ≤ 0.05). Intercropping and crop spacing did not have significant influence on the growth parameters and yield parameters. The maize grain yield of 1.11 t/ha obtained under sole maize was comparable to 1.05 t/ha from maize/jack beans. Weeding regime significantly influenced growth and yields of maize in intercropping with Jack beans. Weeding twice resulted in significantly higher growth than that of the other weeding regimes. Plant height at 6 Weeks After Sowing (WAS) under weeding twice regime (3 and 6 WAS) was 83.9 cm which was significantly different from 67.75 cm and 53.47 cm for weeding once (3 WAS) and no weeding regimes respectively. Moreover, maize grain yield of 1.3 t/ha obtained from plots weeded twice was comparable to that of 1.23 t/ha from single weeding and both were significantly higher than 0.71 t/ha maize grain yield obtained from the no weeding control. The dry matter production of Jack beans reduced at some growth stages due to intercropping of maize with Jack beans though with no significance effect on the other growth parameters of the crop. There was no effect on the growth parameters of Jack beans in maize/jack beans intercrop based on cropping spacing while comparable growth and dry matter production in Jack beans were produced in maize/Jack beans mixture with single weeding.

Keywords: crop spacing, intercropping, growth parameter, weeding regime, sole cropping, WAS, week after sowing

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Jia Zhang, Fengmei Yao, Yanjing Tan

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The accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS-P-YEC (Remote-Sensing-Photosynthesis-Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS-P-YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002-2011. The statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (P < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002-2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.

Keywords: process-based model, C4 crop, maize yield, remote sensing, Northeast China Plain

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Authors: Angesom Gebrezgabiher Tesfay, Afafaw Hailesilasie Tesfay, Muyiwa Samuel Adaramola

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The energy demand boost in Ethiopia urges sustainable fuel options while it is mainly supplemented by traditional biomass and imported conventional fuels. To satisfy the deficiency it has to be sourced from all renewables. Thus identifying resources and estimating potential is vital to the sector. This study aims at an in-depth assessment to quantify, prioritize, and analyze agricultural residue biomass energy and related characteristic forms. Biomass use management and modernization seeks successive information and a clue about the resource quantity and characteristic. Five years of crop yield data for thirteen crops were collected. Conversion factors for their 20 residues are surveyed from the literature. Then residues amount potentially available for energy and their energy is estimated regional, crop-wise, residue-wise, and shares compared. Their potential value for energy is analyzed from two perspectives and prioritized. The gross potential is estimated to be 495PJ, equivalent to 12/17 million tons of oil/coal. At 30% collection efficiency, it is the same as conventional fuel import in 2018. Maize and sorghum potential and spatial availability are preeminent. Cotton and maize presented the highest potential values for energy from application and resource perspectives. Oromia and Amhara regions' contributions are the highest. The resource collection and application trends are required for future management that implicates a prospective study.

