mohammad javad mostafavi

Due to rapid population growth and the reduction of arable land, the most effective way to increase crop yields is by boosting production per unit area. So far, many studies have shown the positive effect of intercropping on LAI (Leaf area index), TDM (Total dry matter) (g.m-2), CGR (Crop growth rate) (g.m-2.day-1), RGR (Relative growth rate) (g.g-1.d-1), and NAR (Assimilation rate) (g.m-2Leaf.day-1) growth indices, and so on. Therefore, this study aimed to evaluate and compare the yield and growth indices of green bean and black seed in sole culture and replacement intercropping ratios. 

The experiment was conducted based on RCBD design during the growing season 2018-19. Treatments included replacement intercropping ratios including 25% green bean + 75% black seed (P1N3), 50% green bean + 50% black seed (P2N2), 75% green bean + 25% black seed (P3N1), and sole culture of green bean (P) and black seed (N). Irrigation was done once a week, and sampling was performed once every 10 days. The effect of different replacement intercropping ratios on growth indices during the growth period was investigated. The curve function was fitted using Slide Write ver 2.0 software, and Excel 2016 was used to draw figures.

The results showed that the treatments affected the growth indices of green bean and black seed. The highest LAI of bean and the black seed (3.53 and 0.5) were observed in the sole culture of these crops. The lowest LAI of green bean (1.14) and black seed (0.2) were obtained in P2N2 and P3N1 treatments. The sole cultures had the highest TDM for green bean (973.34 g.m-2) and black seed (339.55 g.m-2). The lowest TDM of green bean and black seed were observed in P1N3 (164.25 g.m-2) and P3N1 (91.18 g.m-2) treatments, respectively. The highest crop growth rate (CGR) of green bean (10.83 g·m⁻²·d⁻¹) and black seed (25.71 g·m⁻²·d⁻¹) were recorded in their respective sole cropping systems at 73 and 82 days after planting. P3N1 and P2N2 treatments had the highest RGR of green bean (0.1 g.g-1 d-1) and black seed (0.13 g.g-1.d-1), respectively. The highest NAR of green bean (14.95 g.m-2.d-1) and black seed (48.24 g.m-2.d-1) were recorded at 72 days after planting in P2N2 and 63 days after the planting in sole culture of black seed, respectively. The highest yields of green bean and black seed were obtained in P3N1 and P2N2 treatments, respectively, which did not differ significantly from their sole culture. The land equivalent ratio (LER) for the P1N3 treatment was close to one, while the LER values for the P2N2 and P3N1 treatments were greater than one. This suggests that the P2N2 and P3N1 treatments utilized arable land more effectively and ecologically compared to the P1N3 treatment. The findings can be considered as a reason for improving crop yields due to improving ecological efficiency in the intercropping.

 
The results revealed that the intercropping of black seed with green bean improved the growth of this medicinal plant. In both crops, the Leaf area index, total dry matter, and crop growth rate in sole culture were higher than in other treatments due to their higher plant density; however, the relative growth rate and assimilation rate were also improved in the intercropping treatments. Thus, the intercropping of green bean and black seed would be beneficial from the perspective of ecological management. In general, the replacement of half of the black seed planting density with green bean can be considered beneficial in terms of productivity in crop production.

Carbon footprint (CF) is the total amount of greenhouse gas emissions per unit of farmlands. Since the used inputs have an important role in greenhouse gas emissions, CF as an ecological indicator have been extensively applied for assessing the environmental externalities in agroecosystems. This study was conducted to estimate the CF and carbon efficiency (CE) of saffron production systems in North Khorasan, Razavi Khorasan and South Khorasan provinces. Also, life cycle assessment analysis is calculated for quantifying the impact of saffron farming activity on the environment. Studied indices were global warming potential (GWP), acidification potential )AP) and eutrophication potential in terrestrial (UPT) and aquatic (UPA) sub-categories, N2Odirect, N2Oindirect, N2O emissions affected as volatilization and leaching, carbon inputs (Ci), carbon outputs (Co), CF and CE. The results revealed that the lowest GWP for saffron production systems was related to south Khorasan with 339.43 kg CO2 equiv./ one kg flower yield. The minimum environmental index (EcoX) was recorded for south Khorasan (0.039 EcoX/ one kg flower yield). N2O emissions in South Khorasan, Razavi Khorasan and North Khorasan provinces were estimated with 95974.51, 199674.4 and 344723 kg N2O per one ha, respectively. The largest N2O emissions affected as leaching and volatilization were calculated for North Khorasan province (with 1.21 and 24.23 kg N2O per one ha, respectively). The maximum Ci and Co were related to North Khorasan province with 117986.52 and 15135.56 kg C per one ha, respectively. The largest CF and CE were computed for North Khorasan and south Khorasan provinces with 7.8 and 0.18, respectively. It concluded that adoption on conservation and reduced tillages, N2- fixing pulses, cover crops and green manures in rotations with saffron and increased nitrogen use efficiency as ecological approaches can optimize the system performance while reducing environmental externalities and the carbon footprint of the crop cultivation. So, with relevant agro-environmental policies in saffron production systems along with the adoption of improved agronomical practices increasing flower yield with no cost the environment can be achieved effectively, efficiently and economically.

