کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4478523 1622927 2015 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modeling sorghum response to irrigation water salinity at early growth stage
ترجمه فارسی عنوان
مدل سازی پاسخ سورگوم به شوری آب آبیاری در مراحل اولیه رشد
کلمات کلیدی
جذب آب ریشه، مقدار آستانه شوری، نهال سورگوم
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم زراعت و اصلاح نباتات
چکیده انگلیسی


• Salinity threshold value for sorghum is 1 dS/m at seedling stage.
• Seedling rate of sorghum reduces to 50 percent at 11 dS/m soil salinity.
• All linear and nonlinear salinity response models overestimate threshold value.

Agricultural water management in arid and semi-arid regions largely depends on availability and quality of irrigation water at different plant growth stages. In saline environments, plant response to salinity varies at different growth stages. Information on plant response to salinity at various growth stages can be used in managing saline waters for irrigation. This study was conducted to quantitatively assess response of sorghum (Sorghum bicolor L. Moench) to salinity at seedling stage. Consequently, an extensive experiment in natural saline sandy loam soil with five natural saline water treatments including 4, 6, 8, 10, and 12 dS/m was conducted. The reason for selecting natural sources of saline water and a saline soil was to minimize deviations from natural conditions under which sorghum grows. Sorghum seeds were planted and seedles counted at 24 h time intervals. The macroscopic models of Maas and Hoffman, van Genuchten and Hoffman, Dirksen et al., and Homaee et al. were used to predict relative seedlings at different salinity levels. The obtained results indicated that salinity threshold value EC* for sorghum at seedling stage is 1 dS/m and the seedling rate reduces to 50 percent at 11 dS/m of soil salinity. All evaluated models overestimated the EC* value. Calculated statistics indicated that the nonlinear salinity models are more accurate than the linear model. Among those, Homaee et al. model provided better predictions at seedling growth stage.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agricultural Water Management - Volume 152, April 2015, Pages 119–124
نویسندگان
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