دانلود و نمایش مقالات مرتبط با Maize::صفحه 1
دانلود بهترین مقالات isi همراه با ترجمه فارسی 2

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - Maize

تعداد مقالات یافته شده: 12
ردیف عنوان نوع
1 Monitoring crop phenology with street-level imagery using computer vision
پایش فنولوژی محصول با تصاویر سطح خیابان با استفاده از بینایی ماشین-2022
Street-level imagery holds a significant potential to scale-up in-situ data collection. This is enabled by combining the use of cheap high-quality cameras with recent advances in deep learning compute solutions to derive relevant thematic information. We present a framework to collect and extract crop type and phenological information from street level imagery using computer vision. Monitoring crop phenology is critical to assess gross primary productivity and crop yield. During the 2018 growing season, high-definition pictures were captured with side- looking action cameras in the Flevoland province of the Netherlands. Each month from March to October, a fixed 200-km route was surveyed collecting one picture per second resulting in a total of 400,000 geo-tagged pictures. At 220 specific parcel locations, detailed on the spot crop phenology observations were recorded for 17 crop types (including bare soil, green manure, and tulips): bare soil, carrots, green manure, grassland, grass seeds, maize, onion, potato, summer barley, sugar beet, spring cereals, spring wheat, tulips, vegetables, winter barley, winter cereals and winter wheat. Furthermore, the time span included specific pre-emergence parcel stages, such as differently cultivated bare soil for spring and summer crops as well as post-harvest cultivation practices, e.g. green manuring and catch crops. Classification was done using TensorFlow with a well-known image recognition model, based on transfer learning with convolutional neural network (MobileNet). A hypertuning methodology was developed to obtain the best performing model among 160 models. This best model was applied on an independent inference set discriminating crop type with a Macro F1 score of 88.1% and main phenological stage at 86.9% at the parcel level. Potential and caveats of the approach along with practical considerations for implementation and improvement are discussed. The proposed framework speeds up high quality in-situ data collection and suggests avenues for massive data collection via automated classification using computer vision.
keywords: Phenology | Plant recognition | Agriculture | Computer vision | Deep learning | Remote sensing | CNN | BBCH | Crop type | Street view imagery | Survey | In-situ | Earth observation | Parcel | In situ
مقاله انگلیسی
2 Introducing an aflatoxin-safe labeling program in complex food supply chains: Evidence from a choice experiment in Nigeria
معرفی یک برنامه برچسب زدن بدون آفلاتوکسین در زنجیره های تأمین مواد غذایی پیچیده: شواهدی از یک آزمایش انتخاب در نیجریه-2021
Food contaminated with aflatoxins is one of the more prominent food safety issues facing developing countries. These toxins impose an immense burden on countries that have to deal with the repercussions of the contamination. Repercussions include increased public health concerns, increased health care expenditures, and other economic tolls. To alleviate these food safety concerns, the implementation of aflatoxin-safe certification can potentially incentivize and elevate food safety standards. This study uses a discrete choice experiment approach to assess if traders are willing to pay a price premium for aflatoxin-safe maize and whether such a premium varies across their market channels. Results indicate that maize traders who sell to other traders, large feed mills, food companies, and retailers exhibit a higher willingness to pay (WTP) for aflatoxin-safe certification compared to those who sell to small feed mills and consumers. Relevant policy implications are discussed.
