فهرست مطالب

نشریه دانش خاک و گیاه
سال سی و چهارم شماره 4 (زمستان 1403)
- تاریخ انتشار: 1403/10/01
- تعداد عناوین: 6
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صفحات 1-14
کاستی های روش های کلاسیک، ابداع سامانه اطلاعات جغرافیایی و تکنیک های سنجش از دور، ضرورت استفاده از نقشه برداری رقومی خاک را دوچندان نموده است. پژوهش حاضر برای بررسی توانایی تکنیک های یادگیری ماشین در توصیف پراکنش خاک ها در منطقه ای با وسعت حدود 5000 هکتار در غرب شهرستان هریس استان آذربایجان شرقی انجام شد. در این پژوهش از داده های بانک خاک، شامل ویژگی های فیزیکی و شیمیایی 50 خاکرخ و 50 مته که با استفاده از روش طبقه بندی تصادفی، حفر و تشریح شده بودند، استفاده شد. نتایج نشان داد که برای تمامی مدل های مورد مطالعه (رگرسیون درختی توسعه یافته، درخت تصمیم گیری تصادفی و شبکه های عصبی مصنوعی)، با پایین رفتن سطح رده بندی (از رده به گروه بزرگ)، مقادیر صحت عمومی کاهش یافت. از میان مدل های انتخابی، مدل رگرسیون درختی تعمیم یافته بالاترین کارایی را برای تخمین اکثر ویژگی های مورد مطالعه داشت، اما مناسب ترین مدل برای تخمین ویژگی های خاک، به طور حتم نمی تواند تخمین درستی از آن ویژگی های اراضی داشته باشد. از سوی دیگر، اگرچه مدل های مختلف از ویژگی های محیطی متفاوتی برای تخمین استفاده نموده اند، ولی اجزای اراضی، توانایی زیادی در تخمین ویژگی های خاک حتی در اراضی مسطح داشته اند. نتیجه گیری جامع و قطعی در مورد روش های نقشه برداری رقومی برای تخمین ویژگی های خاک در مناطق مسطح دارای ابهام است. شایان ذکر است که تخمین صحیح می تواند متاثر از تغییرپذیری ویژگی های خاک، مدل تخمین، تعداد نمونه های صحرایی و توانایی ویژگی های محیطی کاربردی در بیان تغییرات سطوح مختلف رده بندی باشد.
کلیدواژگان: رگرسیون خطی، شبکه های عصبی مصنوعی، کلاس های خاک، مدل های تخمینی، هریس -
صفحات 15-36
تا کنون توابع انتقالی نقطه ای و پارامتریک با روش های زیادی برای تخمین منحنی نگهداری آب خاک (SWRC) استفاده شده اند، اما از روش جنگل تصادفی (RF) با برخی متغیرهای ورودی تا کنون در هیچ مطالعه ای برای ایجاد توابع انتقالی شبه پیوسته استفاده نشده است. تعداد 120 نمونه خاک از دو استان تهران و همدان برداشت و ویژگی های فیزیکی آن ها اندازه گیری گردید. تعداد 10 تابع انتقالی شبه پیوسته با روش های رگرسیون خطی و RF ایجاد شد. از متغیرهای مکش آب خاک، بافت خاک، درصد رس و شن، جرم مخصوص ظاهری، میانگین و انحراف معیار هندسی قطر ذرات، و رطوبت در ظرفیت مزرعه ای (FC) و نقطه پژمردگی دائم (PWP) در ترکیب های مختلف برای تخمین SWRC استفاده شد. استفاده از مکش خاک به عنوان تنها متغیر ورودی برای تخمین SWRC در روش رگرسیون خطی، مدلی با نتایج قابل قبول ایجاد کرد (R2 مراحل آموزش و معتبرسازی به ترتیب 675/0 و 674/0 بود). استفاده از درصد رس و شن به عنوان تخمین گر موجب بهبود تخمین (5/1 تا 0/25 درصد) گردید. جرم مخصوص ظاهری موجب بهبود معنادار درستی تخمین ها در دامنه 9/6 تا 1/13 درصد گردید. بر خلاف PWP، استفاده از FC موجب بهبود درستی تخمین ها در دامنه 5/3 تا 4/24 درصد شد. توزیع خطا (RMSE) بر روی مثلث بافت خاک وابسته به نوع متغیرهای ورودی و روش ایجاد توابع بود. در تمام توابع شبه پیوسته، درستی تخمین ها، بر مبنای RMSE، در روش RF به طور معنادار و قابل توجهی در دامنه 22 تا 46 درصد بیشتر از رگرسیون خطی بود.
