این مقاله انگلیسی ISI در نشریه IEEE در 10 صفحه در سال 2021 منتشر شده و ترجمه آن 30 صفحه میباشد. کیفیت ترجمه این مقاله ویژه – طلایی ⭐️⭐️⭐️ بوده و به صورت کامل ترجمه شده است.

نوشته دانلود ترجمه مقاله توزیع هوشمند محصولات تازه کشاورزی در شهر هوشمند (IEEE – 2021) (ترجمه ویژه – طلایی ⭐️⭐️⭐️) اولین بار در ترجمه فا پدیدار شد.

این مقاله انگلیسی ISI در نشریه الزویر در 8 صفحه در سال 2021 منتشر شده و ترجمه آن 11 صفحه میباشد. کیفیت ترجمه این مقاله ویژه – طلایی ⭐️⭐️⭐️ بوده و به صورت کامل ترجمه شده است.

مشخصات مقاله انگلیسی
فرمت مقاله انگلیسی	pdf و ورد تایپ شده با قابلیت ویرایش
سال انتشار	2021
تعداد صفحات مقاله انگلیسی	8 صفحه با فرمت pdf
نوع مقاله	ISI
نوع نگارش	مقاله پژوهشی (Research article)
نوع ارائه مقاله	ژورنال
رشته های مرتبط با این مقاله	کشاورزی، منابع طبیعی
گرایش های مرتبط با این مقاله	اقتصاد منابع طبیعی و محیط زیست، آبزی پروری، شیلات
چاپ شده در مجله (ژورنال)	پروسدیا پژوهش حمل و نقل – Transportation Research Procedia
کلمات کلیدی	جذابیت سرمایه گذاری، آبزی پروری دریایی، معیار، ارزیابی
کلمات کلیدی انگلیسی	Investment Attractiveness – Marine Aquaculture – Criteria – Assessment
ارائه شده از دانشگاه	دانشگاه فناوری دریایی دولتی کرچ ، روسیه
نویسندگان	Natalya Logunova, Tatyana Glechikova , Alexander Kotenev
شناسه شاپا یا ISSN	2352-1465
شناسه دیجیتال – doi	https://doi.org/10.1016/j.trpro.2021.02.051
ایمپکت فاکتور(IF) مجله	1.285 در سال 2020
شاخص H_index مجله	25 در سال 2021
شاخص SJR مجله	0.476 در سال 2020
بیس	نیست ☓
مدل مفهومی	ندارد ☓
پرسشنامه	ندارد ☓
متغیر	ندارد ☓
رفرنس	دارای رفرنس در داخل متن و انتهای مقاله ✓
کد محصول	11752
لینک مقاله در سایت مرجع	لینک این مقاله در نشریه Elsevier
نشریه الزویر

نوشته دانلود ترجمه مقاله جذابیت سرمایه گذاری منطقه برای محصولات دریایی (ساینس دایرکت – الزویر 2021) (ترجمه ویژه – طلایی ⭐️⭐️⭐️) اولین بار در ترجمه فا پدیدار شد.

فهرست مطالب:

 چکیده
مقدمه
توصیف منطقه مورد مطالعه
کشاورزی دامنه ای
نگاهی بر مدل حوزه ای WEPP
روش
داده های هواشناسی
داده های هیدرولوژیک
اندازه گیری میدانی خواص خاک
مدل ارتفاع رقومی برای تعیین خصوصیات ابخیز
داده های ماهواره ای
کاربرد مدل wepp
ورودی های مدل
ارزیابی عملکرد مدل
معیارهای ارزیابی مدل
نتایج و بحث
شبیه سازی رواناب
آنالیزهای حساسیت
شبیه سازی تولید رسوب
ارزیابی سناریوهای مدیریت ساختمان و پوشش بنیان
مدیریت کارامد حوزه
ارزیابی عملیات مدیریت زراعی
تیمار شخم
مدیریت ساختمانی
اثر مجموعه بهترین عملیات مدیریتی و ساختارهای حفاظتی
نتیجه گیری

بخشی از ترجمه:

مدل WEPP تولید رسوب و رواناب را به طور رضایت بخشی در شرایط شیب و بارش زیاد حوزه با ضریب ناش سات کلیف بیش از 0.87 درصد و انحراف معیار 5.23 شبیه سازی کرد. مقایسه بین مقادیر شبیه سازی و اندازه گیری شده تولید رسوب و رواناب نشان داد که مدل مقادیر بالا را کم تر از مقدار واقعی براورد می کند. مطالعات بیشتر در خصوص اجزای زیزسطحی پارامتر های مدل می تواند برای بهبود قدرت براورد مدل مفید باشد.
نتایج شبیه سازی نشان می دهد که سویا و بادام زمینی پتانسل تعویض با برنج دیم برای کاهش تولید رسوب به ترتتیب تا 29.60 و 27.70 دارند.
نتایج شبیه سازی نشان می دهد که جایگزینی عملیات شخم سنتی با سیستم بدون شخم و کولتیواتور زارعی می تواند منجر به کاهش تولید رسوب تا 21.88 و 13.14 % شود.
نتایج شبیه سازی نشان می دهد که نصب 26 سد سنگی متخلخل و موانع رسوب گیر در حوزه امروی می تواند تولید رسوب را تا 54.6درصد کاهش دهد.
نتایج به وضوح نشان داد که مدیریت شخم وزراعی و کنترل سازه ای به تنهایی قادر به کاهش تولید رسوب ورواناب نمی باشند. شبیه سازی مجموعه روش های کنترلی بیولوژیکی، شخم و سازه ای دارای پتانسیل کاهش تولید رسوب تا 78.40% می باشد. تناوب کشت ذرت با سویا در ارتفاعات برای کاهش فرسایش خاک و رفع نیازهایی غذایی لازم است.
مدل واسنجی و اعتبارسنجی شده WEPP می تواند به طور موفقیت آمیزی برای توسعه راهبرد های بیولوژیک و ساختمانی در شرایط با شیب و بارش زیاد شرق هیمالیا مورد استفاده قرار گیرد.

بخشی از مقاله انگلیسی:

1. Introduction Food security and environment protection are the most challenging task the world is facing today. Land and water resources are important components of environment. Degradation of the quality of these resources will affect the quality of the environment. Major portion of the food consumed by human being comes from the land. Due to demographic pressure land use is intensified and erosion prone area is brought under subsistence agriculture leading to land degradation. Soil erosion is an irreversible phenomenon causing land degradation and deterioration of surface water quality. It is caused due to inappropriate land use and poor management. Soil degradation is responsible for making 0.3–0.8% of the world’s arable land unsuitable for agricultural production every year and an additional 200 million ha of cropped area would be required over the next 30 years to feed the increasing population (den Biggelaar et al., 2004; Lafond et al., 2006). Therefore, this precious finite resource must be safeguarded against all kinds of degradation and deterioration for sustainability of agricultural production and environment protection. In India, out of the total geographical area of 329 million ha, approximately 145 million ha of the total land resource is subjected to various degrees of wind and water erosion, which cause a loss of 5.3 million Mg of soil every year. In eastern Himalayan region of India, soil erosion by water is a major factor causing land degradation. About one third area of the region suffers from various forms of land degradation problems (Sehgal and Abrol, 1994). Practice of traditional slash-and-burn agriculture on steep slopes, intense rainfall, undulating and sloppy land surface compounds the problem many folds. About 386 900 ha area in the region is affected by shifting cultivation and as high as 76.6 Mg ha1 yr1 of soil is lost due to this system of farming (Satapathy, 1996). Eighty percent area is under threat of moderate to severe erosion. To combat the threat of land degradation, we need to understand physical process of erosion in relation of topography, land use and management. Watershed being a natural drainage unit should form the basis for planning various land uses and conservation measures to optimize the use of soil and water resources to increase and sustain agricultural production. In order to develop a comprehensive plan for soil and water conservation, it is essential to estimate runoff and soil loss resulting from different crop and structure-based management practices. Among the available tools for soil erosion assessment, simulation models are quite important because appropriate models can be used to evaluate a variety of management scenarios without costly and time consuming field tests (Pieri et al., 2007). In recent past a trend of testing and using physical process based runoff and soil erosion prediction models both at field as well as at watershed scales has gained momentum. These physical process based models, often with an explicit attempt to describe runoff and erosion processes, are better equipped to evaluate the impacts of management interventions and help make management decisions aimed at preserving land productivity and environment quality (Yu and Rosewell, 2001). Before application, such models need to be properly calibrated and validated using measured hydrologic data of the watershed. Lack of reliable field-measured data for calibration and validation of models is the major limitation for their application. Runoff and soil loss data can be obtained through field measurements and watershed attributes could be derived using remotely sensed data and digital elevation model of the watershed (Amore et al., 2004; Baigorria and Romero, 2007). In hilly watersheds spatial and temporal variability in terms of soil, land use/land cover, topography, rainfall and biotic interventions are large. The runoff, sediment, fertilizers, pesticides and other pollutants, resulting from the agricultural activities cause deterioration of quality of surface and ground water. Methods for identification of sources of pollutants and their quantification are essential for their control. Distributed parameter watershed models are applicable for this type of assessment. Review of literatures revealed that CREAMS (Knisel, 1980), ANSWERS (Beasley et al., 1982), SWRRB (Arnold et al., 1990), AGNPS (Young et al., 1989), EPIC (Sharpley and Williams, 1990) and SWAT (Arnold et al., 1998) are probably the most important models and widely used worldwide for hydrologic and pollutants transport modeling. The main erosion components of these models are based on concepts originally formulated in the Universal Soil Loss Equation (USLE) model (Wischmeier and Smith, 1978), which relate the total amount of soil loss to six factors: rainfall erosivity, soil texture, slope length and grade, soil cover and conservation practice. Runoff components of these models use the SCS–CN method to predict runoff (Bingner, 1990; Schröder, 2000). Among these models only SWAT, AGNPS and ANSWERS are the distributed parameters physically based watershed scale models mostly used for low slope conditions (Arnold et al., 1998; Bingner et al., 1992; Schröder, 2000). Any model used for computing potential soil loss from an area must deal with a large number of parameters concerning vegetation, management, soil, topography and climate (Amore et al., 2004). Performance of a model depends upon number of parameters it is considering for runoff and soil loss computation based on scientific theory. Performance of such model may not differ much on different scales. Topography and nature of rainfall are quite dominant parameters in generation of runoff and soil erosion particularly in hilly watersheds. Water Erosion Prediction Project (WEPP) is one such process based model developed for estimating soil loss, and selecting catchment’s management practices for conservation planning for field and small catchments (Flanagan and Nearing, 1995; Lane et al., 1997). The model was used successfully world wide (Yu and Rosewell, 2001; Huang et al., 1996; Amore et al., 2004; Pieri et al., 2007; Baigorria and Romero, 2007; Shen et al., 2009; Shen et al., 2010) including India (Pandey et al., 2008) for estimating runoff and soil loss from different land use and crop management practices. Performance of the WEPP model was compared with the ANSWERS (Bhuyan et al., 2002), EPIC (Bhuyan et al., 2002), and SWAT (Shen et al., 2010). They found that the performance of the WEPP model was at par with the ANSWERS and better than the EPIC and SWAT in simulating different management scenario for reduction of sediment yield.

