• Energy Research

Nitrogen (N) fertilizer is an important yield limiting factor for sunflower production. The correlation between yield components and growth parameters of three sunflower hybrids (Hysun-33, Hysun-38, Pioneer-64A93) were studied with five N rates (0, 60, 120, 180, 240 kg ha(-1)) at three different experimental sites during the two consecutive growing seasons 2008 and 2009. The results revealed that total dry matter (TDM) production and grain yield were positively and linearly associated with leaf area index (LAI), leaf area duration (LAD), and crop growth rate (CGR) at all three sites of the experiments. The significant association of yield with growth components indicated that the humid climate was most suitable for sunflower production. Furthermore, the association of these components can be successfully used to predict the grain yield under diverse climatic conditions. The application of N at increased rate of 180 kg ha(-1) resulted in maximum yield as compared to standard rate (120 kg ha(-1)) at all the experimental sites. In this way, N application rate was significantly correlated with growth and development of sunflower under a variety of climatic conditions. Keeping in view such relationship, the N dose can be optimized for sunflower crop in a particular region to maximize the productivity. Multilocation trails help to predict the input rates precisely while taking climatic variations into account also. In the long run, results of this study provides basis for sustainable sunflower production under changing climate.

The original version of this paper was published with error. Corresponding author requested to make a necessary correction in the spelling for the last author. The correct name is “Travis Esau” instead of “Travis Easu”.

The combination of nitrogen and plant population expresses the spatial distribution of crop plants. The spatial distribution influences canopy structure and development, radiation capture, accumulated intercepted radiation (Sa), radiation use efficiency (RUE), and subsequently dry matter production. We hypothesized that the sunflower crop at higher plant populations and nitrogen (N) rates would achieve early canopy cover, capture more radiant energy, utilize radiation energy more efficiently, and ultimately increase economic yield. To investigate the above hypothesis, we examined the influences of leaf area index (LAI) at different plant populations (83,333, 66,666, and 55,555 plants ha-1) and N rates (90, 120, and 150 kg ha-1) on radiation interception (Fi), photosynthetically active radiation (PAR) accumulation (Sa), total dry matter (TDM), achene yield (AY), and RUE of sunflower. The experimental work was conducted during 2012 and 2013 on sandy loam soil in Punjab, Pakistan. The sunflower crop captured more than 96% of incident radiant energy (mean of all treatments), 98% with a higher plant population (83,333 plants ha-1), and 97% with higher N application (150 kg ha-1) at the fifth harvest (60 days after sowing) during both study years. The plant population of 83,333 plants ha-1 with 150 kg N ha-1 ominously promoted crop, RUE, and finally productivity of sunflower (AY and TDM). Sunflower canopy (LAI) showed a very close and strong association with Fi (R 2 = 0.99 in both years), PAR (R 2 = 0.74 and 0.79 in 2012 and 2013, respectively), TDM (R 2 = 0.97 in 2012 and 0.91 in 2013), AY (R 2 = 0.95 in both years), RUE for TDM (RUETDM) (R 2 = 0.63 and 0.71 in 2012 and 2013, respectively), and RUE for AY (RUEAY) (R 2 = 0.88 and 0.87 in 2012 and 2013, respectively). Similarly, AY (R 2 = 0.73 in 2012 and 0.79 in 2013) and TDM (R 2 = 0.75 in 2012 and 0.84 in 2013) indicated significant dependence on PAR accumulation of sunflower. High temperature during the flowering stage in 2013 shortened the crop maturity duration, which reduced the LAI, leaf area duration (LAD), crop growth rate (CGR), TDM, AY, Fi, Sa, and RUE of sunflower. Our results clearly revealed that RUE was enhanced as plant population and N application rates were increased and biomass assimilation in semi-arid environments varied with radiation capture capacity of sunflower.

