NGHIÊN CỨU ĐẶC ĐIỂM SINH TRƯỞNG CỦA RỪNG KEO LAI TRỒNG (Acacia mangium X Acacia auriculiformis)THUỘC TẬP ĐOÀN NGUYÊN LIỆU GIẤY TÂN MAI TẠI HUYỆN EA SÚP TỈNH ĐẮK LẮK

BỘ GIÁO DỤC VÀ ĐÀO TẠO ĐẠI HỌC NÔNG LÂM TP HỒ CHÍ MINH ******************** NGUYỄN TRUNG MỸ NGHIÊN CỨU ĐẶC ĐIỂM SINH TRƯỞNG CỦA RỪNG KEO LAI TRỒNG (Acacia mangium X Acacia auriculiformis)THUỘC TẬP ĐOÀN NGUYÊN LIỆU GIẤY TÂN MAI TẠI HUYỆN EA SÚP TỈNH ĐẮK LẮK LUẬN VĂN TỐT NGHIỆP ĐẠI HỌC CHUYÊN NGÀNH QUẢN LÝ TÀI NGUYÊN RỪNG Thành phố Hồ Chí Minh Tháng 07/2013 BỘ GIÁO DỤC VÀ ĐÀO TẠO ĐẠI HỌC NÔNG LÂM TP HỒ CHÍ MINH ******************** NGUYỄN TRUNG MỸ NGHIÊN CỨU ĐẶC ĐIỂM SINH TRƯỞNG CỦA RỪNG KEO LAI TRỒNG (Acacia mangium X Acacia auriculiformis)THUỘC TẬP ĐOÀN NGUYÊN LIỆU GIẤY TÂN MAI TẠI HUYỆN EA SÚP TỈNH ĐẮK LẮK Ngành: Lâm Nghiệp LUẬN VĂN TỐT NGHIỆP ĐẠI HỌC Ngƣời hƣớng dẫn : ThS MẠC VĂN CHĂM Thành phố Hồ Chí Minh Tháng 07/ 2013 LỜI CẢM ƠN Để hoàn thành báo cáo tốt nghiệp này, cố gắng phấn đấu thân có giúp đỡ nhiệt tình từ phía Thầy cơ, gia đình, bạn bè phận nghiệp vụ Tập Đoàn Nguyên Liệu Giấy Tân Mai Tại Huyện Ea Súp Tỉnh Đắk Lắk Trước hết, em xin cảm ơn Ban Giám Hiệu, thầy cô Khoa Lâm Nghiệp trường Đại Học Nơng Lâm TP Hồ Chí Minh trực tiếp giảng dạy, truyền đạt cho em kiến thức quý báu, học bổ ích để làm hành trang bước vào đời ngày hôm Đặc biệt, em xin chân thành cảm ơn đến Th.S Mạc Văn Chăm nhiệt tình hướng dẫn cho em, giúp em hoàn thành tốt luận văn Em vô cảm ơn chú, bác, anh, chị cơng tác Tập Đồn Ngun Liệu Giấy Tân Mai Huyện Ea Súp Tỉnh Đắk Lắk giúp đỡ nhiệt tình suốt thời gian thực tập, tạo điều kiện thuận lợi để em thu thập số liệu xác để đảm bảo yêu cầu luận văn đề Con xin chân thành cảm ơn Ba Mẹ dạy dỗ, chăm sóc, ni khơn lớn ngày hơm Cảm ơn người gia đình hết lòng ủng hộ vật chất lẫn tinh thần để an tâm học tập hoàn thành luận văn Và cuối cùng, xin chân thành cảm ơn tập thể lớp DH09QR giúp đỡ, động viên suốt trình học tập Xin chân thành cảm ơn! TP Hồ Chí Minh, ngày 30/06/2013 Sinh viên thực NGUYỄN TRUNG MỸ i TÓM TẮT Đề tài: “nghiên cứu đặc điểm sinh trƣởng rừng keo lai (Acacia mangium X Acacia auriculiformis) trồng thuộc công ty cổ phần tập đoàn Tân Mai huyện Easup tỉnh Đắklắk” đƣợc tiến hành huyện Easup tỉnh Đắklắk, thời gian nghiên cứu từ ngày 01/03/2013 đến 15/07/2013 Kết thu đƣợc đề tài nhƣ sau: - Phân bố số theo tiêu sinh trƣởng: Phân bố phần trăm số theo cấp đƣờng kính rừng keo lai trồng khu vực nghiên cứu có dạng đỉnh, lệch trái rừng trồng tuổi lệch phải rừng trồng tuổi Phân bố phần trăm số theo cấp chiều cao rừng keo lai trồng có dạng đỉnh, lệch phải tất lâm phần Về tiêu đƣờng kính tán, phân bố phần trăm số có dạng đỉnh, lệch trái hầu hết lâm phần lệch phải lâm phần tuổi Kết cho thấy, chênh lệch tiêu sinh trƣởng tuổi lớn - Qua nghiên cứu cho thấy quy luật sinh trƣởng rừng keo lai trồng đƣợc thể qua phƣơng trình tƣơng quan với hệ số tƣơng quan chặt, cụ thể là: + Quy luật tƣơng quan đƣờng kính tuổi (D1,3/A): D1.3 = -4,28469 + 5,57404*sqrt(A) với r = 0,99 + Quy luật tƣơng quan chiều cao tuổi (Hvn/A): Hvn = -7,12539 + 9,67833*sqrt(A) với r = 0,99 + Quy luật tƣơng quan đƣờng kính chiều cao (D1,3/Hvn): Hvn = exp(0,676388 + 0,948885*ln(D1.3)) với r = 0,99 - Thể tích keo lai trồng tăng chậm từ tuổi đến tuổi tăng lên nhanh tuổi có phần chậm lại tuổi Quy luật đƣợc mơ phƣơng trình tƣơng quan: V = (-0,152058 + 0,157013*sqrt(A))^2 - Đặc điểm tăng trƣởng rừng keo lai trồng khu vực nghiên cứu: ii + Lƣợng tăng trƣởng đƣờng kính keo lai trồng có xu hƣớng tăng nhanh từ tuổi đến tuổi 3, sau giảm xuống tuổi 5, đặc biệt tuổi lƣợng tăng trƣởng đƣờng kính thấp (0,8 cm) + Lƣợng tăng trƣởng chiều cao (ihvn)của keo lai trồng có xu hƣớng tăng nhanh từ tuổi đến tuổi 3, sau giảm xuống tuổi 5, đặc biệt tuổi có lƣợng tăng trƣởng thấp (1,3 m) Nhìn chung, lƣợng tăng trƣởng chiều cao keo lai khu vực