Examining the Corn Seedling Emergence-Temperature Relationship for Recent Hybrids: Insights from Experimental Studies.

Corn seedling emergence is a critical factor affecting crop yields. Accurately predicting emergence is crucial for precise crop growth and development simulation in process-based crop models. While various experimental studies have investigated the relationship between corn seedling emergence and temperature, there remains a scarcity of studies focused on newer corn hybrids. In the present study, statistical models (linear and quadratic functional relationships) are developed based on the seedling emergence of ten current corn hybrids, considering soil and air temperatures as influencing factors. The data used for model development are obtained from controlled soil plant atmospheric research chamber experiments focused on corn seedling emergence at five different temperatures. Upon evaluating the developed models, the quadratic model relating the air temperature with time to emergence was found more accurate for all corn hybrids (coefficient of determination (R2): 0.97, root mean square error (RMSE): 0.42 day) followed by the quadratic model based on soil temperature (R2: 0.96, RMSE: 1.42 days), linear model based on air (R2: 0.94, RMSE: 0.53 day) and soil temperature (R2: 0.94, RMSE: 0.70 day). A growing degree day (GDD)-based model was also developed for the newer hybrids. When comparing the developed GDD-based model with the existing GDD models (based on old hybrids), it was observed that the GDD required for emergence was 16% higher than the GDD used in the current models. This showed that the existing GDD-based models need to be revisited when adopted for newer hybrids and adapted to corn crop simulation models. The developed seedling emergence model, integrated into a process-based corn crop simulation model, can benefit farmers and researchers in corn crop management. It can aid in optimizing planting schedules, supporting management decisions, and predicting corn crop growth, development, and it yields more accurately.

Climate Stressors on Growth, Yield, and Functional Biochemistry of two Brassica Species, Kale and Mustard.

Due to climate change, the attainment of global food security is facing serious challenges in meeting the growing food demand. Abiotic stresses are the foremost limiting factors for agricultural productivity. However, not much information is available on the effect of multiple abiotic stresses on the morphological and biochemical aspects of kale and mustard. Therefore, an experiment was designed to study the effects of UV-B radiation, CO2 concentration, and high temperature on the growth, yield, and biochemistry of two Brassica species, namely B. oleracea L. var. acephala Winterbor F1 (hybrid kale) and B. juncea var. Green wave O.G. (mustard greens), which were grown under optimal nutrients and soil moisture conditions in soil-plant-atmosphere-research (SPAR) units. Two levels of UV-B radiation (0 and 10 kJ m-2 d-1), two concentrations of CO2 (420 and 720 ppm), and two different temperature treatments (25/17 °C and 35/27 °C) were imposed 12 days after sowing (DAS). Several morphological and biochemical parameters were measured at harvest (40 DAS) in both species. All the traits declined considerably under individual and multi-stress conditions in both species except under elevated CO2 levels, which had a positive impact. Marketable fresh weight decreased by 64% and 58% in kale and mustard plants, respectively, growing under UV-B treatment. A slight increase in the chlorophyll content was observed in both species under the UV-B treatment alone and in combination with high temperature and elevated CO2. Understanding the impacts of high temperature, CO2, and UV-B radiation treatments on leafy vegetables, such as kale and mustard, can help to improve existing varieties to enhance resilience towards environmental stresses while simultaneously improving yield, morphology, and biochemistry in plants.

Developing Functional Relationships between Soil Waterlogging and Corn Shoot and Root Growth and Development.

Short- and long-term waterlogging conditions impact crop growth and development, preventing crops from reaching their true genetic potential. Two experiments were conducted using a pot-culture facility to better understand soil waterlogging impacts on corn growth and development. Two corn hybrids were grown in 2017 and 2018 under ambient sunlight and temperature conditions. Waterlogging durations of 0, 2, 4, 6, 8, 10, 12, and 14 days were imposed at the V2 growth stage. Morphological (growth and development) and pigment estimation data were collected 15 days after treatments were imposed, 23 days after sowing. As waterlogging was imposed, soil oxygen rapidly decreased until reaching zero in about 8-10 days; upon the termination of the treatments, the oxygen levels recovered to the level of the 0 days treatment within 2 days. Whole-plant dry weight declined as the waterlogging duration increased, and after 2 days of waterlogging, a 44% and 27% decline was observed in experiments 1 and 2, respectively. Leaf area and root volume showed an exponential decay similar to the leaf and root dry weight. Leaf number and plant height were the least sensitive measured parameters and decreased linearly in both experiments. Root forks were the most sensitive parameter after 14 days of waterlogging in both experiments, declining by 83% and 80% in experiments 1 and 2, respectively. The data from this study improve our understanding of how corn plants react to increasing durations of waterlogging. In addition, the functional relationships generated from this study could enhance current corn simulation models for field applications.