Biochar produced from transforming bioresource waste can benefit sustainable agriculture and support circular bioeconomy. The objective of this study was to evaluate the effect of the application of biochar, produced from wheat straws, and a nitrification inhibitor, sourced from neem (Azadirachta indica), in combinition with the recommended synthetic fertilizer on soil properties, maize (Zea mays L.) plant growth characteristics, and maize grain yield and quality paramters. The nitrification inhibitor was used with the concentrations of 5 and 10 mL pot−1 (N1 and N2, respectively) with four levels of biochar (B0 = 0 g, B1 = 35 g, B2 = 70 g, B3 = 105 g, B4 = 140 g pot−1), one recommended nitrogen, phosphorous, and potassium syntactic fertilizer (250, 125, and 100 kg ha−1, respectively) treatment, and one control treatment. The results showed that the nitrification inhibitor enhanced crop growth while the application of biochar significantly improved soil fertility. The application of biochar significantly enhanced soil organic matter and soil nitrogen as compared with nitrogen–phosphorus–potassium treatment. The highest root length (65.43 cm) and root weight (50.25 g) were observed in the maize plants treated with B4 and N2 combinedly. The grain yield, total biomass production, protein content from biochar’s B4, and nitrogen–phosphorus–potassium treatments were not significantly different from each other. The application of 140 g biochar pot−1 (B4) with nitrification inhibitor (10 mL pot−1) resulted in higher crop yield and the highest protein contents in maize grains as compared to the control treatments. Therefore, the potential of biochar application in combination with nitrification inhibitor may be used as the best nutrient management practice after verifying these findings at a large-scale field study. Based on the experimental findings, the applied potential of the study treatments, and results of economic analysis, it can be said that biochar has an important role to play in the circular bioeconomy.

Growth, development, and economic yield of agricultural crops rely on moisture, temperature, light, and carbon dioxide concentration. However, the amount of these parameters is varying with time due to climate change. Climate change is factual and ongoing so, first principle of agronomy should be to identify climate change potential impacts and adaptation measures to manage the susceptibilities of agricultural sector. Crop models have ability to predict the crop's yield under changing climatic conditions. We used OILCROP-SUN model to simulate the influence of elevated temperature and CO2 on crop growth duration, maximum leaf area index (LAI), total dry matter (TDM), and achene yield of sunflower under semi-arid conditions of Pakistan (Faisalabad, Punjab). The model was calibrated and validated with the experimental data of 2012 and 2013, respectively. The simulation results showed that phenological events of sunflower were not changed at higher concentration of CO2 (430 and 550 ppm). However LAI, achene yield, and TDM increased by 0.24, 2.41, and 4.67% at 430 ppm and by 0.48, 3.09, and 9.87% at 550 ppm, respectively. Increased temperature (1 and 2 °C) reduced the sunflower duration to remain green that finally led to less LAI, achene yield, and TDM as compared to present conditions. However, the drastic effects of increased temperature on sunflower were reduced to some extent at 550 ppm CO2 concentration. Evaluation of different adaptation options revealed that 21 days earlier (as compared to current sowing date) planting of sunflower crop with increased plant population (83,333 plants ha-1) could reduce the yield losses due to climate change. Flowering is the most critical stage of sunflower to water scarcity. We recommended skipping second irrigation or 10% (337.5 mm) less irrigation water application to conserve moisture under possible water scarce conditions of 2025 and 2050.