کلیدواژگان: انحراف معیار هندسی، توابع انتقالی شبه پیوسته، جنگل تصادفی، رگرسیون خطی، رطوبت ظرفیت مزرعه ای، میانگین هندسی قطر ذرات خاک -
صفحات 37-52
برای بررسی تاثیر ورمی کمپوست بر توزیع شکل های شیمیایی نیکل در خاک، آزمایشی به صورت فاکتوریل و در قالب طرح کاملا تصادفی با سه عامل ورمی کمپوست در سه سطح (0، 5 و 10 درصد وزنی)، نیکل در دو سطح (0 و 100 میلی گرم بر کیلوگرم) و زمان خوابانیدن در دو سطح (1 و 2 ماه) و با سه تکرار انجام شد. نمونه ها در طول دوره آزمایش (دو ماه) در دمای حدود 25 درجه سلسیوس و رطوبت ظرفیت مزرعه ای نگهداری شدند. توزیع شکل های شیمیایی نیکل، با روش عصاره گیری پی درپی تعیین گردید. نتایج نشان داد که در هر دو زمان (1 و 2 ماه)، کاربرد سطوح 5 و 10 درصد ورمی کمپوست سبب کاهش شکل های محلول + تبادلی، کربناتی و باقی مانده و افزایش شکل های آلی، پیوند یافته با اکسیدهای منگنز، اکسیدهای آهن بی شکل و اکسیدهای آهن بلورین شد. باتوجه به نقش مثبت ورمی کمپوست در کاهش زیست فراهمی نیکل خاک در طول زمان می توان نتیجه گرفت که مصرف این کود آلی در خاک های آلوده به فلزهای سنگین از جمله نیکل، می تواند خطرات محیط زیستی این فلزها را کاهش دهد. همچنین، باتوجه به دوره کوتاه زمانی به کار گرفته شده در این پژوهش پیشنهاد می شود که اثر طولانی مدت ورمی کمپوست بر زیست فراهمی نیکل و سایر فلزهای سنگین در زمان های طولانی تری نیز بررسی شود.
کلیدواژگان: خاک های آهکی، شکل محلول و تبادلی، فلزهای سنگین، عصاره گیری پی در پی، کودهای آلی -
صفحات 53-73
شناسایی وضعیت عناصر غذایی گیاه برنج در خاک و گیاه برای مدیریت تغذیه آن ضروری است. در اراضی شالیزاری از نتایج تجزیه خاک برای تخمین فراهمی عناصر غذایی استفاده می شود؛ اما همیشه وضعیت این عناصر با عملکرد گیاه مرتبط نیست؛ از این رو، از روش تشخیص چندگانه عناصر غذایی (CND) می توان در تفسیر نتایج تجزیه گیاه و بهبود مدیریت تغذیه گیاه برنج استفاده نمود. این پژوهش با هدف تعیین اعداد مرجع، دامنه غلظت مطلوب و محدودیت عناصر غذایی برای برنج، به روش CND در 60 مزرعه اراضی شالیزاری استان گیلان انجام شد. نمونه های مرکب خاک و برگ از مزارع زارعان جمع آوری و با استفاده از روش های استاندارد آزمایشگاهی تجزیه شدند. همچنین، عملکرد دانه برنج در هر مزرعه و شاخص های عناصر غذایی به روش CND تعیین شدند. با استفاده از مدل تابع تجمعی نسبت واریانس عناصر غذایی و از حل معادلات تابع تجمعی درجه سه مربوط به 10 عنصر غذایی به همراه غلظت باقی مانده، عملکردهای مرتبط با هر یک از آن ها محاسبه شدند و برای نیتروژن 76/3، فسفر 97/3، پتاسیم 95/3، کلسیم 99/3، منیزیم 01/4، گوگرد 99/3، آهن 98/3، منگنز 98/3، روی 0/4، مس 10/4 و عناصر باقی مانده (Rd) 71/16 به دست آمد. بر اساس میانگین عملکردهای محاسبه شده، عملکرد هدف به مقدار 13/4 تن در هکتار تعیین و با توجه به آن، 3/43 درصد از مزارع انتخابی در گروه با عملکرد زیاد و 6/56 درصد از آن ها در گروه با عملکرد کم قرار گرفتند. مهمترین عناصر غذایی مورد نیاز در اراضی مطالعه شده منیزیم، فسفر، مس و روی بودند. یافته ها نشان داد که روش CND می تواند به عنوان یک ابزار تفسیر نتایج آزمون خاک و تجزیه گیاه در مدیریت تغذیه گیاه برج استفاده شود.