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فهرست مطالب:

 چکیده
۱ مقدمه
۲ مواد و روش ها
۲ ۱ مواد میوه
۲ ۲ تفکیک کلاس های رسیدگی
۲ ۳ پایش نرمی گوشته طی فرایند پس از برداشت
۲ ۴ آنالیز داده ها
۳ نتایج و بحث
۳ ۱تفکیک کلاس های رسیدگی در زمان برداشت
۳ ۲ همبستگی بین پارامتر ها
۳ ۳ پایش نرم شدگی گوشته پس از برداشت
۴ نتیجه گیری

بخشی از ترجمه:

تعیین زمان بهینه برداشت هلو یک فرایند حیاتی است زیرا تنظیم کننده سرعت نرم شدن طی دوره پس از برداشت بوده و از این رو تعیین کننده طول عمر بالقوه نگه داری میوه است.تفکیک هلو ها با سفتی و مقاومت گوشته متفاوت در زمان برداشت، که در دامنه بین ۱۰۰ و ۴۰ نیوتون تعیین می شود می تواندبا شاخص های IAD و زاویه رنگ زمینه صورت پذیرد. بین این دو شاخص، IADزمانی که برای کل میوه با سوزن تعیین شد دارای همبستگی بالایی بود.تعیین فشار تک محوری همبستگی ضعیف تری را با ویژگی های اپتیکی پوست نشان داد.
هنگامی که هلو به مرحله رسیدگی می رسد، که این فرایند معمولا در آخرین بخش زنجیره تجاری رخ میدهد، زاویه رنگی زمینه یک شاخص خوب و معتبر از خواص مکانیکی میوه نخواهد بود زیرا این شاخص تنها اندکی بعد از برداشت تغییر می کند در حالی که IAD همبستکی نزدیکی با بافت میوه دارد.در این دامنه سفتی،سوزن قادر به تعین تغییرات سفتی نخواهد بود زیرا میوه بسیار نرم است. در حالی که مقاومت فشاری و پیستون ۷.۹ میلی متری قادر به تعیین این تغییرات هستند.
نتایج ما به وضوح نشان می دهد که رفتار رسیدگی یکی از مشخصه های اصلی هر رقم بوده و این که این رفتاررا بایستی با روش های مفید و جدید از حیث دامنه سفتی نمونه ها پایش کرد. این رویکرد موجب تسهیل در برنامه ریزی روش های مناسب پس از برداشت شده و به نوبه خود کیفیت محصول را ارتقا می بخشد.

بخشی از مقاله انگلیسی:

1. Introduction Predicting thepotentiallifespanof apeachalong the commercial chain is crucial to planning the storage, transport, and postharvest handling and selling to guarantee high fruit quality and consumer satisfaction. A first point to be considered is the fruit physiological state at harvest because peach shelf-life performance is heavily determined by its ripeness at this key stage (Ruiz-Altisent et al., 2006). One of the most important challenges for the peach industry is the segregation at harvest of fruit into homogeneous groups in terms of state of ripeness. Tijskens et al. (2007) highlighted the importance of grading individual fruit at harvest into classes of usability and of selecting fruit with different ripeness stages for different market segments on the basis of a reliable prediction of their softening rate. The goal is to guarantee a flesh firmness adequate to transport and sufficient ripening potential to reach good eating quality. Commercially, a common criterion for distinguishing immature from mature fruit is the visual evaluation of the ground skin color (Kader, 1999; Zerbini et al., 1994; Tijskens et al., 2007). Although separating peaches on the basis of comparable visual appearance is a common and inexpensive method, the segregation of batches with similar postharvest life potential is a major technical challenge. There are two main difficulties in using this simple approach: first, the ground color of the peach in the new cultivars is masked by the covering blush, and second, the flesh typologies of new peach cultivars do not demonstrate equal behavior, particularly the stony hard (Yoshida, 1970) and non-melting flesh cultivars. Unlike the melting flesh cultivars, these genotypes do not exhibit the melting period of softening, which is marked by a strong decline in firmness, increased solubility of both loosely bound pectins and matrix glycans, and decreases in the numbers of tightly bound molecules (Brummell et al., 2004). Peach flesh firmness has been traditionally determined by the Magness–Taylor pressure test using a 7.9 mm plunger, and this is the most popular method in the peach industry as well as for postharvest studies. When harvest time is near, fruit are sampled at the orchard, and then an appropriate flesh firmness score is associated with a ground skin color. In this way, the skin ground color of the fruit becomes a reliable and non-destructive indicator of the flesh firmness and therefore of its potential market life. There are high correlations between surface ground color and physiological maturity in peach and nectarine (Kader, 1999), and the hue angle (h◦) in particular has been shown to be highly informative and closely associated with ripeness (Ferrer et al., 2005). It has also been observed, however, that the same h◦ could be associated with different levels of firmness because the fruit is influenced by the light environment in which it develops (Lewallen and Marini, 2003). This maturity indicator should therefore be used with caution. Recently, the IAD (difference of fruit absorbance spectra (A) at two wavelengths IAD = A670 − A720), determined nondestructively using a portable device called Delta-A instrument (Sinteleia, Bologna, Italy), has been shown to be a reliable method for assessing ripeness (Ziosi et al., 2008). High correlations between IAD and ripeness level have been reported for peach (Ziosi et al., 2008), prune (Infante et al., 2011a), and Japanese plum (Infante et al., 2011b). The IAD of the skin is especially informative in those cultivars where the covering color does not allow the ground color to be viewed. Herrero-Langreo et al. (2012) combined chlorophyllrelated optical indexes and low mass impact (LMI) to successfully assess peach maturity using the mean values of sequential harvest dates. In peach, ripeness is a complex process that cannot be fully characterized by a single determination; there are many parameters that change during ripening. In the fresh peach industry, the most limiting factors offruit quality along the commercial chainare those dealing with the mechanical properties ofthe flesh and particularly with the softening speed. The evaluation of different methods to assess flesh firmness at harvest will improve the quality and homogeneity of fresh peaches in the marketplace. In addition, there is no knowledge of the mechanical properties of the newer typologies of flesh or of their evolution on-tree and at postharvest, both of which are cultivar-dependent traits; this lack of knowledge makes it essential to test alternative methods for determining firmness. The optical properties of the skin, measured either as the h◦ of the ground color or as IAD, are both non-destructive and reliable indicators of the physiological age of a fruit. The proposed hypothesis of this study is that flesh firmness determined by means of a puncture test with a 7.9 mm plunger is not correlated with these indicators in peaches of different flesh typology, thereby making it necessary to evaluate alternative methods of texture assessment. 2. Materials and methods 2.1. Fruit material Three peach cultivars, all characterized by the visibility of their ground color, were evaluated: the melting flesh genotypes ‘Ryan Sun’ and ‘Sweet September’ and the non-melting ‘Kakamas’. Fruit was harvested from a commercial orchard located in the Central Valley of Chile. Fifteen trees of each variety, uniform for production, were selected. The fruit was sequentially harvested every 2–3 days for a total of 240 samples. Fruit ripeness was established visually at the orchard, and fruit was harvested into separate batches, based on the ground color of the skin. Afterwards, the fruit was transported to the lab and was re-classified under white light conditions into four ground color levels that represent the ripeness classes used in this trial: M1 (green), M2 (green yellow), M3 (yellow) and M4 (yellow orange), containing 60 fruit each.

