Growth and mineral nutrient analysis of teak (Tectona grandis) grown on acidic soils in south China

Teak （Tectona grandis L.f.） is widely planted in the world due to its high market demand, economic, ecological and social value. Its plantations have mostly been established and expanded into sites that are acidic to severely acidic in southern China. But, there are no available and specific evidence-based nutrient management techniques. To better recognize and understand the relationship between teak tree growth and nutrient content in the foliage and soil and establish nutrient norms are critical to optimally manage these young plantations. We studied the foliar nutrient and soil chemistry in 19 representative teak plantations aged 5-8 years. Regression analysis indicated that the mean annual increment of teak volume was linearly and positively correlated with foliar N, Ca, Fe and B concentrations, with soil base saturation percentage, available P and Zn concentrations, and negatively correlated with soil Al concentration. Only if the Ca and Mg contents in soil were enhanced, could the increase in soil base saturation percentage benefit teak growth. A revised classification of low-and high-yielding stands was established by using a sorting method of principal components over 6 foliar macro and 8 micro elements in a Diagnosis and Recommendation Integrated System （DRIS）. Specific DRIS norms for teak plantations in acid soils were derived. The nutrient balance of N, P, K Ca, Mg, Zn, B with Fe or A1, Ca with Mg, and Fe with AI provided a key to promote the growth of teak in acid soils. Meanwhile, soil Zn was also found as a primary trace element that affected teak growth in this study.

Near-infrared leaf reflectance modeling of Annona emarginata seedlings for early detection of variations in nitrogen concentration

Nitrogen(N)monitoring is essential in nurseries to ensure the production of high-quality seedlings.Nearinfrared spectroscopy(NIRS)is an instantaneous,nondestructive method to monitor N.Spectral data such as NIRS can also provide the basis for developing a new vegetation spectral index(VSI).Here,we evaluated whether NIRS combined with statistical modeling can accurately detect early variations in N concentration in leaves of young plants of Annona emargiaata and developed a new VSI for this task.Plants were grown in a hydroponics system with 0,2.75,5.5or 11 mM N for 45 days.Then we measured gas exchange,chlorophylla fluorescence,and pigments in leaves;analyzed complete leaf nutrients,and recorded spectral data for leaves at 966 to 1685 nm using NIRS.With a statistical learning approach,the dimensionality of the spectral data was reduced,then models were generated using two classes(N deficiency,N)or four classes(0,2.75,5.5,11 mM N).The best combination of techniques for dimensionality reduction and classification,respectively,was stepwise regression(PROC STEPDISC)and linear discriminant function.It was possible to detect N deficiency in seedlings leaves with 100%precision,and the four N concentrations with93.55%accuracy before photosynthetic damage to the plant occurred.Thereby,NIRS combined with statistical modeling of multidimensional data is effective for detecting N variations in seedlings leaves of A.emarginata.

Growth and nutrient accumulation of Brazil nut trees(Bertholletia excelsa) in agroforestry at different fertilizer levels

The Brazil nut tree（Bertholletia excelsa） is a frequent component of agroforestry systems in the Amazon because of its adaptation to nutrient-poor upland soils and multiple uses.We investigated the aboveground biomass production（kg dry weight）,nutrient uptake and requirements（N,P,Ca,Mg,K） of Brazil nut trees of different sizes grown under agroforestry conditions and fertilized at different levels.Eight of 70 experimental trees with different size were harvested and stem,branches and leaves were separated.Nutrient contents were determined for three trees of varying size.Average tree growth was fast,but variability was high,suggesting considerable potential for the improvement of this economically important species.The trees responded to increased levels of fertilizer and lime with significantly increased foliar nutrient contents and growth,probably because of the improved availability of Mg and Ca for which the species seems to have a relatively high demand.In contrast to Brazil nut trees grown in forest or dense plantations,the agroforestry trees invested a substantial part of their biomass and nutrients in large branches and developed spreading crowns.To improve stem form,reduce competition with associated crops for light and recycle nutrients,regular pruning of lower branches or planting arrangements that favor self-pruning are recommended.These measures would also increase the recycling of Ca and Mg,large quantities of which are contained in the branches.