کلیدواژگان: برنج، خاک های شالیزار، عملکرد، مدیریت تغذیه گیاه، تعادل عناصر غذایی -
صفحات 75-90
با توجه به پدیده گرمایش جهانی و اثر آن بر تولید محصولات کشاورزی، ارزیابی اثرات تغییر اقلیم بر تولید سیب زمینی در کشور ضروری است. بدین منظور از داده های مدل اقلیمی CanESM2، تحت سناریوهای انتشار RCP در مناطق عمده کشت سیب زمینی (اردبیل، تبریز، شهرکرد، همدان، جیرفت، کهنوج، منوجان، اصفهان، سنندج و شیراز) استفاده شد. از مدل آماری SDSM، برای ریزمقیاس نمایی خروجی مدل CanESM2، و از مدل WOFOST برای شبیه سازی عملکرد غده سیب زمینی استفاده شد. در این مطالعه مدل WOFOST با استفاده از داده های مزرعه ای سال های 1389، 1390 و 1392 واسنجی و با داده های سال های 1391 و 1393 اعتبارسنجی شد. نتایج به دست آمده از شاخص های آماری، نشان از دقت بالای مدل SDSM و مدل WOFOST و مطابقت نتایج واسنجی و اعتبارسنجی با داده های دیدبانی بود. نتایج حاصل از شبیه سازی عملکرد غده سیب زمینی در شرایط اقلیم آینده حاکی از کاهش میزان عملکرد در مناطق مورد مطالعه بود؛ به طوری که بیشترین کاهش عملکرد در دوره سوم و در سناریوی RCP8.5 بود. در مناطق مورد مطالعه به طور میانگین بیشترین و کمترین کاهش میزان عملکرد به ترتیب مربوط به ایستگاه اردبیل با 2397 و سنندج با 813 کیلوگرم بر هکتار بود. به طور میانیگین، در مناطق مورد مطالعه به میزان 1463 کیلوگرم بر هکتار کاهش عملکرد غده سیب زمینی مشاهده شد. نتایج به دست آمده از شبیه سازی عملکرد غده سیب زمینی نشان داد که با افزایش دما، میزان عملکرد غده نیز کاهش می یابد، به طوری که به ازای یک درجه سلسیوس افزایش میانگین دمای سالانه، عملکرد غده به میزان 77/3 درصد کاهش خواهد یافت. با توجه به نتایج حاصل از این پژوهش، بهترین راهکار برای انطباق با تغییرات اقلیمی، تغییر تاریخ کشت و انتخاب رقم های زودرس برای کوتاه تر شدن طول دوره رشد گیاه سیب زمینی می باشد.
کلیدواژگان: تغییر اقلیم، سناریوهای RCP، سیب زمینی، عملکرد غده، مدل WOFOST -
صفحات 91-113
این پژوهش با هدف بررسی تاثیر برهمکنش فسفر و بیوچار حاصل از کاه گندم پیرولیز شده در دمای 300 درجه سلسیوس بر رشد و جذب کلسیم، منیزیم و برخی عناصر غذایی کم مصرف به وسیله گیاه کلزا (Brassica napus L.) رقم هایولا 308 در یک خاک قلیایی با بافت لوم در شرایط گلخانه ای انجام شد. این آزمایش به صورت فاکتوریل و در قالب طرح کاملا تصادفی با سه تکرار اجرا گردید. فاکتورهای آزمایش شامل ماده آلی در پنج سطح (بدون مصرف ماده آلی، 20 و 40 گرم بر کیلوگرم خاک از دو منبع کاه گندم و بیوچار حاصل از آن) و فسفر در سه سطح (صفر، 20 و 40 میلی گرم فسفر بر کیلوگرم خاک از منبع سوپرفسفات تریپل) بودند. بعد از برداشت گیاه ماده خشک شاخساره و غلظت و مقدار کلسیم، منیزیم، آهن، روی، مس و منگنز در شاخساره کلزا اندازه گیری شدند. نتایج نشان داد که کاربرد کاه گندم وزن خشک شاخساره کلزا را به طور معناداری نسبت به شاهد کاهش داد اما در هر دو سطح کاه گندم (2 و 4 درصد) مصرف کود فسفر نسبت به تیمار بدون فسفر، وزن خشک شاخساره را افزایش داد. این یافته نشان دهنده غیرمتحرک شدن احتمالی فسفر بر اثر مصرف کاه گندم و اثر مثبت کود فسفر در این شرایط بود. در شرایط این پژوهش، بیوچار مصرفی در هر دو سطح 2 و 4 درصد باعث افزایش ماده خشک شاخساره کلزا به ترتیب به میزان 46 و 57 درصد نسبت به شاهد شد. مصرف توام کاه و فسفر مقدار جذب کلسیم، منیزیم، آهن و مس را در هر دو سطح 2 و 4 درصد بیوچار نسبت به شاهد کاهش داد؛ اما مقدار جذب روی و منگنز را در سطح 2 درصد بیوچار افزایش ولی در سطح 4 درصد آن کاهش داد. با توجه به نتایج به دست آمده از این تحقیق استفاده از بیوچار حاصل از کاه گندم تولید شده در دمای 300 درجه سلسیوس جذب آهن ، روی و منگنز را افزایش داد که سبب بهبود خصوصیات رشد گیاه کلزا گردید.
کلیدواژگان: بیوچار، کود، کاه گندم، کلزا، فسفر
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Pages 1-14Background and Objectives
The use of geospatial techniques for mapping soils is broadly covered by the term digital soil mapping (DSM). Soil maps have considerable significance as basic maps in many environmental and natural resources studies. Digital soil maps are based on the relationship between environmental variables and soil properties. With the development of computers and technology, digital and quantitative approaches have been developed. Continuous utilization of agricultural lands regardless of the land suitability caused soil destruction. Also, incompetency in custom methods, invention geographic information system (GIS), and remote sensing (RS) techniques cause erupt and use of digital soil mapping.
