Effect of Chilling Stress on Synthesis of Antioxidant Enzymes, Osmotic Adjustment Substances and Membrane Lipid Peroxide Levels in Two White Clover Cultivars

Although white clover has been widely studied and applied,less is known about its physiological responses to chilling stress in northern China.The effects of acclimation time of chilling stress in the two white clover cultivars,Rivendel and Haifa,after exposure to 4℃for 0,4,8,12,24 and 48 h were investigated.Seven physiological indexes were measured in shoots of the two cultivars.It was found that Rivendel had a strong ability to maintain the stability of cells,cope with oxidative damage and accumulate osmotic adjustment substances compared with Haifa.In addition,a comprehensive evaluation on the chilling tolerance of the two cultivars based on subordinate function value analysis showed a stronger chilling tolerance of Rivendel than Haifa.

Nutrient Status and Dynamics of Trifolium spp. at Different Growing Stages

The nutrient status and dynamics of three clover （Trifolium spp.） varieties at different growth stages were investigated with the crude protein content as an indicator of nutrient equilibrium. The crude protein, neutral detergent fiber （NDF）, phosphorus （P）, and calcium （Ca） content followed a decreasing trend at the initial growing stage and increased later. NDF and Ca content peaked in May, while crude protein and P content reached the highest in May and the lowest in July. The crude ash content followed an uncertain pattern as plants growing. The ash content of both wild-type red clover （T. pratensis L.） and ＇Sativum＇ decreased at the beginning and then increased. However, the ash content of ＇Revendef white clover （T. repens L.） decreased all through the experimental period. The general trend was observed for all three clover varieties as the ash content was the highest at vegetative growing stage （May）, and the acidic detergent fiber （ADF） content increased with time. The nutrient equilibrium value was ranked as ＇Revendei＇〉wild-type red clover〉＇Sativum＇.

Effect of Different Stocking Rates on Deyeuxia angustifolia Bog Meadow in Sanjiang Plain of China

This paper investigated the effects of cattle grazing on herbage production and its nutrient and soil characteristics over the grazing season. The grazing experiment was conducted on Deyeuxia angustifolia Bog meadow grassland established in 2010 in Sanjiang Plain. Four grazing treatments were light grazing （LG）, moderate grazing （MG）, heavy grazing （HG）, and a non-grazed exclosure （CK） with corresponding stocking rates of 0.6, 1.0, 1.4, and 0 AU·hm2. month-1, selected as three replications. And then found out the optimum carrying capacity after analyzed the nutrition balance between livestock and grassland. Heavy grazing led to a decline in grassland productivity and soil nutrients. The SOM and the TN content in the soil layer of 0-10 cm were much higher than that in the soil layer of 20-30 cm. More attention should be paid to the nutrient changes in the soil layer of 20-30 cm. Currently, studies showed that the reliable carrying capacity in this type of grassland was 1.0 AU·hm-2. month-l. Inclusion of rangeland health monitoring and optimum stocking rate into grassland management model could facilitate the sustainable development of the grassland.

NIRS Prediction of SOM,TN and TP in a Meadow in the Sanjiang Plain,China

The aim of this study was to establish the applicability of near-infrared reflectance spectroscopy(NIRS)as a rapid method for the accurate estimation of nutrient components in agricultural soils.Focusing on the soil of the Sanjiang Plain,NIRS was used to predict soil organic matter(SOM),the total nitrogen(TN)and the total phosphorus(TP).A total of 540 samples were collected from the three different depths(180 samples from each depth:0-10,10-20 and 20-30 cm),from 2015 to 2017,from the Sanjiang Plain in Heilongjiang Province,China.From every depth,120 samples were used to construct the calibration set.Other 60 samples were used to check the efficiency of the model.Combining the first-order differentiation with the partial least square(PLS)method,a prediction model was obtained to measure SOM,TN and TP.The correlation coefficient of SOM from 0 to 10 cm was R2=0.9567,from 10 to 20 cm was R2=0.9416,and from 20 to 30 cm was R2=0.9402.The corresponding ratio(standard deviation[SD]/root mean square error of prediction[RMSEP])was>2.96.R2 of TN with the three depths was 0.9154,0.9028 and 0.9024,respectively,all with SD/RMSEP>2.89.Meanwhile,R2 of TP with the three depths was 0.8974,0.8624 and 0.7804,respectively,all with SD/RMSEP>2.50.These results demonstrated that NIRS based on the first-order differentiation and PLS could efficiently predict SOM,TN and TP from different soil depths.