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فهرست مطالب:

 چکیده
مقدمه
روش های انتخاب مقاومت جوانه زنی قبل از برداشت در مرکز تحقیقات غلات
عدد نزولی هگبرگ و ثبت رقم
نشان گر های مولکولی DNA
نتیجه گیری

بخشی از ترجمه:

ارقام با سطوح بالا تا متوسط مقاومت به جوانه زنی قبل از برداشت بر اساس خواب RL4137 در کلاس بازاری CWRSمنتشر شده اند . اگر چه ارقام سفید بذر بر اساس خواب مشتق از RL4137  با استفاده از مکانیسم خواب مستقل از رنگ بذر منتشر شده اند ارقام واریته های سفید بذر Snowbird و Snowstar دارای سطوح بالای مقاوت PHS در مقایسه با برخی ارقام با رنگ بذر قرمز بوده اند. روش های فیلترینگ به طور کلی امکان انتخاب با سطوح بالای مقاومت PHS را بدون کاهش معنا دار در واریانس جمعیت برای صفات مهم دیگر می دهد. تولید ژن های جدید از ژن ئلاسم های غیر سازگار برای صفات مطلوب زراعی نظیر عملکرد دانه ی بالا و مقاومت به بیماری نظیر پوزاریم موجب شده است تا سطوح CWRS و  CWHWS و CWAD سطوح بالای مقاومت به PHS را داشته باشند این یک چالش فزاینده برای شناسایی نشانگر های مولکولی از نظر مقاومت به جوانه زنی قبل از برداشت است که در برنامه های اصلاح قابل کاربرد بوده و مستلزم وجود نشانگر های خوب و با تنوع بالای ژنتیکی کم هزینه و قابل انتقال به ازمایش گاه های مختلف می باشند.

بخشی از مقاله انگلیسی:

Introduction Germination of wheat (Triticum spp.) kernels, including initiation of germination and the induction of alpha-amylase without any visible evidence of embryo growth, causes significant economic losses in grain yield, grain functionality and viability of seed for planting (Derera 1989). In Canada, losses amounting to several hundred millions of dollars are experienced due to reduction in market grade in about three out of ten years (Derera 1989; Clarke et al. 2005). Economic losses due to preharvest sprouting (PHS) can be reduced by developing cultivars with increased R. M. DePauw (&) R. E. Knox A. K. Singh Semiarid Prairie Agricultural Research Centre, Agriculture and Agri-Food Canada, P. O. Box 1030, Swift Current, SK S9H 3X2, Canada e-mail: ron.depauw@agr.gc.ca S. L. Fox D. G. Humphreys Cereal Research Centre, Agriculture and Agri-Food Canada, 195 Dafoe Rd, Winnipeg, MB R3T 2M9, Canada P. Hucl Crop Development Centre, Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada 123 Euphytica (2012) 188:7–14 DOI 10.1007/s10681-011-0611-y dormancy and preharvest sprouting resistance (Czarnecki et al. 1986; McCaig and DePauw 1992) and by direct harvesting procedures (Clarke et al. 1984). Procedures used to study and or incorporate genetic resistance differ by science project objectives and by breeding objectives. Various methods have been developed to measure seed dormancy and to assess preharvest sprouting tolerance (Derera 1989). DePauw and McCaig (1991) compared various assays that measure sprouting tolerance, seed dormancy, and alpha-amylase activity. The phenotypic correlations among the various assays were significant and positive. Genotypic effects accounted for 44–90% of the phenotypic variation. Heritability expressed on a genotype mean basis ranged from 0.59 to 0.93 and was highly significant. In genetic analyses and cultivar development procedures, it is important to measure a trait such that it minimizes the error variation relative to the genetic variation. Because preharvest sprouting tolerance is only one trait of a very large suite of traits to be integrated into a cultivar, the methods used in cultivar development have to be moderately to highly heritable, reliable and yet low cost, especially in the early generations. Canadian wheat is segregated into market classes based on end-use suitability parameters of grain protein concentration, gluten strength, and kernel color (DePauw and Hunt 2001) (Table 1). Producers choose to grow cultivars of a market class based on economic considerations, market opportunities, and cultivar response to local abiotic and biotic stresses. Breeding programs target release of cultivars to meet the agronomic performance, resistance to biotic factors, and the necessary quality attributes that define each market class. This paper reviews the breeding methods employed by Canadian breeders to incorporated genetic resistance to preharvest sprouting in various wheat market classes. This information can serve as a guide to future Canadian breeders and to breeders establishing programs in other nations. Methods for selection of preharvest sprouting resistance used at Cereal Research Centre The methods used to incorporate PHS resistance, at Cereal Research Centre Agriculture and Agri-Food Canada, Winnipeg, to meet cultivar registration requirements are similar for the Canada Western Red Spring (CWRS) and Canada Western Hard White Spring (CWHWS) market classes. Crosses aim to include at least one parent that has a high level of PHS resistance (i.e. AC Domain, AC Majestic, Harvest, Snowbird, Snowstar or derivative genotype Table 2). All of these parents are derivatives of RL4137 which has a proven high level of dormancy (DePauw et al. 2009). DePauw and McCaig (1983) provided evidence that RL4137 has two mechanisms for dormancy: one associated with red seed coat color and another mechanism independent of seed coat color. For crosses with parentage that suggests PHS resistance is likely inadequate, F2 spikes are selected without stratification for maturity and stored at -20C until phenotyping. The F2 spikes are subjected to a wetting treatment in a rain simulator and only those spikes with no sprouted seeds are selected, threshed, and kernels examined. The F2 spike-F3 progeny are grown out in greenhouses over the winter months so that thorough screening is conducted and not rushed to make contra-season nursery seeding dates. Per population, 400 to 500 F2 spikes (Table 3) are exposed to 3–5 days of artificial weathering. Spikes are rated for evidence of visible germination: spikes with more than two seeds germinated (visible coleoptile or roots) are discarded. The remaining spikes are dried, threshed, and seed rated for appearance: seed rated ‘‘good’’ generally has no visible sprouting; ‘‘fair’’ seed is somewhat shriveled with little or no visible sprouting; ‘‘poor’’ seed is shriveled with many seeds sprouted. Seed shriveling may be due to seed pathogens which may have a tendency to reduce dormancy (Fox et al. 2003). The CWRS cultivars AC Majestic, AC Domain and Harvest all derive from F2 populations that were subjected to artificial weathering and have parentage related to RL4137 (Table 2). Stage two testing involves collection of spikes from single row plots 5 m long of F9 and F10 lines, and entries into pre-registration and registration trials. Stratification for maturity is achieved by sampling spikes from a plot when the majority of the ultimate stem nodes have turned brown and collapsed. Spikes are air dried for 2 days prior to storage at -20C until phenotyping. All lines are evaluated for sprouting Table 2 Examples of cultivars with preharvest sprouting resistance, parentage, and market class Name Parentage Classa Reference Source PHS Columbus Neepawa*6/RL4137 CWRS Campbell and Czarnecki 1981 RL4137_derivative AC Domain ND499/RL4137//ND585 CWRS Townley-Smith and Czarnecki 2008 RL4137_derivative Pasqua BW63*2/Columbus CWRS Townley-Smith et al. 1993 RL4137_derivative AC Vista HY344/Losprout ‘S’//HY358*3/Bt10 CPS_white DePauw et al. 1998 W_RL4137b AC Majesticc Columbus*2//Saric 70/Neepawa/3/Columbus*5// Saric 70/Neepawa CWRS Townley-Smith and Czarnecki 1995 RL4137_derivative Waskada AC_Domain*2/Sumai_3//2*Superb (Superb = Grandin*2/AC Domain) CWRS Fox et al. 2009 RL4137_derivative Harvest AC Domain*2/ND 640 CWRS Fox et al. 2010 RL4137_derivative Snowbird RL4137*6//Thatcher/Poso48/3/AC Domain CWHWS Humphreys et al. 2007 W_RL4137b Snowstar 94B46*G22/McKenzie CWHWS DePauw et al.

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چکیده
۱ مقدمه
۲ جریان سطحی و انتقال رسوب در سطوح زبر
۳ مدل فرسایش استانه ی سطحی
۴ نتیجه گیری

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چنین استدلال می شود که اثرات متقابل حین خصوصیات طحی به خصوص میکرو توپوگرافی و سله بندی بر کمیت و الگوی مکانی رواناب سطحی تاثیر می گذارند.این اثرات متقابل در همه ی مقیاس از مقیاس های زبری فردی تا مقیاس های حوزه ای دیه می شود.اگر چه پارامتر سازی زبری می تواند به صورت وابسته به مقیاس و بارندگی باشد اما مفهوم ظرفیت ذخیره ی موثر وی ا استانه ی رواناب در دامنه های مقیاس های مربوطه بسیار مهم است و در بسیاری از موارد به شدت بستگی به خواص سطحی خاک و توزیع ان ها دارد.
تغییرات تصادفی هم در شدت باران و هم در ذخیره و خصوصیات نفوذ بر مقدار و توزیع رواناب تاثیر می گذارد و اثرات متقابل بین این تغییر پذیری ها ایجاد وابستگی های قوی بین اندازه ی یمانگین قطه باران و طول دامنه برای یک طح معین می کنند.همه ی این روابط درونی هنوز به اندازه ی کافی خوب درک نشده اند که ما بتوانیم از ان ها برای ایجاد مدل های مناسب فرسایش و رسوب و چشم انداز استفاده کنیم. همچنین ان ها اصول و قواعد مفهومی مهم را برای تنظیم و واسنجی پلات ها تا مقیاس حوزه ای در اختیار می گذارند و به این ترتیب درک بهتر از نتایج تجربی و کاربرد ان ها در سطوح بزرگ تر حاصل خواهد شد.