MethodologyThe study area is approximately 5000 ha which is located in the west of Heris region of East Azerbaijan province, Iran. In the first study, the potential of different models to predict soil classes at different taxonomic levels was investigated. According to semi-detailed soil, survey and using stratified random sampling method, 50 pedons and 50 augers with an approximate distance of 1000 m were excavated, described and soil samples were taken from different genetic horizons. Based on the pedon descriptions and soil analytical data, pedons were classified up to the family level. Different machine learning techniques, namely boosted regression tree (BRT), random forest (RF), artificial neural networks (ANNs), and multinomial logistic regression (MLR) were used to test the predictive power for mapping the soil classes. After preparing the soil properties maps and checking their accuracy, these maps were used along with auxiliary parameters for estimating soil classes using an artificial neural network model in the R software. Finally, the accuracy and uncertainty of the model were evaluated by overall accuracy and confusion index, respectively.
ResultsResults showed that the different models had the same ability for prediction of the soil classes across all taxonomic levels but a considerable decreasing trend was observed for their accuracy at subgroup and family levels. The terrain attributes were the most important auxiliary information to predict the soil classes up to the family level. The main goal of the second study was to predict soil surface properties (pH, electrical conductivity, gypsum, organic carbon, calcium carbonate equivalent, coarse fragments, and particle size distribution) using ANNs, BRT, generalized linear model (GLM), and multiple linear regression (MLR). Among the studied models, GLM showed the highest performance to predict most soil properties whereas the best model is not necessarily able to make an accurate estimation. Also, the terrain attributes were the most important environmental covariates to predict the soil classes in all taxonomic levels, but they could not display the soil variation entirely. This shows that the unexplained variations are controlled by unobserved variations in the environment, which can be due to the management over time. Results suggested that the DSM approaches have not enough prediction accuracy for the soil classes at lower taxonomic levels that focus on the soil properties affecting land use and management. Results showed that the entry of more details in the soil classification at the lower levels of the Soil Taxonomy system while increasing the number of classes, leads to decreasing the overall accuracy and increasing uncertainty. It is noticeable that the ANNs model has a good accuracy up to the great group level through the acceptable level of overall accuracy (i.e., 75 %), hence it has a high degree of uncertainty. Therefore, the accuracy of the model could not be effective in its selection through the modeling process; however, paying attention to its uncertainty is also very important along with the model error.
ConclusionTerrain attributes were the main predictors among different studied auxiliary information. The accuracy of the estimations with more observations is recommended to give a better understanding about the performance of DSM approach over low-relief areas. Further studies may still be required to distinguish new environmental covariates and introduce new tools to capture the complex nature of soils. Accordingly, we suggest using the other methods of soft computing for modeling in plain areas or low relief regions. Finally, the use of DSM methods is increasing over time and will eventually be considered as distinct and novel techniques.
Keywords: Artificial Neural Network, Heris, Linear Regression, Prediction Models, Soil Classes -
Pages 15-36Background and Objectives
Direct methods of measuring soil water retention curve (SWRC) are time-consuming and expensive, so they are not easily applicable to large scales. Therefore, researchers use pedotransfer functions (PTFs) to obtain it. Various point and parametric pedotransfer functions have been used so far, with numerous methods to estimate the SWRC, each of which has its drawbacks. However, rare methods have been used to develop pseudo-continuous pedotransfer functions. The random forest (RF) method has not been utilized in any study so far, to create pseudo-continuous pedotransfer functions. Some variables have not been used as predictors in pseudo-continuous pedotransfer functions in any research. Therefore, the objectives of this article include investigating the potential of the RF method in creating pseudo-continuous pedotransfer functions, comparing its performance with linear regression, and examining the probability of improving the performance of these functions using the geometric mean and standard deviation of particles diameter and field capacity (FC) and permanent wilting point (PWP) as predictors.
MethodologyA total of 120 disturbed and undisturbed soil samples were collected from two provinces of Tehran and Hamedan. Soil texture, bulk density, and soil water retention curve in the range of 0 to 15000 hPa were measured. Then pseudo-continuous pedotransfer functions were created using two methods of linear regression and random forest. The soil water matric suction, soil texture, percentage of silt and sand, bulk density, geometric mean, standard deviation of particles diameter, and moisture content at FC and PWP were used in various combinations to estimate the soil water retention curve. The accuracy and reliability of the generated functions were compared between the two methods and within each method.