Keywords: crop residue, biomass potential, biomass resource, Ethiopian energy

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Hanna Mamo Ergando

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Climate change is already having a severe influence on agriculture, affecting crop yields, the nutritional content of main grains, and livestock productivity. Significant adaptation investments will be necessary to sustain existing yields and enhance production and food quality to fulfill demand. Climate-smart agriculture (CSA) provides numerous potentials in this regard, combining a focus on enhancing agricultural output and incomes while also strengthening resilience and responding to climate change. To improve agriculture production and productivity, the Ethiopian government has adopted and implemented a series of strategies, including the recent agricultural cluster farming that is practiced as an effort to change, improve, and transform subsistence farming to modern, productive, market-oriented, and climate-smart approach through farmers production cluster. Besides, greater attention and focus have been given to wheat production and productivity by the government, and wheat is the major crop grown in cluster farming. Therefore, the objective of this assessment was to examine various opportunities and challenges farmers face in a cluster farming system. A qualitative research approach was used to generate primary and secondary data. Respondents were chosen using the purposeful sampling technique. Accordingly, experts from the Federal Ministry of Agriculture, the Ethiopian Agricultural Transformation Institute, the Ethiopian Agricultural Research Institute, and the Ethiopian Environment Protection Authority were interviewed. The assessment result revealed that farming in clusters is an economically viable technique for sustaining small, resource-limited, and socially disadvantaged farmers' agricultural businesses. The method assists farmers in consolidating their products and delivering them in bulk to save on transportation costs while increasing income. Smallholders' negotiating power has improved as a result of cluster membership, as has knowledge and information spillover. The key challenges, on the other hand, were identified as a lack of timely provision of modern inputs, insufficient access to credit services, conflict of interest in crop selection, and a lack of output market for agro-processing firms. Furthermore, farmers in the cluster farming approach grow wheat year after year without crop rotation or diversification techniques. Mono-cropping has disadvantages because it raises the likelihood of disease and insect outbreaks. This practice may result in long-term consequences, including soil degradation, reduced biodiversity, and economic risk for farmers. Therefore, the government must devote more resources to addressing the issue of environmental sustainability. Farmers' access to complementary services that promote production and marketing efficiencies through infrastructure and institutional services has to be improved. In general, the assessment begins with some hint that leads to a deeper study into the efficiency of the strategy implementation, upholding existing policy, and scaling up good practices in a sustainable and environmentally viable manner.

Keywords: cluster farming, smallholder farmers, wheat, challenges, opportunities

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Authors: Mehmet Savsar

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Several factors affect productivity of Food Processing Assembly Lines (FPAL). Engineers and line managers usually do not recognize some of these factors and underutilize their production/assembly lines. In this paper, a special food processing assembly line is studied in detail, and procedures are presented to illustrate how productivity and efficiency of such lines can be increased. The assembly line considered produces ten different types of freshly prepared salads on the same line, which is called mixed model assembly line. Problems causing delays and inefficiencies on the line are identified. Line balancing and related tools are used to increase line efficiency and minimize balance delays. The procedure and the approach utilized in this paper can be useful for the operation managers and industrial engineers dealing with similar assembly lines in food processing industry.

Keywords: assembly lines, line balancing, production efficiency, bottleneck

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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: Vaibhav Baliyan, Shweta Mehrotra, S. S. Parihar

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The agricultural productivity is challenged by climate change and depletion in natural resources, including water and land, which significantly affects the crop yield. Wheat is a thermo-sensitive crop and is prone to heat stress. High temperature decreases crop duration, yield attributes, and, subsequently, grain yield and biomass production. Terminal heat stress affects grain filling duration, grain yield, and yield attributes, thus causing a reduction in wheat yield. A field experiment was conducted at Indian Agricultural Research Institute, New Delhi, for two consecutive rabi seasons (2017-18 and 2018-19) on six varieties of wheat (early sown - HD 2967, HD 3086, HD 2894 and late sown - WR 544, HD 3059, HD 3117 ) with three moisture regimes (100%, 80%, and 60% ETc, and no irrigation) and six sowing dates in three replications to investigate the effect of different moisture regimes and sowing dates on growth, yield and water use efficiency of wheat for development of best management practices for mitigation of terminal heat stress. HD3086 and HD3059 gave higher grain yield than others under early sown and late sown conditions, respectively. Maximum soil moisture extraction was recorded from 0-30 cm soil depth across the sowing dates, irrigation regimes, and varieties. Delayed sowing resulted in reducing crop growth period and forced maturity, in turn, led to significant deterioration in all the yield attributing characters and, there by, reduction in yield, suggesting that terminal heat stress had greater impact on yield. Early sowing and irrigation at 80% ETc resulted in improved growth and yield attributes and water use efficiency in both the seasons and helped to some extent in reducing the risk of terminal heat stress of wheat grown on sandy loam soils of semi-arid regions of India.

Keywords: sowing, irrigation, yield, heat stress

Procedia PDF Downloads 59