土壤有机质含量可见-近红外光谱反演过程中校正集的构建策略对模型的预测精度有重要影响。以江汉平原洪湖地区水稻土为研究对象,采用Kennard-Stone(KS)法,Rank-KS(RKS)和Sample set Partitioning based on joint X-Y distance(SPXY)法,构建样本数占总校正集不同比例的子校正集,通过偏最小二乘回归,建立土壤有机质含量的可见—近红外光谱反演模型。结果表明:KS法无法提高模型预测精度,但可以在保证标准差与预测均方根误差比(ratio of performance to standard deviation,RPD)2.0的前提下减少30%的校正样本;基于SPXY法的模型,当子校正集样本比例为总校正集的50%时达到最佳的模型预测精度,RPD为2.557;RKS法能够在保证预测精度的情况下(RPD2.0),最多减少总校正集70%的样本,对应模型RPD为2.212。当校正集与验证集的有机质含量分布相近时,能够以较少的建模样本达到与总校正集相近甚至更高的模型预测精度,提升土壤有机质光谱反演模型的实用性。 相似文献
This investigation aims to classify, describe and evaluate the sustainability of dairy goat production systems (GPS) in South Spain Sierra de Cadiz. The research took place throughout 25 goat farms during the 2001–2002 campaigns, with the method posed by Masera et al. (1999) [Masera, O., Astier, M., S., López-Ridaura. 1999. Sustentabilidad y manejo de recursos naturales. El marco de evaluación MESMIS (Sustainability and natural resource management. The MESMIS evaluation framework). Mundi-Prensa, S.A., Gira, IE-UNAM, México. 109 pp.] and adapted to animal production systems, as the guideline and framework to evaluate sustainability.
The principal component, namely energy input from grazing (eigenvalue 1.329) which comprises the indicators total area per goat (factorial value 0.664) together with net energy obtained from grazing (factorial value 0.903) allowed to differentiate significantly between semi extensive (SES), semi intensive (SIS) and intensive (IS) goat production systems.
Intensification of the GPS tends to be inefficient, especially in terms of net margin per litre of milk produced (p < 0.05). A higher degree of adaptability of IS (64.8%) derives from a higher investment on new production strategies. Likewise, higher self-management capacity of SES (60.9%) fosters standards of productivity (76.0%) and stability (42.9%). The SIS presented the highest equity values (67.8%).
On the whole, sustainability of GPS tends to decrease as the degree of intensification increases: SES = 57.3%; SIS = 55.7% and IS = 53.1%. The reduction of the dependency on external input alongside with the optimization of natural resources management would surely improve the standard of sustainability. 相似文献