Land use/land cover (LULC) change has serious implications for environment as LULC is directly related to land degradation over a period of time and results in many changes in the environment. Monitoring the locations and distributions of LULC changes is important for establishing links between regulatory actions, policy decisions, and subsequent LULC activities. The normalized difference vegetation index (NDVI) has the potential ability to identify the vegetation features of various eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. Similarly, the normalized difference built-up index (NDBI) may be used for quoting built-up land. This study aims to detect the pattern of LULC, NDBI, and NDVI change in Lodhran district, Pakistan, from the Landsat images taken over 40 years, considering four major LULC types as follows: water bodies, built-up area, bare soil, and vegetation. Supervised classification was applied to detect LULC changes observed over Lodhran district as it explains the maximum likelihood algorithm in software ERDAS imagine 15. Most farmers (46.6%) perceived that there have been extreme changes of onset of temperature, planting season, and less precipitation amount in Lodhran district in the last few years. In 2017, building areas increased (4.3%) as compared to 1977. NDVI values for Lodhran district were highest in 1977 (up to + 0.86) and lowest in 1997 (up to - 0.33). Overall accuracy for classification was 86% for 1977, 85% for 1987, 86% for 1997, 88% for 2007, and 95% for 2017. LULC change with soil types, temperature, and NDVI, NDBI, and slope classes was common in the study area, and the conversions of bare soil into vegetation area and built-up area were major changes in the past 40 years in Lodhran district. Lodhran district faces rising temperatures, less irrigation water, and low rainfall. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support from government.

Agroforestry is a sustainable land use system with a promising potential to sequester atmospheric carbon into soil. This system of land use distinguishes itself from the other systems, such as sole crop cultivation and afforestation on croplands only through its potential to sequester higher amounts of carbon (in the above- and belowground tree biomass) than the aforementioned two systems. According to Kyoto protocol, agroforestry is recognized as an afforestation activity that, in addition to sequestering carbon dioxide (CO2) to soil, conserves biodiversity, protects cropland, works as a windbreak, and provides food and feed to human and livestock, pollen for honey bees, wood for fuel, and timber for shelters construction. Agroforestry is more attractive as a land use practice for the farming community worldwide instead of cropland and forestland management systems. This practice is a win-win situation for the farming community and for the environmental sustainability. This review presents agroforestry potential to counter the increasing concentration of atmospheric CO2 by sequestering it in above- and belowground biomass. The role of agroforestry in climate change mitigation worldwide might be recognized to its full potential by overcoming various financial, technical, and institutional barriers. Carbon sequestration in soil by various agricultural systems can be simulated by various models but literature lacks reports on validated models to quantify the agroforestry potential for carbon sequestration.

Radiation use efficiency (RUE) is considered critical for calculation of crop yield. The crop productivity can be improved by increasing the interception of solar radiation and maintaining higher RUE for plants. Irrigation water and nitrogen (N) supply are the main limiting factors for RUE in maize (Zea mays L.) across the semi-arid environments. Field experiments were conducted during two consecutive growing seasons (2009-2010) to optimize RUE in relation to N application timings and rates with varying irrigation water management practices. In experiment 1, three N application timings were made, while in experiment 2, three possible water management practices were used. In both experiments, five N rates (100, 150, 200, 250, and 300 kg N ha-1) were applied to evaluate the effects of irrigation water and N on cumulative photosynthetic active radiation (PARi), dry matter RUE (RUEDM), and grain yield RUE (RUEGY). The results demonstrated that cumulative PARi and RUEs were not constant during the plant growth under varying the nutrients. The water and N significantly influenced cumulative PARi and RUEs during the both growing seasons. In experiment 1, the maximum cumulative PARi was observed by application of 250 kg N ha-1 in three splits (1/3 N at V2, 1/3 N at V16, and 1/3 N at R1 stage), and the highest RUEDM was achieved by the application of 300 kg N ha-1. However, the highest RUEGY was observed by application of 250 kg N ha-1. In experiment 2, the maximum cumulative PARi was attained at normal irrigation regime with 250 kg N ha-1, while the highest RUEDM and RUEGY were recorded at normal irrigation regime with the application of 300 kg N ha-1. The regression analysis showed significant and positive correlation of RUEGY with grain yield. Therefore, optimum water and N doses are important for attaining higher RUE, which may enhance maize grain yield semi-arid environment; this may be considered in formulating good agricultural practices for the environmental conditions resembling to those of this study.