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Crop growth models can be valuable tools for researchers, academia, extension educators, and policy makers/planners for the evaluation of sustainable and long-term husbandry practices. Determining the optimum sowing window, which can be determined using crop growth models, is imperative under changing climate conditions. Thus, the main objectives herein were to 1) assess the performance of the cropping system model-crop environment resource synthesis-maize model for hybrids and sowing dates in the spring and autumn, and 2) determine the optimum sowing window in 15 districts of Punjab, Pakistan. In the spring experiment, 3 hybrids (P-33M15, M-DK6525, and S-NK8441) were planted in the main plots and then on 5 different sowing dates (January 15th, February 5th, February 25th, March 15th, and April 5th), they were planted in the subplots. In the autumn experiment, 3 hybrids (P-30R50, M-DK6714, and S-NK6621) were planted in the main plots and then on 5 different sowing dates (June 15th, July 5th, July 25th, August 15th, and September 5th), they were planted in the subplots. Model calibration and evaluation results were better in the spring and autumn. Performance of the model was good for the grain yield in the autumn (mean percentage difference (MPD): 7.47% to 8.90%) compared to the spring (MPD: 9.42% to 11.72%). Model evaluation was good for the early sowing dates (January 15th and February 5th) (error range: 6.26% to 9.65%) compared to the delayed dates (February 25th to April 5th) (error range: 9.34 to 14.91%). In the autumn, the model showed better performance for the delayed sowing dates (February 25th and August 15th) (error range: 5.22% to 9.43%) compared to the early dates (June 15th and July 5th) (error range: 8.56% to 11.27%). The model simulated good growth, development, grain yield, and yield components in the spring and autumn and of both 2016 and 2017. For the model application simulation of data over the long-term (1980 to 2017), the optimum sowing window in the spring was January 15th to March 5th and for the autumn it was July 23rd to August 27th for the 15 districts in Punjab, Pakistan. Simulation of the sowing dates for the whole year indicated that the spring was better compared to the autumn for obtaining the maximum grain yield. The results of the model were in line with the recommendations of the agricultural extension department for the sowing window for spring and autumn maize. It is therefore suggested that farmers should complete the sowing of spring and autumn maize within the sowing window to attain a higher yield of maize in arid and semiarid areas of Punjab, Pakistan. [ABSTRACT FROM AUTHOR]

Resources are limited, thus improving resource use efficiency is a key objective for cereal-based cropping systems. This field study was carried out to quantify resource use efficiencies in selected C3 and C4 cereals under split nitrogen (N) application regimes. The study included the following treatments: six cereals (three C3: wheat, oat, and barley; and three C4: maize, millet, and sorghum) and four split N application regimes (NS1 = full amount of N at sowing; NS2 = half N at sowing + half N at first irrigation; NS3 = 1/3 N at sowing + 1/3 N at first irrigation +1/3 N at second irrigation; NS4 = 1/4 N at sowing + 1/4 N at first irrigation + 1/4 N at second irrigation + 1/4 N at third irrigation). Results revealed that C4 cereals out-yielded C3 cereals in terms of biomass production, grain yield, and resource use efficiencies (i.e., radiation use efficiency (RUE) and nitrogen use efficiency (NUE)), while splitting N into three applications proved to be a better strategy for all of the selected winter and summer cereals. The results suggest that C4 cereals should be added into existing cereal-based cropping systems and N application done in three installments to boost productivity and higher resource use efficiency to ensure food security for the burgeoning population. [ABSTRACT FROM AUTHOR]

Increasing resource-use efficiency is of prime importance in sustainable agriculture. A field study was carried out to improve nitrogen-use efficiency (NUE) and radiation-use efficiency (RUE) of three C4 summer cereals, i.e. maize, millet, and sorghum, under an irrigated arid environment. The results showed that among various cultivars of cereals, cultivars Pearl (maize), 18 BY (millet), and Jumbo (sorghum) produced the highest aboveground total dry matters and grain yields. The highest NUE and RUE were obtained by splitting the nitrogen dose 3 times, i.e. at sowing and at first and second irrigation. The NUE for maize, millet, and sorghum varied from 30.97 to 32.97, 21.34 to 23.32, and 17.39 to 20.22 kg kg-1, respectively. RUE ranged from 1.14 to 1.47, 0.85 to 1.08, and 0.91 to 1.13 g MJ-1 for maize, millet, and sorghum crops, respectively. Maximum resource-use efficiency was achieved by 3 splits, while the minimum was obtained in the control group. It is inferred from this study that those varieties of C4 summer cereals may be commercially grown that are more efficient in utilizing the available resources for harnessing greater NUE as well as RUE under an irrigated arid environment. [ABSTRACT FROM AUTHOR]

Pot experiment was carried out at different nitrogen levels in maize and peanut intercropping system to investigate the mechanisms that govern interactions between intercropped species in soil rhizosphere. Three different nitrogen levels 100%, 75% and 50% of normal nitrogen application rate were used in maize monoculture. Two peanut plants were intercropped with single maize plant per pot. Effect of reduced nitrogen application was investigated in soil rhizosphere by measuring soil enzymatic activity, nutrition, soil microbial diversity and composition. Phospholipid fatty acid (PLFA) was carried out to understand about composition of viable soil micro flora and community level physiological profile (CLPP) was applied to work out the microbial diversity. The results revealed that soil nutrition and enzymatic activities were higher in intercropping treatments as compared to mono-cropping with similar level of nitrogen. The results of PLFA analysis showed that intercropping inhibited the fungal population and promoted the bacterial community. The results of AWCD showed that 4 kinds of carbon utilization sources (carboxylic acid, polymer, amines & carbohydrates) increased by the decrease of nitrogen levels in intercropping treatments and other 2 kinds of carbon sources (phenolic acids & amino acids) showed different trend. Cluster analysis (CA) and Principal component analysis (PCA) carried out from the results of PLFA and CLPP indicated distinct separation amongst all treatments of monocropping and intercropping as well as with different level of nitrogen application that reflected a variation in soil microbial activity and composition. However intercropping treatment with 75% nitrogen level performed similar to 100% monocropping treatment of maize. The results revealed that by intercropping of peanut with maize can be used to decrease the dependence on artificial fertilizer which provides a convenient organic farming model for growers across the world. [ABSTRACT FROM AUTHOR]