In order to study the effects of seed nitrogen content and biofertilizer priming on germination indices of wheat seeds under salinity stress, a factorial experiment based on a completely randomized design with four replications was conducted in 2009. Experimental factors consisted of: (1) the application of different nitrogen fertilizer rates (0, 55, 110 and 165 kg ha 71 N) on parent plants; (2) priming of achieved seeds by biofertilizers (Nitragin, Biophosphorus and distilled water); and (3) different levels of salinity produced by NaCl (0, 70.4, 70.8 and 71.2 MPa). Germination percentage, germination rate, mean germination time, germination index, radicle and plumule length, radicle and plumule dry weight and radicle number per seedling were measured. Nitrogen application increased seed nitrogen content in parent plants. All germination indices decreased with increasing in salinity levels. Biofertilizer priming, especially Nitragin, had a positive effect on germination percentage, radicle number and radicle and plumule length in most salinity levels. The highest values for germination factors were related to achieved seeds from parent plants that were treated with 110 kg ha 71 N. Overall, application of middle levels of N fertilizer (55 and 110 kg ha 71 N) on parent plants combined with seed priming with Nitragin biofertilizer improved the germination indices of wheat under salinity stress.
Optimal application rates of inorganic nitrogen (N), phosphorus (P) and cattle manure were estimated using Response Surface Methodology (RSM). A Central Composite Design (CCD) was conducted at field level during 2012-13 and 2013-14 growing seasons. The applied levels of N were 0, 150 and 300 kg N ha -1 in form of urea. The levels used for P fertilizer were 0, 100 and 200 kg ha -1 (P 2 O 5 ) and for cattle manure were 0, 15 and 30 t ha -1 . Both seed yield (SY), biological yield (BY) were measured at harvest time. N loss (NL) and Agronomic N Use Efficiency (ANUE) were calculated based on other measurements. Increasing N and P rates up to 200 kg ha -1 increased SY. Optimization of N, P and manure application amount was based on economic, environmental and eco-environmental scenarios. Under economic scenario, using 145.4 kg ha -1 N, 200 kg ha -1 P and 18.4 t ha -1 manure resulted in 6500 kg ha -1 SY with ANUE of 10.49. For environmental scenario, by N application of 21.2 kg ha -1 , no application of P and applying 16.3 t ha -1 manure, SY and ANUE of 3160 kg ha -1 and 9.08 were obtained, respectively. Using eco-environmental scenario, by applying 144.7 N and 34.3 kg ha -1 P, plus 30 t ha -1 manure, about 4031 kg ha -1 SY and a considerable high ANUE of 16.5 were recorded. The results of this study showed that the privilege of eco-environmental scenario compared to the other scenarios was mainly due to higher ANUE.
Background: The current knowledge does not prepare a precise scientific tool for quantifying the effects of inputs particularly ecofriendly inputs such as superabsorbent polymer (SAP) and humic acid (HA) are being used to increase soil fertility, improve crop performance and finally food production. This study was designed and conducted aimed to suggest an innovative approach not only to identify and quantify the effects of these inputs but also to determine the efficient path among underground/aboveground relationships associated with sesame oil production. Two experiments were conducted at the Research Farm of Ferdowsi University of Mashhad using randomized complete block design with split strip plot arrangement and three replications in two successive cropping years (2015-2016) to evaluate the effects of SAP and HA on Sesamum indicum L. growth characteristics and oil production under two different irrigation levels including: supplying 50 and 100% of the sesame water requirement were allocated to the main plots. Applying of SAP (80 kg ha −1) into the soil and control (no applying SAP) were allocated to the subplots. Foliar application of HA (6 kg ha −1) and control (not applying HA) were allocated to the strip plots. The analysis of variance revealed that the effects of HA and SAP on many sesame traits also soil properties were significant. Result: The fitted structural equation model suggests a direct strong-positive effect of leaf area index (LAI), plant height (PlantH) and water-use efficiency (WUE) on plant architecture construct (PlantArchitecture), soil nitrogen content (SoilN), soil electrical conductivity (SoilEC), and on soil properties construct (SoilProperties), which finally increase the sesame qualitative yield production. The calculation of the standard regression coefficients of the model's variables revealed that variables including: LAI, WUE and PlantPhysiology have had the most causal effect to defining the yield of sesame oil under the field condition of SAP and HA application. The findings in our study suggest that the direct advantages of SAP and HA application is to increase PlantPhysiology, PlantArchitecture and SoilProperties by 65, 50 and 17 percent, respectively, through contributing to the respective processes. Conclusion: Generally, the coefficient of determination of the suggested model (R 2 = 0.44) indicates that the model explains 44% of the variations in the sesame qualitative yield. The present study suggests employing the structural equation modeling could be best taken as a precise and practical quantitative modeling approach rather than a specific statistical technique, not only to quantify the effects of inputs and management operations but also helps
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.