ResultsUsing soil water matric suction as the only input variable for estimating moisture at different matric suctions was not effective in the RF method, and no model was created. However, in the linear regression method, a model with acceptable results was developed (with R2 values of 0.675 and 0.674 for training and validation stages, respectively), which can be utilized in situations where additional information is not available. The inclusion of soil texture in the linear regression method significantly improved the accuracy of estimates by 5.4% and 5.3% in both training and validation stages, respectively. In the third function, incorporating the percentage of clay and sand alongside soil water matric suction as predictors improved SWRC estimation by 1.5% to 25.0% in both training and validation stages for both RF and linear regression compared to the second function. In the fourth function, using bulk density as an additional predictor led to a significant improvement in accuracy by 6.9% to 13.1%, because bulk density serves as an indicator of soil structure, enhancing the estimation of the soil water retention curve. Utilizing FC improved estimation accuracy by 3.5% to 24.4%, because FC is a point on the SWRC and enters direct information to the models. However, using the PWP as a predictor did not significantly improve estimation accuracy. Using geometric mean (dg) and geometric standard deviation (Sg) instead of percentage of clay and sand in pseudo-continuous pedotransfer functions did not lead to noticeable improvements. Error distribution across soil texture triangles in the linear regression method showed no dependence on soil texture. Because, in pedotransfer functions 1, 2, 4, 7, and 8, the highest error values were obtained in coarse-textured soils, while in pedotransfer functions 5, 6, 9, and 10, the lowest error values were associated with coarse-textured soils. Error distribution across soil texture triangles depended on the type of input variables and the method used to create pedotransfer functions. In all pseudo-continuous pedotransfer functions created by both methods, the accuracy of estimates in both training and validation stages in the RF method was significantly and noticeably higher, ranging from 22% to 46% more than those in linear regression.
ConclusionUsing the regression method and solely relying on soil water matric suction as a predictor, an acceptable pseudo-continuous pedotransfer function was developed. Investigating the potential of establishing a similar relationship using the state-of-the-art estimation methods may lead to independence from relying on numerous soil water retention curve models. Utilizing more detailed information such as particle size distribution and FC for estimating the SWRC through pseudo-continuous pedotransfer functions is recommended. The dependence of error distribution on soil texture triangles on the type of input variables and the method used to create pedotransfer functions underscores the importance of selecting an appropriate combination of input variables and method for creating pseudo-continuous pedotransfer functions for estimating the SWRC. Given the significant superiority of the random forest method over linear regression, using soil water matric suction, percentage of clay and sand, bulk density, and FC as predictors in pseudo-continuous pedotransfer functions with the RF method yielded the best results in estimating the SWRC.
Keywords: Geometric Mean Diameter, Geometric Standard Deviation, Pseudo-Continuous Pedotransfer Functions, Random Forest, Soil Moisture -
Pages 37-52Background and Objectives
One of the major environmental problems is soil and water pollution with heavy metals in human societies. One of the main reasons for increasing the availability of heavy metals in the soil is the excessive use of chemical fertilizers, pesticides, as well as the entry of municipal and industrial wastewaters into the soil environment. Nickel (Ni) is one of the heavy metals but essential elements for plants. This metal is a part of urease enzyme and plays an important role in nitrogen metabolism. But its excessive accumulation reduces the nutritional value of plants. Heavy metals show different behaviors with the passage of time according to the type of soil and its components; So that with the passage of time, their availability for plants root is reduced and they become less soluble. Heavy metals are observed in the soil in the form of soluble, exchangeable complexes, connected to carbonates, oxides and hydroxides of iron and manganese, organic substances, and in the form of a part of the structure of minerals. Determining the chemical forms of heavy metals using successive extractors helps to relate their chemical forms in the soil, evaluate their availability and leaching. In fact, it can show the destructive and environmental effects of heavy metals in the soil. Nowadays, the use of organic fertilizers has increased in reducing the bioavailability of heavy metals and converting them into less soluble forms. Nickel is a nutrient for plants, humans, and animals, but its high concentrations can cause toxicity in these organisms. Therefore, it seems necessary to study the change of shape and its transformation over time in the environment on the growth and health of plants and animals. Therefore, in this study, we investigate the effect of time duration on the forms and chemical components of Nickel in a calcareous soil under the different levels of vermicompost application.
MethodologyIn order to investigate the effect of vermicompost application on the distribution of chemical forms of nickel in the soil, a factorial experiment was conducted on the basis of a completely randomized design with three factors of vermicompost at three levels (0, 5, and 10 % by weight), nickel at two levels (0 and 100 mg Ni/kg), and time duration at two levels (1 and 2 months) with three repetitions in greenhouse conditions. In order to contaminate the soil, first, 500 grams of soil was weighed for each pot, then different levels of nickel nitrate were added to the soil samples by spraying. After drying, the pot soil samples were completely mixed and the desired levels of vermicompost were added to them. During the test period, the samples were incubated at 25 °C and the moisture of the samples were also kept at field capacity. In order to ventilate and create aerobic conditions, a hole with a diameter of several millimeters was created on the lid of the samples. In the first stage, one month after contaminating the studied soil with nickel, 1 gram of soil was removed from each pot and the chemical forms of nickel including solution + exchange, carbonate, organic, and bound to manganese and iron oxides were measured. In the second stage (2 months after contaminating the soil), the steps of the first stage were repeated. Finally, SAS software and Duncan's multiple range test were used for statistical analysis of the data.
