The concentrations of N, P, K, Ca and Mg in different organs of Phyllostachys pubescens with in sequence of age and the amount of soil nutrients were analyzed. The results showed that the content of four nutrition ele...The concentrations of N, P, K, Ca and Mg in different organs of Phyllostachys pubescens with in sequence of age and the amount of soil nutrients were analyzed. The results showed that the content of four nutrition elements(N, P, Ca, Mg) in different organs were in the order as: leaf > branch > stem; while for K: leaf >stem >branch. The abundance of different elements in leaf, in branch and in stem respectively ranged as: N>K>Mg>P>Ca, K>N>Mg>P>Ca and K>N>Mg>Ca>P. The nutrition elements in various organs of P. pubescens were interrelated one another at some extent, significant( P <0 05) or great significant correlation ( P <0 01)existed between eleven pairs nutrient elements contents out of total thirty pairs of nutrient elements. The productivity of the woods in on_year was much higher than that in off_year, while the content of N, P and K in leaf was much higher in off_year. The nutrition in bamboo were generally correlated to nutrients of soils, eg, nitrogen content in leaf had a significant relationship with organic matter, total nitrogen, available nitrogen and available potassium in soil, phosphorus content in leaf had a strong relationship with organic matter and available nitrogen in soil, however, only good relationships in stem were found between nitrogen content and organic matter, available potassium in soil. Potassium content in branch were negatively correlated to organic matter, total nitrogen and available nitrogen in soil.展开更多
The number of bamboo stem at different ages and the mean diameter at breast height(DBH)which are the important target in evaluating productivity of bamboo stand were investigated in 50 plots established in Jianou city...The number of bamboo stem at different ages and the mean diameter at breast height(DBH)which are the important target in evaluating productivity of bamboo stand were investigated in 50 plots established in Jianou city, Fujian Province in this paper, and the authors selected the method of artificial neural network to biuld the simulative and predictive model of mean DBH for bamboo stands. Artificial neural network is a good method in handling the overall nonlinear mapping problems between input variables and output ones, which has a wide application in many research fields, such as system simulating, automation controlling, paralleled data processing and so on. In this paper, the input variables were the number of different age and the total number of stand, the output variable was mean DBH for bamboo stands, the number of neurons of hide level( M ) was M=2L+1=3 according to the last document ( L is the number of factors of input level), and the network activity function is Sigmiod function as follows: F(x)=1/(1+e -x ). Using the built BP network, the samples were trained until E j(W 1 lm ,W 2 mn )=Nn=1(O nj -Y nj ) 2 =min, where O nj and Y nj are output values of network and really values of DBH for bamboo stands respectively, N is the number of trained samples, and E j is sum of square deviation of BP network. If E j didn’t converge, the weights and thresholds of BP network were adjusted as follow: ΔW ij (n+1)=βλ jX i+αΔW ij (n) and Δη j(n+1)=-βλ j+αΔη j(n) .. The results showed that the mean simulative accuracy and the mean predictive accuracy of mean D.B.H BP model for bamboo stands were all satisfactory, which were 89 95% and 89 26% respectively. Therefore, it provided a scientific basis for evaluating the productivity and realizing high yield for bamboo stands.展开更多
文摘The concentrations of N, P, K, Ca and Mg in different organs of Phyllostachys pubescens with in sequence of age and the amount of soil nutrients were analyzed. The results showed that the content of four nutrition elements(N, P, Ca, Mg) in different organs were in the order as: leaf > branch > stem; while for K: leaf >stem >branch. The abundance of different elements in leaf, in branch and in stem respectively ranged as: N>K>Mg>P>Ca, K>N>Mg>P>Ca and K>N>Mg>Ca>P. The nutrition elements in various organs of P. pubescens were interrelated one another at some extent, significant( P <0 05) or great significant correlation ( P <0 01)existed between eleven pairs nutrient elements contents out of total thirty pairs of nutrient elements. The productivity of the woods in on_year was much higher than that in off_year, while the content of N, P and K in leaf was much higher in off_year. The nutrition in bamboo were generally correlated to nutrients of soils, eg, nitrogen content in leaf had a significant relationship with organic matter, total nitrogen, available nitrogen and available potassium in soil, phosphorus content in leaf had a strong relationship with organic matter and available nitrogen in soil, however, only good relationships in stem were found between nitrogen content and organic matter, available potassium in soil. Potassium content in branch were negatively correlated to organic matter, total nitrogen and available nitrogen in soil.
文摘The number of bamboo stem at different ages and the mean diameter at breast height(DBH)which are the important target in evaluating productivity of bamboo stand were investigated in 50 plots established in Jianou city, Fujian Province in this paper, and the authors selected the method of artificial neural network to biuld the simulative and predictive model of mean DBH for bamboo stands. Artificial neural network is a good method in handling the overall nonlinear mapping problems between input variables and output ones, which has a wide application in many research fields, such as system simulating, automation controlling, paralleled data processing and so on. In this paper, the input variables were the number of different age and the total number of stand, the output variable was mean DBH for bamboo stands, the number of neurons of hide level( M ) was M=2L+1=3 according to the last document ( L is the number of factors of input level), and the network activity function is Sigmiod function as follows: F(x)=1/(1+e -x ). Using the built BP network, the samples were trained until E j(W 1 lm ,W 2 mn )=Nn=1(O nj -Y nj ) 2 =min, where O nj and Y nj are output values of network and really values of DBH for bamboo stands respectively, N is the number of trained samples, and E j is sum of square deviation of BP network. If E j didn’t converge, the weights and thresholds of BP network were adjusted as follow: ΔW ij (n+1)=βλ jX i+αΔW ij (n) and Δη j(n+1)=-βλ j+αΔη j(n) .. The results showed that the mean simulative accuracy and the mean predictive accuracy of mean D.B.H BP model for bamboo stands were all satisfactory, which were 89 95% and 89 26% respectively. Therefore, it provided a scientific basis for evaluating the productivity and realizing high yield for bamboo stands.