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1. Introduction Soil erosion models commonly include parameters based on fixed soil properties or moisture–tension curves, but rarely take account of the dynamics linking soil and surface properties with water erosion processes, which are relevant at a range of time and space scales. The four sub-systems of Soil, Vegetation, Atmosphere and Surface interact dynamically with one another within each site, and sites are linked by lateral transfers of water, sediment and solutes in a downslope direction Fig. 1 . Ž . Over short within-storm periods, soils properties influence erosion mainly through their hydrology, aggregate stability, and cation dispersion. Over periods of decades, erosion can lead to profile truncation and armouring of the surface, and these changes then influence subsequent rates and patterns of erosion. Over the still longer periods of soil evolution, the balance between mechanical and chemical denudation determines the entire weathering profile and its variation downslope to create hillslope catenas, which in turn also influence the distribution of erosion rates. Similarly, erosion interacts with soil properties at a wide range of spatial scales. Macro-pores and crusting are examples of dominant influences at the finest 10 –10 Ž y3 y1 m scales, and give way in importance to spatial patterning produced by cultivation or . natural vegetation location at moderate 1–10 m scales, to catena differences at the Ž . Ž 2 3 . Ž 4 5 hillslope 10 –10 m scale, to major soil series at the catchment 10 –10 m scale and . Ž 6 8 to climatically based major soil groups at continental 10 –10 m scales. In all cases, . there are also strong links with soil via the vegetation cover, so that the direct importance of the soil is greatest under sparse covers. The direct links with the soil are therefore strongest under arid and semi-arid climates for uncultivated areas. Under conditions of global change, relatively slow changes in soils and erosion rates are giving way to much more rapid modifications under the impact of climate and landuse change. Under these strongly non-equilibrium conditions, many ‘natural’ inter-relationships between the soils and the associated pattern of erosion will be broken down, demanding a more fundamental assessment of cause and effect in highly disturbed systems and making it difficult to use analogue studies with any confidence. On natural semi-arid surfaces, microtopography evolves through sediment transfers and through the dynamics associated with mounds around perennial shrubs, with a time scale of decades to hundreds of years. On cultivated fields, microtopography is created by tillage operations and destroyed by sediment transfers over an annual cycle. These two systems have rather different dynamics but a number of important features in common. This paper explores developments with respect to one set of processes which are believed to be important, and have been relatively neglected—the interactions between overland flow, water erosion and surface microtopography. This theme is being explored through research in a number of related erosion models, which are concerned with the wide range of relevant spatial and temporal scales. Some are primarily related to hydrology, others to soil erosion under global change while others are concerned with the evolution of soils and landforms over geological time spans. These include the MEDALUS and MEDRUSH models Kirkby et al., 1997, 1998 , the Regional Degrada- Ž . tion Index RDI Ž . rCSEP: Kirkby and Cox, 1995 and a number of models for long-term landscape evolution e.g. Kirkby, 1991, 1992, 1994 . Ž . 2. Overland flow and sediment transport on rough surfaces Roughness due to random irregularities on a soil surface is usually well represented as a normal distribution of elevations relative to a mean, and is characterized by its standard deviation, or RMS roughness. There may also be various forms of systematic roughness due to tillage operations or, at a coarser scale, to terracing. Their orientation with respect to the slope direction is vitally important, particularly for long linear features like plough ridges. The scale dependence of roughness is not fully understood, but it is clear that roughness occurs at a number of scales, and natural roughness may well have a fractal or similar structure, with larger RMS roughness as it is measured with a coarser grid of points. At sufficiently coarse scales, roughness of natural surfaces merges into landscape elements such as ephemeral gullies and stream valleys. Cultivated areas also show systematic roughness elements, most strikingly at the scales of plough furrows and terrace systems.

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چکیده
۱ مقدمه
۲ ایده عمومی در خصوص تاثیر درختان روی حاصلخیزی خاک
۳ درختان و کربن خاک
۴ درختان و تنوع زیستی خاک
۵ درختان در خاک های حاره ای
۶ درختان در کشاورزی امازون
۷ نتیجه گیری

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مقاله حاضر به بحث در خصوص اثرات درختان روی حاصلخیزی خاک با تاکید بر سیستم های کشاورزی در آمازون می پردازد. بررسی منابعی خصوص اثرات درختان روی خواص فیزیکی و شیمیایی خاک در مناطق حاره ای،نیمه حاره ای و معتدله انجام شده که شامل اکوسیستم های طبیعی و اکوسیستم های زراعی می شود. کربن خاک در شکل ماده آلی به عنوان شاخص فعالیت بیولوژیک و نیز مشکلات سیاسی نظیر ترسیب کربن و تغییر اقلیم مطرح است. در رابطه با خاک های حاره ای و آمازون، اطلاعات در خصوص اثرات درختان روی خاک در سیستم های زراعی سنتی علاوه بر توسعه راه کارهای جایگزین کشاورزی پایدار تر برای منطقه مورد بحث قرار می گیرد . در نهایت مطالعه موردی در منطقه ساوانا رورامیا شمال برزیل معرفی می شود که توالی زمانی سیستم های آگروفارستری بومی اثرات مبرهن عملیات مدیریتی از جمله اثر درختان روی حاصلخیزی خاک را نشان می دهند. استفاده از گونه های مختلف درختی و دیگر عملیات به کار گرفته شده در سیستم های آگروفارستری می تواند یک راهکار جایگزین برای افزایش باروری خاک و حفظ تولیدات کشاوری با اهمیت کاربردی برای پایداری کشاورزی حاره ای تلقی شود.

۱ مقدمه

بر اساس مطالعه انجام شده توسط مرکز آگروفارستری جهانی ICRAF، ۴۳ درصد اراضی زراعی زمین(بیش از ۱ میلیارد هکتار) دارای پوشش درختی بیش از ۱۰ درصد می باشد. سطح وسیعی از اراضی زراعی یعنی ۱۶۰ ملیون هکتار دارای پوشش درختی بیش از ۵۰ درصد هستند. پتانسیل درختان برای بهبود تغذیه، درامد، مسکن، سلامتی و بهداشت، رفع نیاز های انرژی و پایداری زیست محیطی در چشم انداز های کشاورزی موجب شد تاICRAF حضور درختان را به عنوان ممولفه اصلی کشاورزی همیشه سبز معرفی کنند. در میان طیف وسیعی از مزایای ناشی از درختان، یک عنصر مهم اثر مثبت درختان روی خواص خاک و در نتیجه مزایای آن برای گونه های زراعی می باشد. این مقاله به بررسی دانش فعلی در خصوص رابطه بین درخت و خاک بر اساس تحقیقات سیستم های اگروفارستری علاوه بر مطالعات در محیط های طبیعی و غیر زراعی که اثرات درخت را روی خاک اثبات کرده اند می پردازد.