Keywords: Aflatoxin contamination | Aflatoxin safe certification | Traders preferences | Traders willingness to pay | Maize, Nigeria
مقاله انگلیسی
3 In-field automatic detection of maize tassels using computer vision
تشخیص خودکار کاکل ذرت با استفاده از بینایی ماشین-2021
The heading stage of maize is an important period during its growth and development and indicates the beginning of its pollination. In this regard, an automated method for maize tassel detection is highly important to monitor maize growth. However, the recognition of maize heading stage mainly relies on visual evaluation. This method presents some limitations, such as expensive and subjective. This work proposed a novel method for automatic tassel detection. In the proposed algorithm, a color attenuation prior model was used to model the scene depth of saturation graph to remove image saturation. An Itti visual attention detection algorithm was used to detect the area of interest. Texture features and vegetation indices were used to develop a classification model to eliminate false positives. Pictures were captured using a commercial camera for two years to verify the stability of the proposed algorithm. Three indices were calculated to quantitatively assess and rate the algorithms. Experimental results show that the proposed method outperforms other existing methods, and its recall, precision, and F1 measure values are 86.30%, 91.44%, and 88.36%, respectively. Results indicate that the proposed method can effectively detect maize tassels in field images and remain stable with time.© 2020 China Agricultural University. Production and hosting by Elsevier B.V. on behalf of KeAi. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Maize tassel detection | Texture feature | Vegetation index | Saliency based
مقاله انگلیسی
4 استفاده از روش GIS-AHP برای ارزیابی مستعد بودن زمین در زراعت ذرت در منطقه نیمه خشک ، ایران
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 17
هدف از این مطالعه تهیه نقشه های در زمینه استعداد زمین در زراعت ذرت در خاک های آهکی و شور در دشت مرودشت ، ایران است. برای تخمین وزنی ویژگی های خاک ، اقلیم و توپوگرافی از روش چندمعیاره ای از فرآیند سلسله مراتبی تحلیلی (AHP) استفاده شده است. طبق نتایج، بافت خاک بیشترین ضریب وزنی ویژه (0.20) را در زراعت ذرت نشان داد و پس از آن، هدایت الکتریکی (121/0) ، شیب (1 2 0) و pH (1111/0) بیشترین ضریب وزنی را نشان داد. نقشه مستعد بودن اراضی نشان داد که 38.72٪ (76.646.7 هکتار) از اراضی کشاورزی مورد مطالعه، خاک مستعدی در تولید ذرت داشتند یعنی در طبقه مناسب ، 26.89٪ (53216.0 هکتار) در طبقه متوسط و 9/23٪ (47473 هکتار) در طبقه کمی مناسب قرار گرفتند. حدود ٪ 41/10 (4/2086٪) منطقه مورد مطالعه مناسب زراعت ذرت نبود. می توان دریافت که داده های مربوط به ویژگی های خاک ، آب و هوا و توپوگرافی به نظر متخصصان محلی، اولین قدم در کشت محصولات زراعی است.
کلمات کلیدی: داده های خاک | مدل سازی | توپوگرافی | روش AHP | GIS | مرودشت
مقاله ترجمه شده
5 Water-saving agriculture can deliver deep water cuts for China
کشاورزی با صرفه جویی در آب می تواند کاهش عمیق آب را برای چین به همراه آورد-2020
China is working hard to reconcile growing demands for freshwater with already oversubscribed renewable water resources. However, the knowledge essential for setting and achieving the intended water consumption cuts remains limited. Here we show that on-farm water management interventions such as improved irrigation and soil management practices for maize cultivation can lead to substantial water consumption reductions, by a simulated total of 28–46 % (7–14 billion m3/year) nationally, with or without the impacts of climate change. The water consumption cut is equivalent to 16–31 % of the ultimate capacity of the South-North Water Transfer Project. Much of the reduction is achievable at the populous and water-stressed North China Plain and Northeast China. Meanwhile, the interventions can increase maize production by an estimated 7–15 %, meeting 22–28 % of demand increase projected for 2050. The water management and food production improvements obtained are crucial for achieving multiple Sustainable Development Goals (SDGs) related to water, land, and food in China and far beyond.
