An estimation of the evapotranspiration of typical steppe areas using Landsat images and the METRIC model

Remote sensing excels in estimating regional evapotranspiration (ET). However, most remote sensing energy balance models require researchers to subjectively extract the characteristic parameters of the dry and wet limits of the underlying surfaces. The regional ET accuracy is affected by wrong determined ideal pixels. This study used Landsat images and the METRIC model to evaluate the effects of different dry and wet pixel combinations on the ET in the typical steppe areas. The ET spatiotemporal changes of the different land cover types were discussed. The results show that the surface temperature and leaf area index could determine the dry and wet limits recognition schemes in grassland areas. The water vapor flux data of an eddy covariance system verified that the relative error between the ETd,METRIC and ETd,GES of eight DOYs (day of the year) was 18.8% on average. The ETMETRIC values of the crop growth season and the ETIMS of eight silage maize irrigation monitoring stations were found to have a relative error of 11.1% on average. The spatial distribution of the ET of the different land cover types in the study area was as follows: ETwater > ETarable land > ETforest land > ETunutilized land > ETgrassland > ETurban land.

Cd and Zn Concentrations in Soil and Silage Maize following the Addition of P Fertilizer

Studies of soil Cd and Zn are often performed on sites that are contaminated or have deficient Zn conditions. Soil characteristics and crop management could impact the soil mobility and uptake of Cd and Zn, even when considering unpolluted Cd soils and adequate soil Zn levels. The concentrations of these two metals were assessed in soil and silage maize under five P fertilization treatments at two growth stages under low Cd and sufficient Zn conditions. Pearson correlation coefficients and stepwise linear regressions were calculated to investigate the soil characteristics influencing the bioavailable metal fraction in soil and the metal concentration in silage maize. P treatments did not impact Cd accumulation in maize; however, the Zn uptake was affected by P placement at the leaf development stage. From early development to maturity, the Cd level in maize decreased to 10% of the initial uptake, while the Zn level decreased to 50% of the initial uptake. This reduction in both metals may be attributed to a dilution effect derived from high biomass production. Silage maize could alleviate the initial Cd uptake while diminishing the depressant effect of P fertilizer on Zn concentration. Further research is required to understand the effect of P fertilizer on Cd uptake and its relation to Zn under field conditions at early and mature stages.

Transcriptional and Metabolic Responses of Maize Shoots to Long-Term Potassium Deficiency

AimsPotassium is important for plant growth and crop yield. However, the effects of potassium (K+) deficiency on silage maize biomass yield and how maize shoot feedback mechanisms of K+ deficiency regulating whole plant growth remains largely unknown. Here, the study aims to explore the maize growth and transcriptional and metabolic responses of shoots to long-term potassium deficiency.MethodsThe growth of silage maize and its biomass were analyzed with K+ treatment in field and hydroponic experiments. Furthermore, transcriptional and metabolic profiles of shoots were investigated for their effects on maize development under K+ deficiency condition. ResultsUnder K+ insufficiency condition, the biomass yield of silage maize decreased by 14%-17% in two-year field trials. The transcriptome data showed that there were 390 differently expressed genes overlapping and similarly regulated in the two varieties and they were considered as the fundamental responses to K+ deficiency in maize shoots, with many stress-induced genes involved in transport, primary and secondary metabolism, regulation, and other processes involved in K+ acquisition and homeostasis. Metabolic profiles indicated that most amino acids, phenolic acids, organic acids, and alkaloids were accumulated in shoots under K+ deficiency condition and part of the sugars and sugar alcohols also increased. ConclusionOur results suggested putrescine and putrescine derivatives were specifically accumulated under K+ deficiency condition, which may play a role in feedback regulation of shoot growth. These results confirmed the importance of K+ on silage maize production and provided a deeper insight into the responses to K+ deficiency in maize shoots.

A Bayesian sequential updating approach to predict phenology of silage maize

Crop models are tools used for predicting year to year crop development on field to regional scales. However, robust predictions are hampered by factors such as uncertainty in crop model parameters and in the data used for calibration. Bayesian calibration allows for the estimation of model parameters and quantification of uncertainties, with the consideration of prior information. In this study, we used a Bayesian sequential updating (BSU) approach to progressively incorporate additional data at a yearly time-step to calibrate a phenology model (SPASS) while analysing changes in parameter uncertainty and prediction quality. We used field measurements of silage maize grown between 2010 and 2016 in the regions of Kraichgau and Swabian Alb in southwestern Germany. Parameter uncertainty and model prediction errors were expected to progressively reduce to a final, irreducible value. Parameter uncertainty reduced as expected with the sequential updates. For two sequences using synthetic data, one in which the model was able to accurately simulate the observations, and the other in which a single cultivar was grown under the same environmental conditions, prediction error mostly reduced. However, in the true sequences that followed the actual chronological order of cultivation by the farmers in the two regions, prediction error increased when the calibration data was not representative of the validation data. This could be explained by differences in ripening group and temperature conditions during vegetative growth. With implications for manual and automatic data streams and model updating, our study highlights that the success of Bayesian methods for predictions depends on a comprehensive understanding of inherent structure in the observation data and model limitations.

GHG and NH3 Emissions vs. Energy Efficiency of Maize Production Technology: Evidence from Polish Farms; a Further Study

The paper determines the effect of selected cultivation technologies, including production chain energy inputs (growing, harvest, heap forming) on greenhouse gas emissions (GHGs) to the atmosphere. The data for the study was collected from 13 actually operating family farms ranging in size from 2 to 13 ha, located in the Podlaskie voivodship (Poland). GHG and ammonia (NH3) emissions from natural and mineral fertilisation as well as GHGs from energy carriers in a form of fuels (ON) were estimated. The average GHG emissions from the sources analysed were 1848.030 kg·CO2eq·ha−1 and 29.492 kg·CO2eq·t−1 of the green forage yield. The average NH3 emissions per hectare were 15,261.808 kg NH3 and 248.871 kg NH3·t−1 of yield. The strongest impact on the environment, due to the GHG emissions to the atmosphere, thus contributing to the greenhouse effect, is due nitrogen fertilisation, both mineral and natural. On average, in the technologies under study, 61% of the total GHG emissions came from fertilisation. The GHG emissions were correlated with the energy efficiency, calculated at the previous research stage, of the production technologies applied. There is a negative correlation (r = −0.80) between the features studied, which means that the higher the energy efficiency of the silage maize plantations, the lower the air pollution emissions in a form of the GHGs from the sources under study. It is so important to prevent environmental degradation to continue, conduct in-depth, interdisciplinary research on reducing the energy consumption of crop production technologies and striving to increase energy efficiency.