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This paper discusses the effects of trees on soil fertility, with a focus on agricultural systems in Amazonia. Relevant literature concerning the effects of trees on soil physical and chemical properties in tropical, subtropical, and temperate regions is reviewed, covering both natural ecosystems and agroecosystems. Soil carbon, in the form of organic matter, is considered as an indicator of biological activity as well as in relation to policy issues such as carbon sequestration and climate change. In the case of tropical soils and Amazonia, information on the effects of trees on soils is discussed in the context of traditional agriculture systems, as well as in regard to the development of more sustainable agricultural alternatives for the region. Lastly, attention is given to a case study in the savanna region of Roraima, northern Brazil, where a chronosequence of indigenous homegarden agroforestry systems showed clear effects of management practices involving trees on soil fertility. The use of diverse tree species and other practices employed in agroforestry systems can represent alternative forms of increasing soil fertility and maintaining agricultural production, with important practical applications for the sustainability of tropical agriculture. 1. Introduction According to a study by the World Agroforestry Centre, ICRAF, 43% of the planet’s agricultural lands (more than a billion hectares) has more than 10% tree cover [1]. A lesser but still significant area of agricultural land, 160 million hectares, has more than 50% tree cover. The potential of trees to bring improvements in nutrition, income, housing, health, energy needs, and environmental sustainability in the agricultural landscape has guided ICRAF’s mission, with the presence of trees being the principal component of an “evergreen agriculture” [2]. Within the array of benefits brought by trees, an important element is the positive effect of trees on soil properties and consequently benefits for crops. This paper explores current knowledge as to this relation between trees and soil, based on agroforestry systems research, as well as studies innon-agricultural or natural environments that demonstrate effects of trees on soil. Although we consider information from various ecosystems and biomes, the focus will be on Amazonia, where the authors have most of their experience. This focus on Amazonia is also due to the strong policy demands for the development of more sustainable agricultural systems in the region, as alternatives to forms of land use that have shown significant and negative impacts on natural resources and ecosystem services, such as deforestation for extensive cattle ranching. In this scenario, agroforestry systems have been indicated as one of the more promising alternatives to achieve a more sustainable agriculture, in greater equilibrium with the environment [3]. The presence of trees in farming systems, although an ancient practice, began to gain institutional attention during the 1970s and 1980s, with the beginning of studies on “agroforestry systems”. One of the principal definitions employed in this context was that proposed by Lundgren and Raintree in 1982: “Agroforestry is a collective name for landuse systems and technologies where woody perennials (trees, shrubs, palms, bamboos, etc.) are deliberately used on the same land-management units as agricultural crops and/or animals, 2 Applied and Environmental Soil Science Figure 1: Agroforestry system with rubber (Hevea brasiliensis), cacao (Theobroma cacao), and ac¸a´ı (Euterpe oleracea) in Tome-ac ´ ¸u, Para, showing the litter layer that is typically found in such ´ multistrata systems. Figure 2: Agroforestry system in initial phase, with black pepper (Piper nigrum) as principal cash crop, interplanted with cupuac¸u (Theobroma grandiflorum) and ac¸a´ı (Euterpe oleracea) for future fruit production, as well as timber trees (mahogany—Swietenia macrophylla and ipe—ˆ Tabebuia sp.) and Brazil nut (Bertholletia excelsa) as long-term products. in some form of spatial arrangement or temporal sequence. In agroforestry systems there are both ecological and economical interactions between the different components” [4] (Figures 1, 2, and 3). While trees in general can provide a number of environmental benefits in both rural and urban landscapes, and play key roles in ecosystem services provided by natural areas, in this paper we will restrict our focus to the effects of trees on soil fertility, in the specific context of agricultural systems. Although the benefits that trees can provide on rural properties such as food security, household income, economic stability, and thermal comfort (shade) are most often associated with their products, such as fruit, timber, or other items, the inclusion of trees in agricultural systems can also optimize nutrient cycling and have positive effects on soil chemical and physical properties. This process is especially important in tropical soils, where a high degree of weathering has created deep, leached soils that are poor in Figure 3: Multistrata agroforestry system in Tome-ac ´ ¸u, Para, with ´ harvest of hogplum (Spondias mombin) grown as the upper canopy over cacao and ac¸a´ı. plant nutrients [5, 6]. Although poor in nutrients, tropical soils are very rich in biodiversity, with higher diversity and biomass of microorganisms than temperate soils, with these being the principal agents mediating the supply of nutrients to the soil by means of the decomposition of organic matter, derived from the vegetation [7–9]. In the humid tropics, the removal of surface litter or organic matter generally results in the depletion of soil fertility in a few years [10, 11]. In agricultural systems practiced by traditional peoples, this limitation is circumvented by using the land for a short period (generally 2- 3 years), after which the cultivated areas are left to fallow with natural regeneration of secondary vegetation. The associated ecological interactions reestablish nutrient cycling and recuperate soil qualities, after which the area can once again be used for agriculture [12, 13]. This is the basis for shifting cultivation in Amazonia, a system that has permitted native populations to manage their natural resources over centuries, with small-scale environmental impacts that do not exceed the support capacity and resilience of ecosystems. However, the present-day situation of population growth and increasing pressure on agricultural lands lead to situations where there is demand for more intensive land use. This most often implies in repeated burning, the cheapest way to prepare land for planting, which can interrupt processes of nutrient cycling and accumulation, leading to loss of soil fertility and consequently slowing the recuperation of natural vegetation during fallow cycles [14]. In light of the present-day situation of Amazonia, where there are now good reasons and policy demands to balance conservation with development, it is necessary to think in terms of agricultural systems that optimize nutrient cycling and permit permanent or semipermanent production, as well as minimize dependence on external inputs and have low environmental impact. The inclusion of diverse tree species is a key element in maintaining the production of organic matter and generating other positive benefits, as well as allowing the diversification of products. However, before we discuss topics specific to tropical soils and Amazonia, Applied and Environmental Soil Science 3 the following sections will review general information about the influence of trees on soil and their role in accumulation of soil carbon stocks. 2. A General View of the Influence of Trees on Soil Fertility One of the pioneer studies to measure the effects of individual trees on soils was that by Zinke [15], who looked at pines growing on dunes in northern California, USA. His study found that under trees, certain soil properties exhibited a pattern of radial symmetry, with changes in pH, nitrogen, cations, and cation exchange capacity varying according to distance from the tree trunk, with a peak in these characteristics at a certain distance. Subsequent studies also demonstrated patterns in the variation of soil characteristics as influenced by trees, such as in tropical savannas [16, 17], deserts [18], and areas of temperate forests [19–23]. In analyzing soil characteristics under individual tree crowns in Kenyan savannas, Belsky et al. [16] found greater levels of mineralizable N, microbial biomass, P, K, and Ca underneath the crowns when compared to open savanna. Burke et al. [17] explain that in dry savannas the strong limitation on water availability permits only punctuated establishment of trees and shrubs but that under crowns cycling occurs in a different form than in open grasslands, with the possibility of soil enrichment in a scale of decades. However, such soil changes can be reverted with the death of the tree or by fires. Belsky et al. [16] also point out the effect of nutrients deposited in dung by birds and large mammals that utilize trees as resting places or roosts. Such patterns form what have been called “islands of fertility” or “resource islands” created by trees or bushes, generally in savannas or desert areas. The microenvironment of these “islands” can also influence the composition of the herb stratum [16, 19], soil density [19, 20], and earthworm activity [20, 23] among other factors, allowing the creation of positive feedbacks that favor plant establishment and productivity [23, 24]. At the same time, these patterns can be important indicators of stability or risk of desertification in such areas [17, 18]. Studies of forests in temperate climates indicate variations in soil that can be related to individual tree species. Besides the expected correlations, such as greater levels of N under legumes [20] or lower pH under species that produce acidifying litter, such as Pinus spp. [20, 23], other interesting interactions show that different species can alter soil in distinct ways, with variations in the increment of soil carbon [20], exchangeable Ca and Mg and per cent base saturation [21, 23]. In a study of 14 tree species in Poland, Reich et al. [23] found varied effects on soil characteristics; however, these effects were significantly related to the level of Ca in litter, independent of the species. Trees producing litter rich in Ca were associated with soils with greater pH, exchangeable Ca, and per cent base saturation, as well as greater rates of forest floor turnover and greater diversity and abundance of earthworms. Dijkstra [22] emphasizes that the rate of mineralization of organic Ca is a fundamental factor in this process, since it determines the immediate availability of this nutrient in the soil and can vary between species. The study of vertical patterns of the distribution of nutrients in soil can indicate other phenomena that are not detected when only the horizontal distribution of nutrients is examined. In an evaluation of more than 20,000 globally distributed soil profiles, the greater part in temperate climates, Jobbagy and Jackson [ ´ 25] found that cycling mediated by plants exerts a marked influence on the vertical distribution of nutrients in the soil, especially in the case of more limiting nutrients such as P and K. Patterns of greater concentration of these nutrients in surface layers (0– 20 cm) were attributed to the fact that since these are more important to plants, they are subject to greater uptake and cycling, being absorbed from deeper layers and returned to the soil surface through litterfall and rain water throughfall. This process of uptake functions in opposition to leaching, which moves nutrients downward and acts more strongly on those nutrients that are in lessdemand by plants. If a nutrient is not limiting, its movement in the soil profile will be more influenced by leaching than by cycling and it will present higher concentrations at greater depth, as occurs with Na, Cl, and Mg [25].

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فهرست مطالب:

چکیده
۱مقدمه
۲ مکانیسم جذب زیستی
۳ مدل های جذب زیستی
۴ پارامترهای ترمودینامیکی
۵ عملکرد مواد پسماند کشاورزی به عنوان جاذب های زیستی برای حذف فلزات سنگین
۵ ۱ حذف کرومیوم
۲ ۵ حذف سرب
۵ ۳حذف کادمیوم
۴ ۵ حذف نیکل
۶ نتیجه گیری

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حذف و احیای فلزات سنگین از جریانات آبی یک نگرانی اصلی به شمار می رود زیرا این یون ها مقاوم بوده و در محیط دوام زیادی دارند. فناوری های سنتی تصفیه برای حذف این یون های فلزات سنگین از نظر اقتصادی به صرفه نبوده و ایجاد حجم عظیمی از پسماند ها و فاضلاب سمی شیمیایی می کند.جذب زیستی در حال حاضر یک روش جایگزین بالقوه برای فناوری های زیست محیطی موجود جهت حذف و بازیابی یون های فلزی از محلول های آبی محسوب می شود.مزایای اصلی جذب زیستی نسبت به روش های تصفیه سنتی شامل موارد ذیل می باشد: قیمت پایین، کارایی بالا، به حداقل رساندن پسماند های شیمیایی و زیستی، بازتولید جاذب های زیستی، و امکان بازیابی فلزی.پسماند های کشاورزی سلولزی از منابع فراوان برای جذب زیستی فلزات محسوب می شوند.گروه های عاملی موجود در بیوماس پسماند های کشاورزی نظیرگروه های استامیدو،الکلی، کربونیل،فنولیک، آمید، آمین، سولفیدریل و … با یون های فلزات سنگین دارای قرابت و خویشاوندی بوده و ایجاد کمپلکس های فلزی و کلات می کنند.مکانیسم فرایند جذب زیستی شامل جذب شیمایی، کمپلکس شدن، جذب سطحی، انتشار از طریق خلل و فرج ها و تبادل یونی می باشد. هدف این مقاله مروری فراهم کردن اطلاعاتی در خصوص ابعاد مختلف بهره برداری از پسماند های کشاورزی برای حذف فلزات سنگین می باشد.پسماند های کشاورزی منابع بسیار کارامد، کم هزینه و تجدید پذیر بیوماس می باشند که برای حذف فلزات سنگین مورد بهره برداری قرار می گیرند. به علاوه این جاذب های زیستی را می توان برای افزایش کارایی و استفاده چند منظوره برای بهبود کاربرد آن ها در مقیاس صنعتی اصلاح کرد.

۱ مقدمه

یون های سمی فلزات سنگین توسط فعالیت های مختلف صنعتی نظیر معدن کاوی، پالایش کانسنگ، صنایع تولید کود، پالایشگاه های نفتی، پیل های سوختی، صنایع تولید کاغذ، آفات کش ها غیره وارد منابع آبی می شوند و ایجاد تهدید جدی برای محیط زیست می کنند(کلیک و دمیرباس ۲۰۰۵،فریدمن و وایس ۱۹۷۲،جلستروم و همکاران ۱۹۷۷،باستیرکوا۲۰۰۴).یون های فلزی عمده خطرناک و سمی برای انسان علاوه بر دیگر اشکال حیات شامل کروم؛آهن، سلنیوم، وانادیوم، مس، کبالت، نیکل،کادمیوم، جیوه، استرانسیوم، سرب و روی می باشند. این فلزات سنگین به دلیل سمیت، انباشت زیستی و دوام در طبیعت یک نگرانی اصلی محسوب می شود(فردبیگ و الیندر ۱۹۸۵،گارک و همکاران ۲۰۰۷،راندل و همکاران ۱۹۷۴).چندین فجایع گذشته ناشی از آلودگی فلزات سنگین در سیستم های آبی شامل تراژدی میناماتا ژاپن به دلیل آلودگی توسط متیل اورانیوم و ایتای ایتای ناشی از آلودگی کادمییوم در رودخانه جینسو می باشند(فریدبیگ الیندر ۱۹۸۵،جلستروم و همکاران ۱۹۷۷). آژانس های زیست محیطی مختلف ماکزیمم آستانه تجویز شده برای تخلیه فلزات سنگین به درون سیستم های زیست محیطی را وضع کرده اند. با این حال یون های فلزی با غلظت بسیار بیشتری نسبت به حد آستانه توسط فعالیت های صنعتی به مخازن آب وارد شده و ایجاد خطرات جدی برای سلامتی کرده و موجب تخریب محیط زیست می شوند.