Keywords: Deep water saving | Irrigation water consumption | Integrated on-farm water management | interventions
مقاله انگلیسی
6 Maize production and environmental costs: Resource evaluation and strategic land use planning for food security in northern Ghana by means of coupled emergy and data envelopment analysis
تولید ذرت و هزینه های زیست محیطی: ارزیابی منابع و برنامه ریزی استراتژیک کاربری اراضی برای امنیت غذایی در شمال غنا با استفاده از تجزیه و تحلیل آمیخته و پوشش داده ها-2020
This paper applies an integrated methodology which is constituted of the following: (i) the Emergy-Data Envelopment Analysis (EM-DEA), (ii) environmental Cost-Benefit Analysis (CBA), (iii) Value Chain Analysis (VCA), and (iv) Sustainability Balanced Scorecard (SBSC) approaches, -to support multicriteria decision analysis (MCDA) for strategic agricultural land use planning, which could contribute to improve food security in northern Ghana. Five scenarios of land use and resource management practices for maize production were modelled. The business-as-usual scenario was based on primary data, which were collected using semi-structured questionnaires administered to 56 small-scale maize farmers through personal interviews. The dominant land use was characterised by an external input ≤12 kg/ha/yr inorganic fertilizer with/without the addition of manure in rainfed maize systems. The project scenarios were based on APSIM simulations of maize yield response to 0, 20, 50 and 100 kg/ha/yr urea dosages, with/without supplemental irrigation. The scenarios were dubbed as follows: (1) no/low input systems were denoted by Extensive0, Extensive12, and Intercrop20, and (2) moderate/high input systems were denoted by Intensive50, and Intensive100. The EM-DEA approach was used to assess the resource use efficiency (RUE) and sustainability in maize production systems, Ghana. The measured RUE and sustainability were used as a proxy for further analyses by applying the environmental CBA and VCA approaches to calculate: (a) the environmental costs of producing maize, i.e. resource use measured as total emergy (U), and (b) benefits from the yielded maize, i.e. (b i) food provision from grain measured in kcal/yr, and (b ii) potential electricity (bioenergy) which could be generated from residue measured in MWh/yr. The information which was derived from the applications of the EM-DEA, CBA and VCA approaches was aggregated by applying the SBSC approach to do a sustainability appraisal of the scenarios. The results show that, when labour and services are included in the assessment of RUE and sustainability, Intercrop20 and Intensive50 achieved greater marginal yield, better RUE, sustainability and appraisal score. The same scenarios caused lesser impacts in terms of expansion of area cultivated compared to Extensive0 and Extensive12. Meanwhile the impacts of Intercrop20 and Intensive50 in terms of ecotoxicity, emissions, and demand for resources (energy, materials, labour and services) were lesser compared to Intensive100. The implications of the various scenarios are discussed. The environmental performance of the scenarios are compared to maize production systems in other developing regions in order to put this study within a broader context. We conclude that, the EM-DEA approach is useful for assessing RUE and sustainability of agricultural production systems at farm and regional scales, as well as in connecting the management planning level and regional development considerations.
Keywords: Food security | Sustainable agriculture | Strategic land use planning | Emergy-Data envelopment analysis | Environment-biomass-food-energy nexus | Sub-Saharan Africa
مقاله انگلیسی
7 Pixel-level aflatoxin detecting based on deep learning and hyperspectral imaging
تشخیص آفلاتوکسین در سطح پیکسل مبتنی بر یادگیری عمیق و تصویربرداری hyperspectral-2019
Aflatoxin is a kind of virulent and strong carcinogenic substance, and it is found widely in peanut, Maize and their agricultural products. In order to detect Aflatoxin in peanut, we first built a hyperspectral imaging system using a grating module, SCOMS camera, and electric displacement platform, and acquired 146 hyperspectral images cubes of 73 peanut samples before and after contaminated with aflatoxin. Then, we proposed a reshaped image method of pixel spectral for the CNN method. By studying on random selection data-sets and comparing with different identification models, we found that: (1) Reshape image established by the pixel level spectral is good enough for aflatoxin detected problems, overall recognition rate reached above 95% on pixel-level. (2) The deep learning method is worked well and it is better than traditional identification models, not only on the pixel level but also on the kernel identification. The recognition rate of above 90% on the kernel level can quickly use in sorting machines design.
Keywords: Aflatoxin | Deep learning | CNN | Reshape image of pixel spectral | Hyperspectral images
مقاله انگلیسی
8 Potential benefits of drought and heat tolerance for adapting maize to climate change in tropical environments
منافع بالقوه خشکسالی و حد گرما برای سازگاری ذرت با تغییرات آب و هوایی در محیط های گرمسیری-2018
Climate change and population growth pose great challenges to the food security of the millions of people who grow maize in the already fragile agricultural systems in tropical environments. There is an urgent need for maize varieties that are both drought and heat tolerant given the already prevailing drought and heat stress levels in many tropical environments, which are set to exacerbate with climate change. In this study, the crop growth simulation model for maize (CERES-Maize) was used to quantify the impact of climate change on maize and the potential benefits of incorporating drought and heat tolerance into the commonly grown (benchmark) maize varieties at six sites in Eastern and Southern Africa and one site in South Asia. Simulation results indicate that climate change will have a negative impact on maize yield at all the sites studied but the degree of the impact varies with location, level of warming and rainfall changes. Combined hotter and drier climate change scenarios (involving increases in warming with a reduction in rainfall) resulted in greater average simulated maize yield reduction (21, 33 and 50% under 1, 2 and 4 °C warming, respectively) than hotter only climate change scenarios (11, 21 and 41%, respectively). Incorporating drought, heat and combined drought & heat tolerance into benchmark varieties increased simulated maize yield under both the baseline and future climates. The average simulated benefit from combined drought & heat tolerance was at least twice that of heat or drought tolerance and it increased with the increase in warming levels. The magnitude of the simulated benefits from drought tolerance, heat tolerance and combined drought & heat tolerance and potential acceptability of the varieties by farmers varied across sites and climate scenarios indicating the need for proper targeting of varieties where they fit best and benefit most. It is concluded that incorporating drought and heat tolerance into maize germplasm has the potential to offset predicted yield losses and sustain maize productivity under climate change in vulnerable sites.