cao So với đƣờng kính chiều cao tăng trƣởng nhanh nhiều iii ABSTRACT The Thesis: “Research growth characteristicsofplantation Acacia mangiumXAcaciaauriculiformisat Easupdistrict, Daklak province which was managed by incorporated company Tan Mai Group, study period from 01/03/2013 to 15/07/2013 The result of the thesis are as follow: Distribution of trees by the growth indicators: The percentage of trees distribution by diameter class of acacia plantations in the study area as a top, misses at and years olds plantation and misses right at and years olds one The percentage of trees distribution by height of acacia plantations here as a peak On the canopy diameter, the percentage of one have a peak shape, most misses in the forests and not just differences in the forest age Results showed differences in each growth indicators in each age is huge The result shows that growing rule of Acacia plantations here are reflected in the Correlation equation with correlation coefficients very close, namely: Correlation between diameter anh age (D1, / A): D1.3 = -4,28469 + 5,57404*sqrt(A) with r = 0,99 Correlation between height and age (Hvn / A): Hvn = -7,12539 + 9,67833*sqrt(A) with r = 0,99 Correlation between diameter anh height (D1, /Hvn): Hvn = exp(0,676388 + 0,948885*ln(D1.3)) with r = 0,99 The volume of growing acacia trees here grow slowly from age to age and increases rapidly until the age of and has slowed somewhat at age This rule is modeled by the correlation equation: V = (-0,152058 + 0,157013 * sqrt (A)) ^ Characteristics of growth of Acacia forest planted in the study area: The amount of diameter growth of planted acacia trees here tend to increase rapidly from age to age 3, and then decreased at age and 5, especially at age 5, diameter growth is very low (0.8 cm) iv The amount of growth in height (ihvn) of Acacia trees grown here tend to increase rapidly from age to age 3, and then decreased at age and 5, especially at age 5, the growth is very low (1,3 m) In general, height growth of acacia trees in this area is very high Compared with the diameter growth is much faster v MỤC LỤC TRANG LỜI CẢM ƠN i TÓM TẮT ii ABSTRACT iv MỤC LỤC vi NHỮNG CHỮ VIẾT TẮT VÀ KÍ HIỆU ix DANH SÁCH CÁC BẢNG x DANH SÁCH CÁC HÌNH xi CHƢƠNG MỞ ĐẦU 1.1 Đặt vấn đề 1.2.2Mục tiêu nghiên cứu 1.2Mục đích mục tiêu đề tài 1.2.1 Mục đích nghiên cứu Chƣơng TỔNG QUAN 2.1 Tình hình nghiên cứu sinh trƣởng rừng 2.1.1 Khái niệm sinh trƣởng rừng 2.1.2 Tình hình nghiên cứu sinh trƣởng rừng giới 2.1.3 Tình hình nghiên cứu sinh trƣởng rừng việt nam 2.2 Tổng quan khu vực nghiên cứu 12 2.2.1 Điều kiện tự nhiên 12 2.2.1.1 Vị trí địa lý 12 2.2.1.2 Địa hình, đất đai 13 2.2.1.3 Khí hậu 13 2.2.1.4 Thủy văn 14 2.2.1.5 Tài nguyên rừng 15 2.2.2 Điều kiện kinh tế - xã hội 15 2.2.2.1 Dân số - kinh tế 15 vi 2.2.2.2 Cơ sở hạ tầng 16 2.3 Tổng quan đối tƣợng nghiên cứu 17 2.3.1 Đối tƣợng nghiên cứu 17 2.3.2 Đặc điểm đối tƣợng nghiên cứu 17 2.3.3 Đặc tính sinh học 18 2.3.4 Đặc điểm sinh thái 19 Chƣơng NỘI DUNG VÀ PHƢƠNG PHÁP NGHIÊN CỨU 20 3.1 Nội dung nghiên cứu 20 3.2 Phƣơng pháp nghiên cứu 20 3.2.1 Công tác chuẩn bị 20 3.2.2 Công tác ngoại nghiệp 20 3.2.3 Công tác nội nghiệp 22 3.2.3.1 Nghiên cứu quy luật phân bố số theo tiêu sinh trƣởng 22 3.2.3.2 Nghiên cứu quy luật sinh trƣởng rừng 23 3.2.3.3 Nghiên cứu phát triển thể tích theo tuổi rừng 24 3.2.3.4 Nghiên cứu tăng trƣởng rừng 24 Chƣơng KẾT QUẢ NGHIÊN CỨU VÀ THẢO LUẬN 25 4.1 Quy luật phân bố số nhân tố sinh trƣởng rừng keo lai trồng khu vực nghiên cứu 25 4.1.1 Phân bố số theo cấp đƣờng kính rừng keo lai trồng khu vực nghiên cứu 25 4.1.2 Phân bố số theo cấp chiều cao rừng keo lai trồng khu vực nghiên cứu 27 4.1.3 Phân bố số theo cấp đƣờng kính tán rừng keo lai trồng khu vực nghiên cứu 29 4.2 Quy luật sinh trƣởng rừng keo lai trồng khu vực nghiên