Non-destructive estimation of maize leaf area, fresh weight, and dry weight using leaf length and leaf width

Leaf area and leaf weight measurements are required to calculate several growth indices, which are leaf area index (LAI), net assimilation rate (NAR), specific leaf area (SLA), specific leaf weight (SLW), and leaf area duration (LAD). We developed three predictive equations to estimate leaf area, leaf fresh and dry weight in maize from leaf length and leaf width measurements. A total of 1,314 leaves from different parts of plants at different plant growth stages, different planting densities and different sowing dates were collected in 2008 at the Agricultural Research Center near Gorgan, Golestan, Iran. To evaluate the equations, some goodness of fit indicators used included mean absolute error, root mean square error and index of agreement. This study found strong relationships between leaf length and leaf width and LA, LFW and LDW (R2 > 0.85). Based on the results LA, LFW and LDW of individual maize leaves can be estimated non-destructively by leaf length and leaf width. These equations allow the research workers to make non-destructive or repeat measurements on the same leaves. The general equation to estimate LA, LFW, and LDW was: Ln (Y) = a + b Ln (L) + c Ln (W)

Impact of planting date and density on growth of maize in Northern Iran

Planting date and density are two major factors affecting maize growth and yield. Although many worldwide studies were done to evaluate the effect of planting date and density on maize, it is still necessary to do more studies to add the knowledge in this area because environmental factors affect planting date and density. During the last four decades, many simulation studies were conducted to evaluate maize growth. A robust simulation model can help researchers to understand, predict and control a system. Despite the importance of modeling studies on maize, no simulation study was done in Golestan-Iran. The purpose of this study was to investigate maize growth and yield response to planting date and density in field and simulation studies in Golestan-Iran. The field studies were conducted at the Agricultural Research Center of Golestan, Iran in 2007 and 2008. In the first experiment, the effects of eight planting dates and three planting densities (0.16, 4.5, and 6.5 plants m-2) were investigated in 2007. The experiment was replicated in 2008 by adding another planting density (8.5 plants m-2). In the second xperiment, maize yield response to a wide range of planting densities (0.16, 2.5, 4.5, 6.5, 8.5, 10.5 and 12.5 plants m-2) was evaluated for two seasons in 2008. In the third study, empirical equations were developed to estimate leaf area and leaf weight using the data from different treatments of the first experiment in 2008. Simulation studies were done using two specific maize models: CERES-Maize and IXIM. To calibrate the models, the data of the first five planting dates in optimum planting densities (6.5 plants m-2) from the first field experiments in 2007 were used. Using stepwise approach and sensitivity analysis, genetic coefficients were calibrated for both models. To evaluate the accuracy of the models, the data from different treatments from the first and second experiments in 2008 were used. The models’ validity was tested using three goodness of fit indicators namely, root mean square error, index of agreement (d) and mean error. Results of the first experiment showed planting date, planting density and the interaction between them had significant effect on yield and yield components. The highest yield was produced in the first planting date (10659 kg ha-1). The best planting density among early and middle planting dates was 6.5 plants m-2 while for late plantings no significant differences were observed in yield among the different planting densities. Results of the second experiment showed that in the first season the highest yield was observed in planting density 6.5 plants m-2 (9470 kg ha-1). However, in the second season, no significant difference in yield was observed among the different planting densities (~4500 kg ha-1). Empirical equations were fitted to the observed data to show the relationship of each of the parameters, yield, total dry matter (TDM), leaf area index (LAI) and harvest index (HI) to planting density. Results of the third study showed that the empirical equations developed to estimate leaf area, fresh weight and dry weight could predict their values with a high degree of accuracy in different situations. The results of simulation study showed that both CERE-Maize and IXIM models predicted days to anthesis, days to physiological maturity, LAI, and kernel weight with high accuracy in different planting dates and densities although the IXIM showed a better performance comparing to CERES-Maize model. IXIM model simulated TDM, kernel number and yield with higher accuracy comparing to CERES-Maize model in the first five planting dates. However, both models could not give accurate predictions of these traits in the last three planting dates. Evaluating response of CERES-Maize and IXIM models to planting density showed that both models could predict different traits accurately in the middle planting densities (4.5-8.5 m-2). However, both models verestimated most traits in high planting densities (10.5-12.5 plants m-2). In conclusion, maize should be planted in early planting dates with planting density 6.5 plants m-2 in Golestan-Iran. However, to obtain high yield in late planting dates, planting density should be decreased to 4.5 plants m-2. In simulation study, both models could not predict yield and yield component with high accuracy in the late planting dates and high planting densities therefore, it seems some modification are needed to be done in the functions that calculate daily crop growth rate, kernel number m-2, and LAI. These modifications may improve the accuracy of the models to estimate these traits

Effect of heat stress during anthesis on the Summer Maize grain formation : Using integrated modelling and multi-criteria GIS-based method

PeerReviewe

Effect of heat stress during anthesis on the Summer Maize grain formation: Using integrated modelling and multi-criteria GIS-based method

peer reviewedDealing with high temperatures during the anthesis stage is an important factor that can affect summer maize. Here, the possibility of heat stress injury (HSI) in the summer maize-grown fields of Golestan province was investigated. A multi-criteria weighted overlay procedure was used to determine the suitability of arable land for maize cultivation. Using the CERES-Maize model and long-term meteorological data, the map of the days with Tmax > 35 °C from three days before to seven days after anthesis was provided. The results showed that the irrigated corn fields in the study area have suitable degrees for corn cultivation and different conditions in the field of HSI experience around pollination. Although most of the fields were located in highly suitable areas, probable HSI (as described by PDT35) affected the final suitability. Also, more reliable sowing dates were introduced. The results revealed that on 18th of June, maize could be sown at all suitable areas except in some arable lands of Kalaleh where the PDT35 was more than 40%. The results showed that HSI should also be considered around the pollination stage to obtain reliable results from land suitability