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Due to a boom in the dairy industry in Northeast China, the hay industry has been developing rapidly. Thus, it is very important to evaluate the hay quality with a rapid and accurate method. In this research, a novel technique that combines near infrared spectroscopy (NIRs) with three different statistical analyses (MLR, PCR and PLS) was used to predict the chemical quality of sheepgrass (Leymus chinensis) in Heilongjiang Province, China including the concentrations of crude protein (CP), acid detergent fiber (ADF), and neutral detergent fiber (NDF). Firstly, the linear partial least squares regression (PLS) was performed on the spectra and the predictions were compared to those with laboratory-based recorded spectra. Then, the MLR evaluation method for CP has a potential to be used for industry requirements, as it needs less sophisticated and cheaper instrumentation using only a few wavelengths. Results show that in terms of CP, ADF and NDF, (i) the prediction accuracy in terms of CP, ADF and NDF using PLS was obviously improved compared to the PCR algorithm, and comparable or even better than results generated using the MLR algorithm; (ii) the predictions were worse compared to laboratory-based spectra with the MLR algorithmin, and poor predictions were obtained (R2, 0.62, RPD, 0.9) using MLR in terms of NDF; (iii) a satisfactory accuracy with R2 and RPD by PLS method of 0.91, 3.2 for CP, 0.89, 3.1 for ADF and 0.88, 3.0 for NDF, respectively, was obtained. Our results highlight the use of the combined NIRs-PLS method could be applied as a valuable technique to rapidly and accurately evaluate the quality of sheepgrass hay.

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The reduced-tillage (Rt) has been proposed as a strategy to improve soil organic carbon and soil total nitrogen pools. However, little is known of the role of the reduced-tillage compared with the organic (Org) and conventional (Con) management in the Songnen Plain of China. We studied the 4 yr effect of three management strategies (Con, Org and Rt management) on labile soil organic carbon (C) and nitrogen (N) pools, including variation in mineralizable carbon and nitrogen, microbial biomass carbon and nitrogen, dissolved organic carbon and nitrogen in the rotation of alfalfa-corn established in 2009. Soil characteristics including soil organic carbon (SOC), soil total nitrogen (STN), dissolved organic carbon (DOC), dissolved organic nitrogen (DON), microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) were quantified in samples collected during the 9 yr rotation of 5yr-alfalfa (Medicago sativa L.) followed by 4 yr corn (Zea mays L.). The mineralizable C was increased in the four years, and although not statistically significant, 12% higher in the fourth year under reduced-tillage than conventional management (268 kg ha−1). Soil organic C was increased by 30% under reduced-tillage compared to conventional management (15.5 Mg ha−1). Three management strategies showed similar labile N pools in the Con and Org management, but differed in the Rt management. Org management showed significantly lesser mineralizable and inorganic N compared to other strategies, but soil microbial community and comparable crop yield across management strategy in year 4, indicating more efficient N use for organic than other management strategy. In our conditions, reduced-tillage for corn cropping after five years of alfalfa grassland can accumulate labile C and N and improve N utilization to for crop yields in the forage-based rotations. These findings suggest an optimal strategy for using Rt management to enhance soil properties and crop yield in plantation soils and provide a new perspective for understanding the potential role of Rt management in plantation soil.

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