ResultsThe results of this research showed that vermicompost application had different effects on the chemical forms of nickel over time, so that in both times (1 and 2 months) the application of 5 and 10 % of vermicompost caused a decrease in the form of soluble + exchangeable, carbonate, and residual nickel, while it increased the nickel concentration in the forms of organic-bound, and bounded to manganese oxides, amorphous iron oxides, and crystalline iron oxides.
ConclusionConsidering the results of this research and the positive effects of vermicompost application in reducing the bioavailability of soil nickel over time, it can be concluded that application of this organic fertilizer can reduce the environmental risks of this heavy metal in contaminated soils. Also, considering the short period of time used in this research, it is suggested to investigate the long term effect of vermicompost on the bioavailability of nickel and other heavy elements in longer periods of time.
Keywords: Calcareous Soils, Fractionation, Heavy Metals, Organic Fertilizers -
Determining limitation of nutrients for rice using the compositional nutrient diagnosis (CND) methodPages 53-73Background and Objectives
Nutrient limitations often reduce crop yield in farmers' fields. Identifying the status of rice plant nutrients in the soil and plant is necessary for plant nutrition management. In rice plant, it is common to use soil chemical properties test to understand the availability of soil nutrients. Although soil tests based on critical level may indicate the adequacy of nutrients, sometimes the rice plant in the field exhibit signs of its deficiency. Flooding conditions in rice cultivation leads to chemical and electrochemical changes in some nutrients, which result in inadequate nutrient uptake by the plant. Solely relying on soil testing in such conditions increase errors in results interpretation and fertilizer recommendations. Therefore, measuring the nutrients characteristics of both plant and soil can be effective in fertilizer recommendations. One method for interpreting leaf analysis results is the use of compositional nutrient diagnosis (CND) method. The aim of this study was to establish reference norms, the range of optimal concentration and nutrients limitation in rice plant using the CND method during 2018 growing season in 60 paddy fields of Guilan province, Iran.
MethodologySoil and leaf composite samples were collected from farmers' fields in a standard manner and analyzed using appropriate laboratory methods. At harvest time, the yield of each field was determined. Nutrient indices were assessed by the compositional nutrient diagnosis (CND) method. By employing the cumulative function model of the variance ratio of nutrients and solving third-degree cumulative function equations related to 10 nutrients along with their residual concentrations, yields corresponding to each of them were calculated in terms of tons per hectare. To categorize the yield community into favorable and unfavorable groups, initially, the yield-nutrient function was plotted and the yield groups were separated by identifying the inflection points of the curve. To validate the compositional nutrient diagnosis method, the relationship between the nutrition balance index (r2) and crop yield was evaluated through a scatter plot. Descriptive statistics were conducted using SPSS version 24 and CND calculations were performed using Excel software.
ResultsBased on the average of available phosphorus concentration and its critical level 47% of the fields exhibited phosphorus deficiency. According to the critical level of available potassium, except for one farm, the available potassium content exceeded the critical level in all fields. Due to the fact that the minimum amount of micronutrients (zinc, iron, copper, and manganese) was more than their critical level in paddy fields, indicating no deficiency in the studied soils. Available magnesium concentration ranged from 0.8 to 4.6 with the median of 2.4 cmol+/kg. Nearly 75% of the studied soils were deficient in magnesium, based on the critical level of available magnesium (3 cmol+/kg).The average phosphorus concentration in leaves was 0.23% and based on the critical level, there was phosphorus deficiency in two fields. The average potassium concentration in the sample of leaves collected from the fields was 1.57% and based on the critical level, potassium deficiency was observed in rice plant tissue in 55% of the fields. The average magnesium concentration in rice leaf samples was 0.17% and six farms showed deficiency based on the magnesium critical level. The average zinc concentration was 13.69 in rice leaf samples and based on zinc critical level, 58 farms (96%) showed zinc deficiency. Based on the calculated average yields, the target yield was determined as 4133 kg/hectare, and according to the target yield, 43.3% of selected fields were classified as high-yielding and 56.6% were classified as low-yielding group. The CND method correctly recognized the balance of nutrients in rice plant with 55% accuracy. The relationship between yield and nutrients balance index showed that 31% of fields had nutritional balance, 24% had nutritional unbalanced, 22.4% had yield reduction other than nutritional factors such as climate, root depth limitations, pests, and diseases.