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Abstract Heavy metal remediation of aqueous streams is of special concern due to recalcitrant and persistency of heavy metals in environment. Conventional treatment technologies for the removal of these toxic heavy metals are not economical and further generate huge quantity of toxic chemical sludge. Biosorption is emerging as a potential alternative to the existing conventional technologies for the removal and/ or recovery of metal ions from aqueous solutions. The major advantages of biosorption over conventional treatment methods include: low cost, high efficiency, minimization of chemical or biological sludge, regeneration of biosorbents and possibility of metal recovery. Cellulosic agricultural waste materials are an abundant source for significant metal biosorption. The functional groups present in agricultural waste biomass viz. acetamido, alcoholic, carbonyl, phenolic, amido, amino, sulphydryl groups etc. have affinity for heavy metal ions to form metal complexes or chelates. The mechanism of biosorption process includes chemisorption, complexation, adsorption on surface, diffusion through pores and ion exchange etc. The purpose of this review article is to provide the scattered available information on various aspects of utilization of the agricultural waste materials for heavy metal removal. Agricultural waste material being highly efficient, low cost and renewable source of biomass can be exploited for heavy metal remediation. Further these biosorbents can be modified for better efficiency and multiple reuses to enhance their applicability at industrial scale. 2007 Elsevier Ltd. All rights reserved. Keywords: Agricultural wastes; Biosorption; Industrial effluents; Heavy metal remediation; Adsorbent 1. Introduction Toxic heavy metal ions get introduced to the aquatic streams by means of various industrial activities viz. mining, refining ores, fertilizer industries, tanneries, batteries, paper industries, pesticides etc. and posses a serious threat to environment (Celik and Demirbas, 2005; Friedman and Waiss, 1972; Kjellstrom et al., 1977; Pastircakova, 2004). The major toxic metal ions hazardous to humans as well as other forms of life are Cr, Fe, Se, V, Cu, Co, Ni, Cd, Hg, As, Pb, Zn etc. These heavy metals are of specific concern due to their toxicity, bio-accumulation tendency and persistency in nature (Friberg and Elinder, 1985; Garg et al., 2007; Randall et al., 1974). Several past disasters due to the contamination of heavy metals in aquatic streams are Minamata tragedy in Japan due to methyl mercury contamination and ‘‘Itai-Itai” due to contamination of cadmium in Jintsu river of japan (Friberg and Elinder, 1985; Kjellstrom et al., 1977). Various regulatory bodies have set the maximum prescribed limits for the discharge of toxic heavy metals in the aquatic systems. However the metal ions are being added to the water stream at a much higher concentration than the prescribed limits by industrial activities, thus leading to the health hazards and environmental degradation (Table 1). Conventional methods for removal of metal ions from aqueous solutions include chemical precipitation, ion exchangers, chemical oxidation/reduction, reverse osmosis, electro dialysis, ultra filtration etc (Gardea-Torresdey et al., 1998; Patterson, 1985; Zhang et al., 1998). However these conventional techniques have their own inherent limitations such as less efficiency, sensitive operating conditions, production of secondary sludge and further the disposal is a costly affair (Ahluwalia and Goyal, 2005a). Another powerful technology is adsorption of heavy metals by activated carbon for treating domestic and industrial waste water. (Horikoshi et al., 1981; Hosea et al., 1986). However the high cost of activated carbon and its loss during the regeneration restricts its application. Since 1990’s the adsorption of heavy metal ions by low cost renewable organic materials has gained momentum (Bailey et al., 1999; Orhan and Bujukgungor, 1993; Rao and Parwate, 2002; Vieira and Volesky, 2000). The utilization of seaweeds, moulds, yeasts, and other dead microbial biomass and agricultural waste materials for removal of heavy metals has been explored (Bailey et al., 1999; Haung and Haung, 1996; Sudha and Abraham, 2003; Zhou and Kiff, 1991). Recently attention has been diverted towards the biomaterials which are byproducts or the wastes from large scale industrial operations and agricultural waste materials. The major advantages of biosorption over conventional treatment methods include: low cost, high efficiency, minimization of chemical or biological sludge, no additional nutrient requirement, and regeneration of biosorbents and possibility of metal recovery. Agricultural materials particularly those containing cellulose shows potential metal biosorption capacity. The basic components of the agricultural waste materials biomass include hemicellulose, lignin, extractives, lipids, proteins, simple sugars, water hydrocarbons, starch containing variety of functional groups that facilitates metal complexation which helps for the sequestering of heavy metals (Bailey et al., 1999; Hashem et al., 2005a,b, 2007). Agricultural waste materials being economic and ecofriendly due to their unique chemical composition, availability in abundance, renewable, low in cost and more efficient are seem to be viable option for heavy metal remediation. Studies reveal that various agricultural waste materials such as rice bran, rice husk, wheat bran, wheat husk, saw dust of various plants, bark of the trees, groundnut shells, coconut shells, black gram husk, hazelnut shells, walnut shells, cotton seed hulls, waste tea leaves, Cassia fistula leaves, maize corn cob, jatropa deoiled cakes, sugarcane bagasse, apple, banana, orange peels, soybean hulls, grapes stalks, water hyacinth, sugar beet pulp, sunflower stalks, coffee beans, arjun nuts, cotton stalks etc has been tried (Annadurai et al., 2002; Cimino et al., 2000; Hashem et al., 2006a,b; Macchi et al., 1986; Maranon and Sastre, 1991; Mohanty et al., 2005; Orhan and Bujukgungor, 1993; Reddad et al., 2002; Tee and Khan, 1988). These promising agricultural waste materials are used in the removal of metal ions either in their natural form or after some physical or chemical modification. The present review article deals with the utilization of agricultural waste materials as biosorbents for removal of toxic heavy metal ions from aqueous streams. 2. Mechanism of biosorption The removal of metal ions from aqueous streams using agricultural materials is based upon metal biosorption (Volesky and Holan, 1995). The process of biosorption Table 1 Permissible limits and health effects of various toxic heavy metals Metal contaminant Permissible limits for industrial effluent discharge (in mg/l) Permissible limits by international bodies (lg/l) Health hazards Into inland surface waters Indian Standards: 2490(1974) Into public sewers Indian Standards: 3306(1974) On land for irrigation Indian Standards: 3307 (1974) WHO USEPA Arsenic 0.20 0.20 0.20 10 50 Carcinogenic, producing liver tumors, skin and gastrointestinal effects Mercury 0.01 0.01 – 01 02 Corrosive to skin, eyes and muscle membrane, dermatitis, anorexia, kidney damage and severe muscle pain Cadmium 2.00 1.00 – 03 05 Carcinogenic, cause lung fibrosis, dyspnea and weight loss Lead 0.10 1.00 – 10 05 Suspected carcinogen, loss of appetite, anemia, muscle and joint pains, diminishing IQ, cause sterility, kidney problem and high blood pressure Chromium 0.10 2.00 – 50 100 Suspected human carcinogen, producing lung tumors, allergic dermatitis Nickel 3.0 3.0 – – – Causes chronic bronchitis, reduced lung function, cancer of lungs and nasal sinus Zinc 5.00 15.00 – – – Causes short-term illness called ‘‘metal fume fever” and restlessness Copper 3.00 3.00 – – 1300 Long term exposure causes irritation of nose, mouth, eyes, headache, stomachache, dizziness, diarrhea 6018 D. Sud et al. / Bioresource Technology 99 (2008) 6017–6027 involves a solid phase (sorbent) and a liquid phase (solvent) containing a dissolved species to be sorbed. Due to high affinity of the sorbent for the metal ion species, the latter is attracted and bound by rather complex process affected by several mechanisms involving chemisorption, complexation, adsorption on surface and pores, ion exchange, chelation, adsorption by physical forces, entrapment in inter and intrafibrillar capillaries and spaces of the structural polysaccharides network as a result of the concentration gradient and diffusion through cell wall and membrane (Basso et al., 2002; Sarkanen and Ludwig, 1971; Qaiser et al., 2007) (Fig. 1). Agricultural waste materials are usually composed of lignin and cellulose as the main constituents. Other components are hemicellulose, extractives, lipids, proteins, simple sugars, starches, water, hydrocarbons, ash and many more compounds that contain a variety of functional groups present in the binding process. Cellulose is a crystalline homo-polymer of glucose with b1 ? 4 glycosidic linkage and intra-molecular and intermolecular hydrogen bonds (Demirbas, 2000a,b). Hemicellulose is a heteropolymer of mainly xylose with b1 ? 4 glycosidic linkage with other substances of acetyl feruoyl and glycouronyl groups (Garg et al., in press). Lignin is three dimensional polymer of aromatic compounds covalently linked with xylans in hardwoods and galactoglucomannans in softwoods (Garg et al., 2007; Sjo¨tro¨m, 1981) The functional groups present in biomass molecules acetamido groups, carbonyl, phenolic, structural polysaccharides, amido, amino, sulphydryl carboxyl groups alcohols and esters (Beveridge and Murray, 1980; Gupta and Ali, 2000). These groups have the affinity for metal complexation.