cứu 31 4.2.1 Quy luật sinh trƣởng đƣờng kính (D1,3) rừng keo lai trồng khu vực nghiên cứu 31 4.2.2 Quy luật sinh trƣởng chiều cao (Hvn) rừng keo lai trồng khu vực vii nghiên cứu 33 4.2.3 Tƣơng quan đƣờng kính (D1,3) chiều cao ( Hvn) rừng rừng keo lai trồng khu vực nghiên cứu 34 4.3 Quy luật sinh trƣởng thể tích (V/A) rừng keo lai trồng khu vực nghiên cứu 36 4.3.1 Xác định hình số (f) keo lai 36 4.3.2 Sinh trƣởng thể tích (V) keo lai theo tuổi 36 4.4 Đặc điểm tăng trƣởng rừng keo lai trồng khu vực nghiên cứu 38 4.4.1 Lƣợng tăng trƣởng đƣờng kính (id1.3) rừng keo lai trồng khu vực nghiên cứu 38 4.4.2 Lƣợng tăng trƣởng chiều cao (ihvn) rừng keo lai trồng khu vực nghiên cứu 39 Chƣơng KẾT LUẬN VÀ KIẾN NGHỊ 42 5.1 Kết luận 42 5.2 Kiến nghị 43 TÀI LIỆU THAM KHẢO 44 viii Simple Regression - Hvn vs D Dependent variable: Hvn (Chieu cao) Independent variable: D (Duong kinh) Reciprocal-X model: Y = a + b/X Coefficients Least Standard T Squares Parameter Estimate Error Statistic P-Value Intercept 14.313 1.63253 8.76738 0.0031 Slope -17.6507 4.4273 -3.98678 0.0283 Analysis of Variance Source Sum of Df Mean FP-Value Squares Square Ratio Model 75.9288 75.9288 15.89 0.0283 Residual 14.3312 4.77708 Total 90.26 (Corr.) Correlation Coefficient = -0.917182 R-squared = 84.1223 percent R-squared (adjusted for d.f.) = 78.8297 percent Standard Error of Est = 2.18565 Mean absolute error = 1.51559 Durbin-Watson statistic = 1.56725 (P=0.1025) Lag residual autocorrelation = 0.0530703 The StatAdvisor The output shows the results of fitting a reciprocal-X model to describe the relationship between Hvn and D The equation of the fitted model is Hvn = 14.313 - 17.6507/D Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between Hvn and D at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 84.1223% of the variability in Hvn The correlation coefficient equals -0.917182, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 2.18565 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 1.51559 is the average value of the residuals The DurbinWatson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level oo Simple Regression - Hvn vs D Dependent variable: Hvn (Chieu cao) Independent variable: D (Duong kinh) Reciprocal-Y model: Y = 1/(a + b*X) Coefficients Least Squares Standard Paramet Estimate Error er Intercept 0.370132 0.0594022 Slope -0.0419217 0.0105662 T Statistic P-Value 6.23095 -3.96754 0.0083 0.0286 Analysis of Variance Source Sum of Df Mean FP-Value Squares Square Ratio Model 0.052744 0.052744 15.74 0.0286 Residual 0.010052 0.00335066 Total 0.062796 (Corr.) Correlation Coefficient = -0.916475 R-squared = 83.9926 percent R-squared (adjusted for d.f.) = 78.6568 percent Standard Error of Est = 0.0578849 Mean absolute error = 0.0390638 Durbin-Watson statistic = 1.93778 (P=0.1665) Lag residual autocorrelation = -0.194089 The StatAdvisor The output shows the results of fitting a reciprocal-Y model to describe the relationship between Hvn and D The equation of the fitted model is Hvn = 1/(0.370132 - 0.0419217*D) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between Hvn and D at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 83.9926% of the variability in Hvn The correlation coefficient equals -0.916475, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.0578849 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.0390638 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level pp Simple Regression - Hvn vs D Dependent variable: Hvn (Chieu cao) Independent variable: D (Duong kinh) Exponential model: Y = exp(a + b*X) Coefficients Least Standard T Squares Parameter Estimate Error Statistic P-Value Intercept 0.817814 0.170227 4.80427 0.0172 Slope 0.244065 0.0302791 8.06052 0.0040 NOTE: intercept = ln(a) Analysis of Variance Source Sum of Df Mean FP-Value