ConclusionThe findings showed that: 1- Using only the critical level of soil and plant nutrients for assessing the nutritional status of soil and plants was not efficient in the studied paddy fields. 2- The CND method, due to its consideration of the interactive effects of nutrients, had greater capability than the critical level method in diagnosing nutritional disorders, nutrient deficiencies, and fertilizer recommendations for the studied paddy fields. However, it was not the most accurate, sensitive and unique because factors other than soil fertility and rice plant nutrition, such as climatic conditions and irrigation, and field management, also influence the growth and development of rice plant and its yield. 3- The most important macronutrients and micronutrients needed in studied paddy soils based on the CND method were magnesium and phosphorus (macronutrients) and copper and zinc (micronutrients). 4- The CND method can be as an effective tool for interpreting soil and plant analysis in plant nutrition management at paddy farming systems.
Keywords: Nutrient Balance, Paddy Soils, Plant Nutrition Management, Rice, Yield -
Pages 75-90Background and Objectives
After wheat, rice and corn, potato is the fourth product in the food basket of human societies, which shows the importance of its role in providing protein and food needs of people. Potatoes contain large amounts of vitamins A, B1, B2, and C along with potassium, phosphorus, and calcium, and consumption of 300 grams of potatoes tuber per day provides more than 50% of the human need for vitamin C and potassium. The World Food and Agriculture Organization (FAO) has introduced potatoes as a product that provides future food security in the world, and the country of Iran, having a diverse climate and with an annual production of five million tons of potatoes, ranks thirteenth in the production of this product in the world. So, in this research, the consequences of climate change on the yield of potato tuber, the statistics of the production values, and the area under cultivation of potatoes were evaluated.
MethodologyThe dada of Ardabil, Tabriz, Shahrekord, Hamadan, Jiroft, Kohnouj, Manojan, Isfahan, Sanandaj, and Shiraz stations in the statistical period of 1982–2015 were used. The mentioned regions are among the main centers of potato production in the Iran and account for 62.7% of the cultivated area and 68.3% of the country's potato production. In this research, the production and performance data of 10 meteorological stations inside Iran were used and the data of the fifth report of the Representative Concentration Pathway scenarios (RCPs) have been used to evaluate the consequences of climate change on potato tuber yield.In order to prepare field data for calibration and determining the validity of the WOFOST model in potential conditions (conditions without water and nutrients restrictions, disease, and weed control) the data of the Agricultural Research Stations of Hamedan, Isfahan, Ardabil, Shiraz, Tabriz, Shahrekord, Jiroft, Kohnouj, Manojan and Sanandaj were collected during 2010-2014 and used as a base or monitoring period.This information includes planting date, phenological stages from planting to germination, germination to flowering, and germination to physiological maturity of the potato plant in each of the regions.The SDSM statistical model was used for downscalling of CanESM2 model data, and the WOFOST model was used to simulate the performance of the potato tuber. In order to calibrate the WOFOST model using field data, the phenological and performance data in the years of 2010, 2011, and 2013 were used to calibration of the model, and from phenological and performance data in the years of 2012 and 2014 were used to determine the validity of the model. In order to calibrate and determine the validity of the WOFOST model in the study areas, it is first necessary to adjust the potato plant parameters (coefficients) for different climatic conditions. Therefore, the creation of the plant file, which is the most sensitive part of WOFOST model calibration, was done for tuber performance. In this study, WOFOST version 7.1 was used. This model uses parameters and functions to describe the effects of temperature, radiation and water stress on the main processes of crop growth. The outputs of the model include the final yield, leaf area index, crop growth rate, dry matter accumulation rate in each organ, and development stages with one-day intervals. The calibration of the model and the determination of the coefficients of the model were done in such a way that the expected performance of the tuber was simulated by the WOFOST model. Parameters of specific leaf area as a function of development stage (SLATB), maximum leaf CO2 assimilation rate as a function of development stage of the crop (AMAXTB), efficiency of conversion into leaves (CVL), efficiency of conversion into roots (CVR), efficiency of conversion into stems (CVS) and Lower threshold temperature for emergence (TBASEM), which were necessary for the simulation of gland function, were calibrated and determined based on the permissible range of model coefficients changes and using resources. Then, in order to simulate the potential performance of the potato plant for all 10 study areas and every five years, with conventional planting dates and also with a range of planting dates (three dates) a total of 150 loads were executed.
ResultsAccording to the obtained results, the average yield for the 10 studied stations was 46190 kg/ha for the calibration stage and 44434 kg/ha for the validation data. In the model implementation stage, the average yield during five years for the 10 studied stations was 45919 kg/ha for calibration and 43813 kg/ha for the validation stage by the model. Therefore, by evaluating the statistical indicators, the WOFOST model has high accuracy for simulating performance in all regions.
ConclusionThe results of the simulation of the yield of potato tuber under the future climate conditions indicated a decrease in yield in the studied stations. Thus, the greatest decline in performance was observed in the period of 2071-2099 and under the RCP8.5 scenario. In the studied areas, on average, the highest yield decrease was related to Ardebil station with 2397 kg/ha and Hamedan with 1817 kg/ha, and the lowest decrease in the yield of potato belonged to Sanandaj station with 813 kg/ha and Isfahan station with 982 kg/ha. On average, in the 10 studied areas, a decrease in potato tuber yield was observed by 1436 kg/ha. Reducing the length of the potato ripening period has the biggest contribution in reducing the potato tuber yield. The results obtained from the simulation of the yield of potato tuber showed that in parallel with the increase in temperature, the yield of potato also decreases, so that for one degree Celsius increase in the average annual temperature, the yield of potato will decrease by 3.77%.
