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Experiments were conducted in the wet seasons of 2018 and 2019 to study the effect of cultivar on the growth and yield of ginger (Zingiber officinale Roscoe) in Kafanchan in Jema'a Local Government Area of Kaduna State, Nigeria. The treatments consisted of three cultivars of ginger (China, UG1 and UG2) arranged in a randomized complete block design (RCBD) and replicated three times. The parameters measured included number of shoots per plant, number of leaves per shoot, plant height, ginger fresh weight and ginger dry weight. Cultivar significantly affected the ginger fresh and dry weights, moisture content and plant height but did not have significant effects on the number of shoots per plant and number of leaves per shoot. The mean fresh and dry weights were 54.3 and 14.1 t/ha, 40.2 and 12.8 t/ha, and 27.0 and 8.4 t/ha for the China, UG1 and UG2 cultivars respectively. The China cultivar produced heavier fresh rhizomes than the UG1 and UG2 in both years of the study and the mean but this weight advantage did not reflect in the dry weight of the ginger especially when compared with UG1. A further study is recommended to determine the pungency, aroma and oleoresin contents as well as market acceptability of the three ginger cultivars to enable a good recommendation to ginger farmers in the study area. [ABSTRACT FROM AUTHOR]

The white mulberry is a native fruit to China. The white mulberry as a fruit with high water content and sensitive texture, is a perishable fruit with high-level waste. To reduce the losses of the white mulberry, it used to be processed traditional dried fruit and mulberry molasses. The purpose of this study was to determine chemical and physical properties of white mulberry molasess made up of different cultivars, neutralizers and concentration methods. Two examples of cultivars were Bokhara and Khardar mulberry (local cultivars), two neutralizing compounds were white soil (traditionally special soil can be used as neutralization) and calcium carbonate, the concentration conditions were concentration under vacuum conditions and concentration under atmospheric pressure to achieve the desired final concentration (70°Brix). The experimental design was factorial in the frame of completely randomized design which was performed in three replications. The results showed that the neutralization and concentration methods had significant effects on acidity, pH and color (L*, a*, b* indexes). The selected sample for preparing mulberry molasses was the concentration of Bokhara mulberry in vacuum condition with calcium carbonate as neutralizing agent. [ABSTRACT FROM AUTHOR]

There has been increasing concern in recent years regarding lead (Pb) transfer in the soil-plant system. In this study the transfer of Pb (exogenous salts) was investigated from a wide range of Chinese soils to corn grain (Zhengdan 958). Prediction models were developed with combination of the Pb bioconcentration factor (BCF) of Zhengdan 958, and soil pH, organic matter (OM) content, and cation exchange capacity (CEC) through multiple stepwise regressions. Moreover, these prediction models from Zhengdan 958 were applied to other non-model corn species through cross-species extrapolation approach. The results showed that the soil pH and OM were the major factors that controlled Pb transfer from soil to corn grain. The lower pH and OM could improve the bioaccumulation of Pb in corn grain. No significant differences were found between two prediction models derived from the different exogenous Pb contents. When the prediction models were applied to other non-model corn species, the ratio ranges between the predicted BCF values and the measured BCF values were within an interval of 2-fold and close to the solid line of 1∶1 relationship. Moreover, the prediction model i.e. Log[BCF] = −0.098 pH-0.150 log[OM] −1.894 at the treatment of high Pb can effectively reduce the measured BCF intra-species variability for all non-model corn species. These suggested that this prediction model derived from the high Pb content was more adaptable to be applied to other non-model corn species to predict the Pb bioconcentration in corn grain and assess the ecological risk of Pb in different agricultural soils. [ABSTRACT FROM AUTHOR]

[Display omitted] • Studied effect of soil thickness on green roof thermal performance in winter. • Conducted field experiments in three green roof plots in subtropical south China. • Monitored roof outer surface temperature and microclimatic parameters. • Applied Random Effects Model and regression to analyze the nested data. • Found 20-cm soil thickness with medium moisture content optimal for passive warming. Soil can absorb and retain solar heat to influence critically the thermal-energy performance of green roofs. Its modification to optimize warming effect in winter has received inadequate attention. Adopting the modeling approach, this study investigated key soil parameters to improve warming of the roof outer surface temperature (ROST) in winter using three experimental green-roof plots in subtropical south China. We assessed the effect of soil thickness and soil moisture as controllable predictor variables on ROST, and environmental factors of outdoor air temperature, relative humidity, horizontal solar radiation and wind speed as uncontrollable predictor variables. Adjusting the controllable variables, 14,784 sets of valid empirical data were collected to develop a Random Effects Model of ROST. Regression analysis indicated good fit between predicted and measured ROST and accurate model prediction, with an average absolute error of 1.12 °C and standard deviation of 1.53 °C. At 19.7% moisture content suitable for plant growth, the soil-thickness effect on ROST was evaluated. The model found average ROST of a 10-cm soil layer cooler than the bare roof to indicate poor warming performance, whereas a 20-cm layer warmed ROST notably. The findings can inform green-roof design by adjusting soil thickness and moisture to optimize winter thermal-energy performance. [ABSTRACT FROM AUTHOR]