Squares Square Ratio Model 1.78774 1.78774 64.97 0.0040 Residual 0.082547 0.0275157 Total 1.87029 (Corr.) Correlation Coefficient = 0.977683 R-squared = 95.5864 percent R-squared (adjusted for d.f.) = 94.1152 percent Standard Error of Est = 0.165878 Mean absolute error = 0.112878 Durbin-Watson statistic = 1.82502 (P=0.1269) Lag residual autocorrelation = -0.149112 The StatAdvisor The output shows the results of fitting an exponential model to describe the relationship between Hvn and D The equation of the fitted model is Hvn = exp(0.817814 + 0.244065*D) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between Hvn and D at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 95.5864% of the variability in Hvn after transforming to a reciprocal scale to linearize the model The correlation coefficient equals 0.977683, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.165878 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.112878 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level qq Simple Regression - Hvn vs D Dependent variable: Hvn (Chieu cao) Independent variable: D (Duong kinh) Square root-X model: Y = a + b*sqrt(X) Coefficients Least Standard T Squares Parameter Estimate Error Statistic P-Value Intercept -5.94221 0.877963 -6.76817 0.0066 Slope 6.9463 0.390302 17.7972 0.0004 Analysis of Variance Source Sum of Df Mean F-Ratio P-Value Squares Square Model 89.4131 89.4131 316.74 0.0004 Residual 0.846871 0.28229 Total (Corr.) 90.26 Correlation Coefficient = 0.995298 R-squared = 99.0617 percent R-squared (adjusted for d.f.) = 98.749 percent Standard Error of Est = 0.53131 Mean absolute error = 0.389889 Durbin-Watson statistic = 1.53027 (P=0.0600) Lag residual autocorrelation = 0.0258132 The StatAdvisor The output shows the results of fitting a square root-X model to describe the relationship between Hvn and D The equation of the fitted model is Hvn = -5.94221 + 6.9463*sqrt(D) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between Hvn and D at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 99.0617% of the variability in Hvn The correlation coefficient equals 0.995298, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.53131 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.389889 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level rr Phụ lục KẾT QUẢ PHÂN TÍCH HỒI QUY VÀ TƯƠNG QUAN SINH TRƯỞNGVỀ THỂ TÍCH THEO TUỔI (V/A) Tuổi Vtn Vlt 0.000237 0.000264 0.002455 0.002628 0.015504 0.010077 0.028452 0.026148 0.039095 0.054783 ss Simple Regression - V vs A Dependent variable: V (The Tich) Independent variable: A (Tuoi) Multiplicative model: Y = a*X^b Coefficients Least Standard T Squares Parameter Estimate Error Statistic P-Value Intercept -8.23881 0.287564 -28.6503 0.0001 Slope 3.31447 0.258251 12.8343 0.0010 NOTE: intercept = ln(a) Analysis of Variance Source Sum of Df Mean F-Ratio P-Value Squares Square Model 17.7473 17.7473 164.72 0.0010 Residual 0.323227 0.107742 Total (Corr.) 18.0705 Correlation Coefficient = 0.991016 R-squared = 98.2113 percent R-squared (adjusted for d.f.) = 97.6151 percent Standard Error of Est = 0.328241 Mean absolute error = 0.206106 Durbin-Watson statistic = 1.69784 (P=0.0980) Lag residual autocorrelation = -0.043545 The StatAdvisor The output shows the results of fitting a multiplicative model to describe the relationship between V and A The equation of the fitted model is V = exp(-8.23881 + 3.31447*ln(A)) Or ln(V) = -8.23881 + 3.31447*ln(A) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between V and A at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 98.2113% of the variability in V The correlation coefficient equals 0.991016, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.328241 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.206106 