Response surface methodology (RSM) is defined as statistical technique for optimization of multiple parameters which determine optimum process conditions by combining experimental treatments (5,10,11). In this work, optimization of N and P fertilizers on yield, yield components and seed quality of wheat using RSM were studied.

An experiment was conducted with 13 treatments and two replications at the Research Field of Ferdowsi University of Mashhad during the growing season of 2015-2016. The treatments were allocated based on low and high levels of N fertilizer (0 and 400 kg Urea per ha, respectively) and P fertilizer (0 and 100 kg triple super phosphate per ha, respectively). Biological yield, seed yield, harvest index, growth criteria and yield components (such as tiller No./m2, plant height, spike length, seed No./ spike, seed weight/ spike, seed weight/ plant, spike No./ plant, spike weight/ plant and dry weight of stem per m2) and seed quality characteristics (including N percentage, protein percentage and P percentage) were calculated as dependent variables and changes of these variables were evaluated by a regression model. Lack-of-fit test was used to evaluate the quality of the fitted model. The adequacy of the model was tested by analysis of variance. The quality of the fitted model was judged using the determination coefficient (R2). Finally, the optimum levels of N and P fertilizers were calculated based on three scenarios including economic, ecological and economic-ecological.

The results showed that effect of linear component was significant on harvest index, spike length, yield components (such as seed weight per plant, spike No./plant, spike weight per plant and tiller No./m2), N percent and protein percent of seed. Effect of square component was significant on biological yield, seed yield, tiller No./m2, seed weight per plant and spike weight per plant, N percent, protein percent and P percent of seed. Interaction effect of full quadratic was significant on plant height, spike length and seed No./spike and N percent of seed. Lack of fit test had no significant effect on the studied traits. The full square model for the response variables gave insignificant lack-of-fit indicating that the data of experimental were satisfactorily explained. The highest observed and predicted values of seed yield were recorded for 400 kg Urea per ha+100 kg triple super phosphate per ha and 200 kg Urea per ha+50 kg triple super phosphate per ha with 717.54 and 594.89 kg.ha-1, respectively. The maximum observed and predicted amounts of seed N percent (with 1.72 and 1.62 percent, respectively) and seed protein percentage (with 10.76 and 10.02percent, respectively) were recorded for 400 kg Urea per ha+50 kg triple super phosphate per ha. Both seed yield and N and P percent of seed were considered in economic-ecological scenario, so the estimated levels for N and P fertilizers were 141.41 kg Urea.ha-1 and without P fertilizer.

Increasing rates of N and P fertilizers up to optimum rates increased yield and seed quality of wheat. Nutrient optimization enhances nutrient absorption and yield in the wheat cropping systems may reduce the dependence on external sources of chemical fertilizers that increase the costs of production and can potentially contribute to environmental contamination. The optimization of soil nutrients provides information on the sustainability of cropping systems and potential environmental pollutions. Generally, nutrient optimization is a useful technique widely used in modern agriculture.

In order to study the correlation between yield component and seed yield of sesame and to determine the relationships between shoot length, capsules per plant, seeds per capsule, 1000-seed weight, biological yield and harvest index, in 2013 an experiment was conducted based on RCBD design with ten treatments (including different biological and chemical fertilizers) in experimental field of Ferdowsi university of Mashhad. Results showed that there was a positive and significant correlation between seed yield and plant height, but much of the efficacy of plant height on seed yield was by influencing capsules per plant. Biological and seed yield had a positive and significant correlation (0.81 and 0.87, respectively) with capsules per plant. The highest direct effect of components on seed yield was belonged to “capsules per plant” and the least belonged to “plant height”. Analysis of regression showed that capsules per plant and biological yield had the most effect on seed yield and their partial regression coefficient was 10.7 and 0.134, respectively. The partial regression coefficient for standardized data of these two traits showed the priority of biological yield in comparison with capsules per plant. Yield function that is a function of capsules per plant and biological yield, with the coefficient of determination of 0.96 justified a large part of seed yield. So biological yield and capsules per plant were the most important traits of sesame that can be considered by researchers. Also, after calibration of yield function, it can be used for estimating the production of sesame.