Keywords: Climate Change, Potato, Rcps Scenarios, Tuber Performance, WOFOST Model -
Pages 91-113Background and Objectives
Phosphorus (P) is a macronutrient that its deficiency severely limits plant growth and production. Because of the complexity of P chemistry in soil, less than 30% of applied P fertilizer is absorbed by plants and the rest in the soil converts to unavailable forms. Organic matter can be applied to the soil to reduce soil P fixation and increase soil P bioavailability because organic matter and its decomposition products (e.g., organic acids) occupy the surfaces of phosphate adsorbents in soils and prevent the precipitation of phosphate compounds. During pyrolysis of organic material a complex mixture of P species is formed, which may include amorphous, semi-crystalline, and crystalline constituents, along with organic constituents. However, organic P forms will tend to disappear while inorganic P forms will subsequently be formed and crystallinity will increase with increasing pyrolysis temperature. The crystalline P minerals that have been identified in biochars include whitlockite [(Ca, Mg)3(PO4)2] pyrolysed from manure at 500 °C, dehydrated struvite (NH4MgPO4) produced from cattle manure and sewage sludge, and hydroxyapatite [Ca10(PO4)6(OH)2] made from slaughterhouse waste and from mixtures of that waste with either corn residue or wood. The crystallinity of hydroxyapatite was lower when corn residues or wood were added to the slaughterhouse waste and as result increased the soluble P fraction. To the best of the authors’ knowledge, the evidence to support the impact of biochar on P sorption and desorption in Iranian soils is scarce while taking account of the fact that P deficiency is dominant in approximately 72% of the arable soils. So, in this research, the effects of combined application of biochar pyrolysed at 300 ˚C and P fertilizer on dry matter and uptake of calcium (Ca), magnesium (Mg), iron (Fe), zinc (Zn), copper (Cu), and manganese (Mn) by rapeseed (Brassica napus L.), Hyola 308 cultivar, were studied in an alkaline loamy soil under greenhouse conditions.
MethodologyAfter being washed with deionized water, wheat straw samples were milled, sieved < 1 mm, and then were oven-dried at 60 ºC for 24 h. The biochars were produced by slow pyrolysis of wheat straw at 300 ºC for 1 h under argon (Ar) gas flow at the heating rate of 10 ºC per minute. The produced biochars were transported in plastic containers for later analysis. Afterward, a factorial experiment was done on the basis of a completely randomized design with three replications. The factors were organic matter at 5 levels (no organic matter application, wheat straw 2%, wheat straw 4%, biochar 2%, and biochar 4%) and phosphorous (P) fertilizer at 3 levels (0, 20, and 40 mg/kg) as triple superphosphate. After the plant harvesting, shoot dry matter and the concentration and content of Ca, Mg, Fe, Zn, Cu, and Mn in plant shoot were determined by Atomic Absorption Spectrophotometer.
ResultsWheat straw application significantly reduced rapeseed shoot dry matter compared to the control. At each level of wheat straw (2 and 4%), P application significantly increased shoot dry matter as compared to the control treatment. Under wheat straw application conditions, the using both levels of P (20 and 40 mg/kg) significantly increased shoot dry matter. This finding indicates the possible immobilization of P due to wheat straw application and the positive effect of P fertilizer under these conditions. Using biochar at both levels of 2 and 4 percent increased the rapeseed shoot dry matter by 46 and 56.5 percent, respectively, compared to the control. The combined application of straw and P reduced the Ca, Mg, Fe, and Cu uptake at both levels of biochar (2 and 4 %) compared to the control. However, the content of Zn and Mn increased at the biochar level of 2% compared to the control, but significantly decreased at the biochar level of 4% compared to the control.
ConclusionAccording to the results obtained from this research, the use of biochar produced from wheat straw at the temperature of 300˚C increased the uptake of Fe, Zn, and Mn, which led to the improvement of the growth characteristics of rapeseed. In this research, the effect of biochar on the Cu concentration and content in shoot unlike other nutrients was negative. According to the results, the wheat straw drived biochar at 300 °C improved rapeseed plant growth characteristics and nutrients uptake except Cu. Also, application of biochar and P at 2% and 20 mg/kg levels, respectively, is recommended to reduce the consumptions of P fertilizer without yield reduction of rapeseed in under similar conditions. In addition, application of wheat straw at 2 and 4 % levels is not recommended and future research should be done at its lower levels. Finally, it was concluded that biochar may play an important role in soil fertility and plant production, so further research should continue.
Keywords: Biochar, Fertilizer, Phosphorus, Rapeseed, Wheat Straw