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level tt Simple Regression - V vs A Dependent variable: V (The Tich) Independent variable: A (Tuoi) Logarithmic-X model: Y = a + b*ln(X) Coefficients Least Squares Standard T Parameter Estimate Error Statistic P-Value Intercept -0.00596682 0.00664394 -0.898084 0.4353 Slope 0.0241415 0.00596668 4.04605 0.0272 Analysis of Variance Source Sum of Df Mean Square F-Ratio P-Value Squares Model 0.000941523 0.000941523 16.37 0.0272 Residual 0.00017254 0.000057513 Total (Corr.) 0.00111406 Correlation Coefficient = 0.919307 R-squared = 84.5125 percent R-squared (adjusted for d.f.) = 79.3501 percent Standard Error of Est = 0.00758376 Mean absolute error = 0.00534544 Durbin-Watson statistic = 1.65182 (P=0.0861) Lag residual autocorrelation = -0.0491219 The StatAdvisor The output shows the results of fitting a logarithmic-X model to describe the relationship between V and A The equation of the fitted model is V = -0.00596682 + 0.0241415*ln(A) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between V and A at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 84.5125% of the variability in V after transforming to a Y/(1-Y) scale to linearize the model The correlation coefficient equals 0.919307, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.00758376 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.00534544 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level uu Simple Regression - V vs A Dependent variable: V (The Tich) Independent variable: A (Tuoi) Double reciprocal model: Y = 1/(a + b/X) Coefficients Least Standar T Squares d Parameter Estimate Error Statistic P-Value Intercept -1533.99 486.06 -3.15597 0.0510 Slope 5441.91 898.384 6.05744 0.0090 Analysis of Variance Source Sum of Df Mean F-Ratio P-Value Squares Square Model 1.24644E7 1.24644E7 36.69 0.0090 Residual 1.01909E6 339697 Total (Corr.) 1.34834E7 Correlation Coefficient = 0.961467 R-squared = 92.4419 percent R-squared (adjusted for d.f.) = 89.9226 percent Standard Error of Est = 582.835 Mean absolute error = 398.024 Durbin-Watson statistic = 1.73252 (P=0.1388) Lag residual autocorrelation = -0.0239387 The StatAdvisor The output shows the results of fitting a double reciprocal model to describe the relationship between V and A The equation of the fitted model is V = 1/(-1533.99 + 5441.91/A) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between V and A at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 92.4419% of the variability in V The correlation coefficient equals 0.961467, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 582.835 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 398.024 is the average value of the residuals The DurbinWatson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level vv Simple Regression - V vs A Dependent variable: V (The Tich) Independent variable: A (Tuoi) Reciprocal-X model: Y = a + b/X Coefficients Least Standard T Squares Parameter Estimate Error Statistic Intercept 0.0362357 0.00937091 3.86683 Slope -0.0417966 0.0173202 -2.41317 Analysis of Variance Source Sum of Df Mean Square Squares Model 0.000735276 0.000735276 Residual 0.000378788 0.000126263 Total (Corr.) 0.00111406 P-Value 0.0306 0.0947 F-Ratio P-Value 5.82 0.0947 Correlation Coefficient = -0.8124 R-squared = 65.9994 percent R-squared (adjusted for d.f.) = 54.6659 percent Standard Error of Est = 0.0112367 Mean absolute error = 0.00787298 Durbin-Watson statistic = 1.44861 (P=0.0647) Lag residual autocorrelation = 0.0651794 The StatAdvisor The output shows the results of fitting a reciprocal-X model to describe the relationship between V and A The equation of the fitted model is V = 0.0362357 - 0.0417966/A Since the P-value in the ANOVA table is greater or equal to 0.05, there is not a statistically significant relationship between