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فهرست مطالب:

چکیده
مقدمه
مواد و روش ها
ساخت لایسی متر
جمع آوری داده
داده های اقلیمی
رطوبت خاک
شوری خاک

بخشی از ترجمه:

یک آزمایش لایسی متر برای بررسی تاثیر مدیریت سفره آب WTM روی توزیع شوری خاک و عملکرد یونجه یک ساله(Medicago scutellata) انجام شد.آبیاری هایی با سه سطح سفره آب یعنی ۰.۵ (WT0.5)، ۰.۷ (WT0.7) و ۱.۰ m(WT1.0) و تیمار آبیاری سنتی زهکش آزاد برای این مطالعه انتخاب شدند.همه تیمارها در قالب طرح بلوک های کاملا تصادفی با سه تکرار انتخاب گردیدند.نتایج این مطالعه نشان داد که هدایت الکتریکی متوسط خاک عصاره ااشباع در ناحیه ریشه به تدریج افزایش یافت و به بیش از مقدار آستانه طراحی شده (۴ دسی زمیتر) بعد از نخستین برداشت علوفه در لایسی مترهای کارگذاشته شده در زیر زمین رسید.انباشت بیشتر نمک در تیمار WT0.5 مشاهده شد.عملکرد و وزن متوسط خشک یونجه یک ساله در WT0.5 و WT0.7 به ترتیب ۵۲ و ۷۳ درصد نسبت به تیمار شاهد بیشتر بود.

۱ مقدمه

مدیریت سفره آب موجب افزایش تولید گیاه و کیفیت آب زهکش در مناطق مرطوب شد(ورکمن و همکاران ۱۹۹۰،کالیتا و همکاران ۱۹۹۲،فیشر و همکاران ۱۹۹۹،جای و همکاران ۲۰۰۶).زهکشی زیر سطحی تاثیر بسزایی بر کیفیت و کمیت تولیدات گیاهی مختلفی دارد و این در حالی است که بسیاری از مطالعات اخیر نشان دادند که بسیاری از گیاهان به طور مطلوبی به عملیات زهکشی کنترل شده و سیستم های آبیاری زیرسطحی واکنش می دهند(ساپی و همکاران ۲۰۰۱،فازی و بیکر ۲۰۰۳،آیرز و همکاران۲۰۰۳).در سیستم زهکشی کنترل شده،خروجی زهکش جهت حفظ بخشی از آب نفوذی در پروفیل خاک به عنوان مکمل نیازهای آبی گیاه تعبیه شد.در سیستم آبیاری زیر سطحی،با این حال، آب از طریق لوله های زهکشی زیرسطحی برای حفظ سفره آب زیر ناحیه ریشه جهت رفع نیازهای آبی گیاهی وارد شد(فازی و بیکر۲۰۰۳).برخی از مزایای نسبت داده شده به WTM به صورت ذیل می باشند:کاهش آب زهکش و مواد شیمیایی،کاهش آلودگی زیست محیطی، و تامین محیط آبی خاکی بهتر برای رشد گیاه(اسکاج و ایوانز ۱۹۹۶،مجا و همکاران ۲۰۰۰).اسکاج و همکاران ۱۹۹۹ به مقایسه عملکرد زهکشی کنترل شده، آبیاری زیرسطحی و سیستم های زهکشی مدیریت آب در یک زمین چهار هکتاری پرداختند.غلظت نیترات آب زهکشی تا ۶۳ درصد در سیستم زهکشی کنترل شده کاهش یافت و مقدار کل نیترات تا ۵۰ درصد در مقایسه با سیستم زهکشی آزاد کاهش نشان داد.محصول گوجه و ذرت در سیستم ابیاری زیرسطحی به ترتتیب ۴۴ و ۶۴ درصد بود.آهنن ۱۹۹۱ افزایش ۱۰ درصدی در عملکرد سیب زمینی در آبیاری زیرسطحی در مقایسه با سیستم زهکشی آزاد نشان داد.مجیا و همکاران ۱۹۹۸ نیز کاهش ۷۵ تا ۸۴ درصدی نیترات و افزایش ۴۲ درصدی عملکرد ذرت را از طریق مدیریت سفره آب گزارش کردند.

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Abstract A lysimeter experiment was conducted to investigate the eVect of water table management (WTM) on distribution of soil salinity and annual alfalfa (Medicago scutellata) yield. Subirrigations with three levels of water table namely, 0.5 (WT0.5), 0.7 (WT0.7), and 1.0 m (WT1.0) and a free drainage (FD) conventional irrigation treatment were selected for this study. All treatments were arranged in a complete randomized block design with three replicates. The results of this study indicated that the average soil electrical conductivity of the saturated extract (ECe) in the root zone gradually increased and exceeded the designated crop threshold value (4 dS/m) after the Wrst forage harvest in subirrigated lysimeters. A higher salt accumulation was observed at the WT0.5 treatment. The average dry matter yield of annual alfalfa in WT0.5 and WT0.7 treatments was found to be 52 and 73% higher compared with the control treatment, respectively. Introduction Water table management has shown to increase crop production and drainage water quality in humid regions (Workman et al. 1990; Kalita et al. 1992; Fisher et al. 1999; Jia et al. 2006). Conventional subsurface drainage has long been proved to have substantial impact on quality and quantity of various crop productions, whereas many recent studies have shown that many crops respond more favorably to the practice of controlled drainage and subirrigation systems, instead (Soppe et al. 2001; Fausey and Baker 2003; Ayars et al. 2003). In controlled drainage system, the drain outlet is raised to a speciWed level in order to retain a portion of percolating water in the soil proWle to supplement crop water requirements. In subirrigation system, however, water is introduced through subsurface drainage pipes to maintain the water table just below the root zone to fulWll crop water requirements (Fausey and Baker 2003). Some of the advantages attributed to WTM are: reduction in drainage water and losses of chemicals, reduction in environmental pollution, and provision of a better soilwater environment for crop growth (Skaggs and Evans 1996; Mejia et al. 2000). Skaggs et al. (1999) compared the performance of controlled drainage, subirrigation and free drainage systems for management of drainage water in a 4- ha Weld study. Nitrate concentration of drainage water was reduced by 63% in the controlled drainage system and the total nitrate losses were reduced by 50% compared with the free drainage system. Tomato and corn yields in the subirrigation system were 44 and 64% more than those in the free drainage system, respectively. Ahonen (1991) reported a 10% increase in potato yield in the subirrigation as compared to the free drainage system. Mejia et al. (1998) also reported 75-84% reduction of nitrate losses and 42% increase in corn yield through water table management.A study performed on a Ravenna silt loam showed that the average yield of subirrigated soybeans over a 5-year period was 5.22 Mg, whereas the non-irrigated yield over the same period was limited to 3.44 Mg (Fausey and Cooper 1995). Controlled drainage and subirrigation can also improve conservation of water during drought (Skaggs and Gilliam 1981; Evans et al. 1995; Meija and Madramootoo 1998). Lothar et al. (2005) quantiWed the water use eYciency of several crops at shallow water table in temperate climate. They showed that water requirements strongly depend on the level of water control and the type of crops. Freshwater supplies are becoming more limited in dry regions, while the demand for food is increasing globally (FAO 1995a). There are numerous problems in arid and semi-arid regions associated with the practice of surface irrigation using brackish water (FAO 2002). Sensitivity of young plants to saline water and the extent of salt buildup within the root zone during growing season are among the most serious limitations in this respect (Von Hoyningen Huene 1994; Patel et al. 1999). However, a number of studies have reported positive impacts of adopting controlled drainage and subirrigation in arid and semi-arid regions by reducing drainage discharge and saving irrigation water (Abbott et al. 2001; Khalil et al. 2004). Patel et al. (2001) investigated the eVect of initial soil salinity and salinity level of brackish subirrigation water on tuber weight of potato under simulated arid condition. The average root zone salinities were found to be 3.2–3.7 dS/m in lysimeters subirrigated with 1 and 9 dS/m of water, respectively. There was no signiWcant eVect of either initial soil salinity or subirrigation water salinity on the total tuber weight. Therefore, more work is needed to investigate the eVectiveness of WTM on soil salinity proWle and crop yield. Adoption of subirrigation system in semi-arid regions like Khoozestan province in the south and Moghan region in the northwest of Iran is feasible, due to the existence of a shallow water table. Discharge of massive amounts of brackish drainage water from the existing irrigated lands has imposed major environmental problems, which could signiWcantly be tempered using WTM systems. The objective of this study was to investigate the eVect of the subirrigation system on the salt proWle in the root zone of annual alfalfa in the semi-arid climatic conditions of Karaj, Iran. Materials and methods Lysimeter construction The study was carried out in 2005 and 2006 (March–July) in the research Weld at the Soil and Water Research Center of Tehran University (35°56
N, 50°58
E), in the city of Karaj, Iran. The study was conducted with 12 lysimeters installed in the middle of a 0.8-ha Weld (Fig. 1). The soil was excavated in order to place the lysimeters at a certain depth so that their top was on level with the ground surface. The excavated soil was then placed back into the lysimeters and the surrounding space, preserving the proWle similar to the Weld soil. The 1.5-m height lysimeters were made up of 0.7-m diameter polyethylene pipes, with the bottom end sealed with a circular Xat plate. A perforated pipe, 0.05 m in diameter, was installed just above the bottom of each lysimeter to allow the drainage of water through the lysimeter (Fig. 2). In the subirrigated lysimeters, the drain pipes were connected to a gauged riser pipe to maintain and control the water table to the speciWed depth. As the plants were consuming water from the water table, the level of water had to continuously be preserved at the speciWed depth. For this reason, a Marriot system was installed into the control chamber beside the lysimeters to automatically resupply the plant with water (Fig. 1). The depleted amount of water from the storage tank at a certain period of time could then be assumed as the net plant water use. The controlled water level in the lysimeters was also monitored by a piezometer installed in each one.