keywords: Climate change |Maize |Drought tolerance |Heat tolerance |Tropical environments
مقاله انگلیسی
9 To mulch or to munch? Big modelling of big data
کود یا جویدن؟ مدل سازی بزرگ داده های بزرگ-2017
African farmers are poorly resourced, highly diverse and aground by poverty traps making them rather impervi ous to change. As a consequence R4D efforts usually result in benefits but also trade-offs that constraint adoption and change. A typical case is the use of crop residues as mulches or as feedstock. Here we linked a database of household surveys with a dynamic whole farm simulation model, to quantify the diversity of trade-offs from the alternative use of crop residues. Simulating all the households in the survey (n = 613) over 99 years of syn thetic climate data, showed that benefits and trade-offs from “mulching or munching” differ across agro-ecolo gies, and within agro-ecologies across typologies of households. Even though trade-offs between household production or income and environmental outcomes could be managed; the magnitude of the simulated benefits from the sustainable intensification of maize-livestock systems were small. Our modelling framework shows the benefits from the integration of socio-economic and biophysical approaches to support the design of develop ment programs. Our results support the argument that a greater focus is required on the development and diver sification of farmers livelihoods within the framework of an improved understanding of the interconnectedness between biophysical, socio-economic and market factors.
Keywords:APSIM|Whole farm modelling|Integrative analyses|Farm diversity
مقاله انگلیسی
10 Nutritional deterioration of stored Zea mays L: along supply chain in southwestern Ethiopia: Implication for unseen dietary hunger
وخامت غذایی ذخیره شده ذرت در طول زنجیره تامین در جنوب غربی اتیوپی: کاربرد در زمینه گرسنگی در رژیم غذایی نهان-2017
Maize plays a key role in household food security in southwestern Ethiopia, but its benefits have been negated by high post-harvest losses. Previous loss assessment and management studies have focused mainly on quantity losses. This study was therefore designed to assess nutritional quality losses of stored maize along the supply chain in Jimma Zone, southwestern Ethiopia. Three districts representing po tential maize producers and different agro-ecological regimes for maize production were selected for analyses. Sample collection started at harvest and continued for six months at two-month intervals from 21 selected actors along the supply chain. The experiment was conducted for two seasons, and a total of 72 samples were collected during each season. Both nutritional and anti-nutritional analyses were carried out following the international standards of the Association of Official Analytical Chemists. Data were analysed using SAS software (version 9.2) using a general linear model (GLM). The result revealed that moisture content significantly decreases (P < 0.05) as storage duration increases under different actors and agro-ecological conditions. But, showed increment during the final months under farmers storage conditions. In addition, moisture content at the loading stage was not optimal for safe storage. Crude protein, crude fat, carbohydrate, and calorific value content significantly decreased (P < 0.05) as the storage duration increased, but fibre, ash, and major mineral (Ca, Zn, and Fe) content increased significantly over the storage period. Phytate and tannin content varied with storage duration and agro ecological setting. Storing maize under traditional conditions along the supply chain resulted in sub stantial quality losses. This has great implications for nutrition insecurity and unrecognized under nourishment in the society. Additionally, substantial increases in fibre content above the optimum have important effects on nutrient absorption. There is thus a need to develop and disseminate appropriate storage technologies that minimize quality loss in maize stores.
Keywords: Agro-ecology | Quality loss | Nutrition | Storage duration | Stored maize
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 3985 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 3985 :::::::: افراد آنلاین: 81