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چکیده

افزایش کمبود آب موجب به وجود آمدن محدودیت های جدی در پایداری تولید غذا در بسیاری از بخش های جهان گردیده است. به منظور مطالعه این وضعیت در سطح منطقه ای، ما ایران را به عنوان نمونه مورد مطالعه انتخاب کردیم و به تجزیه تحلیل این پرداختیم که چگونه یک راهبرد تجارت مجازی آب درون کشوری(VWTS) می تواند به بهبود تولید غلات و نیز حل مسئله کمبود آب کمک کند. این مسئله از نظر راهبردی تا حدودی مستلزم تعدیل و تنظیم ساختار الگوی کشت (ASCP) و تجارت غذای بین منطقه ای است که در آن عملکرد محصول و تولید کنندگی آب و نیز شرایط اقتصادی و اجتماعی در نظر گرفته شود. ما یک قالب کاری سیستماتیک را برای ارزیابی (ASCP) در سطح استانی تحت نیرو های محرک و محدودیت های متعدد ایجاد کردیم. یک مدل ترکیبی چند منظوره و خطی ایجاد و با روش برنامه نویسی خطی حل شد. داده های ۱۹۹۰-۲۰۰۴ برای توجیه نوسانات سالانه دسترسی به آب و تولید غذا استفاده شدند. ۵ سناریو با هدف بیشینه سازی تولید ملی غلات ضمن رسیدن به سطوح خود کفایی گندم تحت محدودیت های متعدد آب و خاک در تک تک استان ها طراحی شدند. نتایج نشان می دهد که تحت سناریوی معیار، که تداوم استفاده از آب موجود و سیاست غذا را در سطح ملی فرض می کند، برخی سناروی های (ASCP) می توانند تولید گندم بیشتری با آب کم تر کنند. بر اساس سناریو های متعدد (ASCP)، ما چنین نتیجه می گیریم که ۳۱ درصد تا ۱۰۰ درصد کمبود گندم کل در استان های دارای کمبود آب را می توان با استان های دارای گندم مازاد جبران و تامین کرد. در نتیجه، استان های دچار کمبود آب ۳.۵ میلیارد متر مکعب تا ۵.۵ میلیارد متر مکعب آب مجازی با وارد کردن گندم مازاد استان های دیگر را دریافت می کنند.

بخشی از مقاله انگلیسی:

Abstract. Increasing water scarcity has posed a major constraint to sustain food production in many parts of the world. To study the situation at the regional level, we took Iran as an example and analyzed how an intra-country “virtual water trade strategy” (VWTS) may help improve cereal production as well as alleviate the water scarcity problem. This strategy calls, in part, for the adjustment of the structure of cropping pattern (ASCP) and interregional food trade where crop yield and crop water productivity as well as local economic and social conditions are taken into account. We constructed a systematic framework to assess ASCP at the provincial level under various driving forces and constraints. A mixedinteger, multi-objective, linear optimization model was developed and solved by linear programming. Data from 1990– 2004 were used to account for yearly fluctuations of water availability and food production. Five scenarios were designed aimed at maximizing the national cereal production while meeting certain levels of wheat self-sufficiency under various water and land constraints in individual provinces. The results show that under the baseline scenario, which assumes a continuation of the existing water use and food policy at the national level, some ASCP scenarios could produce more wheat with less water. Based on different scenarios in ASCP, we calculated that 31% to 100% of the total wheat shortage in the deficit provinces could be supplied by the wheat surplus provinces. As a result, wheat deficit provinces would receive 3.5 billion m3 to 5.5 billion m3 of virtual water by importing wheat from surplus provinces. Correspondence to: K. C. Abbaspour (abbaspour@eawag.ch) 1 Introduction Population growth and industrialization on the one hand and extended drought, environmental concerns, and a possible adverse impact of climate change on the other hand are the major limiting factors on water resources threatening food security in developing countries of arid and semi-arid regions. With no significant room to expand cultivation areas in these regions, increased food demand will have to be met through sustainable agricultural production, which entails improved management of the available resources and development of crop production strategies (Qadir et al., 2007) as well as import from outside (Yang et al., 2006; Allan, 1997). Large parts of Iran are characterized as arid and semiarid environment. The country is enduring increasing water scarcity, which has posed a major constraint to the expansion of crop land and food production. Agriculture is by far the largest water user in Iran, accounting for more than 90% of the total water withdrawal. Despite the scarce water resources, wheat self-sufficiency has long been an important national goal, which was temporarily achieved in 2004. However, there is a general doubt about Iran’s ability to maintain this level of production amid the mounting water challenges, among other obstacles. In general, the agricultural water use efficiency is low in Iran. The average irrigation and conveyance efficiency is around 36% at the national level. For many provinces, the efficiency can be as low as 15%. Main reasons for low efficiency are improper design of irrigation facilities, poor maintenance, careless operation, negligible water pricing, as well as inefficient division of responsibilities among different agencies (Pazira et al., 1999; Kehsavarz et al., 2005). Efforts to increase the Published by Copernicus Publications on behalf of the European Geosciences Union. 1418 M. Faramarzi et al.: Analysis of intra-country virtual water trade strategy agricultural water use efficiency have been made through increasing crop water productivity (CWP) at plant and field levels (Ardakanian, 2005). But this has not so far alleviated the water scarcity problem, as in many areas the situation has been worsening. Facing the sober challenges, there have been renewed calls and efforts from the government of Iran to improve water resources management and plans to mitigate water scarcity. The long term policies are to invest on water projects, exploit new water resources, and investigate the benefits from adjustment of structure of cropping pattern (ASCP) to deal with the growing water shortages (National Research Council, NRC, 2005; The 5th World Water Forum by Iranian Ministry of Energy, 2009). So far, however, bulk of the investment is allocated for harnessing and regulating water resources via construction of dams, water transfer projects, and building irrigation networks (http: //icerik.worldwaterforum5.org/files/ThematicDocuments/ SessionDocuments/18 03 2009/Ayvansaray/). Little effort has so far been made in developing a strategy for ASCP. Iran currently has 19 million ha of agricultural land, accounting for 12% of the total area of the country. Of the total agricultural land, over 60% is devoted to wheat, 20% to barley, 5% to rice, 2% to maize and the rest of the land is covered by other crops. Cereals are the largest user of irrigation water. Of the total water diverted to irrigate cereal crops, wheat uses more than 70%. This amount of water exceeds the internal renewable blue water resources (IRWR) in many provinces located in central dry regions. Therefore, a large amount of water is extracted from fossil groundwater or water transfer projects to meet the water demand. It was found by Faramarzi et al. (2009) that about 53% of the area under cultivation of wheat in Iran is located in water scarce sub-basins. Of the total wheat production (10.83 million tons) in the country, 4.4 million tons of irrigated wheat and 1.9 million tons of rainfed wheat are produced every year in water scarce regions. This has a significant implication for future agricultural food production. The virtual water trade (VWT) introduced by Allan (1997) has been seen as one of the ways to improve water use ef- ficiency and to mitigate water scarcity at the regional level through ASCP and interregional food trade (Chapagain et al., 2006; Yang et al., 2006; Liu and Savenije, 2008; Liu et al., 2007). What we refer to as “virtual water trade strategy” (VWTS) in this paper involves adjustment of the structure of cropping pattern and interregional food trade where crop yield (y) and CWP, national food production objectives, as well as local economic and social conditions are taken into account as discussed in Sect. 2.2. VWT has so far been mainly studied in the arena of international trade. A set back in developing a clear VWTS internationally has been the exercise of trade sanctions imposed on importing countries at will. This although did not stop VWT, it had the effect of deterring the countries from formulating clear and long-term VWT strategies as an effective policy option for combating local water scarcities. The principles of VWT are also applicable within a country like Iran where there are lesser political barriers in interprovincial trades and significant regional variations in climate, resources and crop production. In such a situation, water resources can be used more efficiently at the national level if crops are produced in the regions/provinces where CWP is large and exported to the regions where CWP is small. However, any change in cropping structure is subject to many factors ranging from natural resources, ecological, socio-economic, and institutional conditions. Hence, there is a need for a systematic framework to support the policy makers in the planning of the structure of regional cropping pattern to meet certain national goals of food production while taking these constraints into consideration. Based on the best of our knowledge, so far such a study has not been seen in the virtual water literature. The current study is a novel step to develop a systematic framework for implementing VWTS in Iran through ASCP. Improving the water resources management through ASCP can be formulated as a multi-criteria analysis problem and solved by optimization methods. In the literature there are different techniques dealing with multi-criteria analysis problems. Very broadly they can be grouped into two categories: participatory based decision making processes and non-participatory based optimization techniques. The first category includes methods such as: multiple-criteria utility functions (e.g. Prato and Herath, 2007), analytical hierarchy process (AHP) (e.g. Mau-Crimmins et al., 2005), and Electre (e.g. Kangas et al., 2002; Figueria and Roy, 2002). In the second category, the techniques of linear programming (Makowski et al., 2000), genetic algorithms (Ines et al., 2006), meta modeling (Mousavi and Shourian, 2010), and goal programming (Foued and Sameh, 2001; Agha, 2006; Al-Zahrani and Ahmad, 2004; Yang and Abbaspour, 2007) are more widely used. The first category might not be relevant in this study because it is interview-based and calls for direct participations of decision makers and other stakeholders. As our project is large scale with multiple-criteria, the second category would be more suitable to apply. In the second category, goal programming is one of the popular multi-criteria optimization techniques used for water resources management and planning. It provides a way of considering more than one objective function. It sets a specific numeric goal for each objective, and then seeks a solution that maximizes the weighted sum of objectives while taking a set of constraints into consideration.

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