V and A at the 95.0% or higher confidence level The R-Squared statistic indicates that the model as fitted explains 65.9994% of the variability in V The correlation coefficient equals -0.8124, indicating a moderately strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.0112367 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.00787298 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level ww Simple Regression - V vs A Dependent variable: V (The Tich) Independent variable: A (Tuoi) Exponential model: Y = exp(a + b*X) Coefficients Least Standard T Squares Parameter Estimate Error Statistic P-Value Intercept -8.86423 0.863673 -10.2634 0.0020 Slope 1.26634 0.260407 4.86292 0.0166 NOTE: intercept = ln(a) Analysis of Variance Source Sum of Df Mean FP-Value Squares Square Ratio Model 16.0362 16.0362 23.65 0.0166 Residual 2.03436 0.67812 Total (Corr.) 18.0705 Correlation Coefficient = 0.94203 R-squared = 88.7421 percent R-squared (adjusted for d.f.) = 84.9895 percent Standard Error of Est = 0.82348 Mean absolute error = 0.583866 Durbin-Watson statistic = 1.38453 (P=0.0307) Lag residual autocorrelation = 0.0456977 The StatAdvisor The output shows the results of fitting an exponential model to describe the relationship between V and A The equation of the fitted model is V = exp(-8.86423 + 1.26634*A) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between V and A at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 88.7421% of the variability in V after transforming to a reciprocal scale to linearize the model The correlation coefficient equals 0.94203, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.82348 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.583866 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is less than 0.05, there is an indication of possible serial correlation at the 95.0% confidence level Plot the residuals versus row order to see if there is any pattern that can be seen xx Simple Regression - V vs A Dependent variable: V (The Tich) Independent variable: A (Tuoi) Square root-X model: Y = a + b*sqrt(X) Coefficients Least Standard Squares Parameter Estimate Error Intercept -0.0379625 0.00976632 Slope 0.0328734 0.00563859 T Statistic P-Value -3.88709 0.0302 5.83007 0.0101 Analysis of Variance Source Sum of Df Mean FP-Value Squares Square Ratio Model 0.00102371 0.00102371 33.99 0.0101 Residual 0.0000903545 0.000030118 Total (Corr.) 0.00111406 Correlation Coefficient = 0.958591 R-squared = 91.8896 percent R-squared (adjusted for d.f.) = 89.1862 percent Standard Error of Est = 0.005488 Mean absolute error = 0.00381793 Durbin-Watson statistic = 1.79455 (P=0.1168) Lag residual autocorrelation = -0.124018 The StatAdvisor The output shows the results of fitting a square root-X model to describe the relationship between V and A The equation of the fitted model is V = -0.0379625 + 0.0328734*sqrt(A) Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between V and A at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 91.8896% of the variability in V The correlation coefficient equals 0.958591, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.005488 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.00381793 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level yy Simple Regression - V vs A Dependent variable: V (The Tich) Independent variable: A (Tuoi) Double square root model: Y = (a + b*sqrt(X))^2 Coefficients Least Standard T Squares Parameter Estimate Error Statistic P-Value Intercept -0.152058 0.0250617 -6.06732 0.0090 Slope 0.157013 0.0144694 10.8514 0.0017 Analysis of Variance Source Sum of Df Mean F-Ratio P-Value Squares Square Model 0.023354 0.023354 117.75 0.0017 Residual 0.000594991 0.00019833 Total (Corr.) 0.023949 Correlation Coefficient = 0.9875 R-squared = 97.5156 percent R-squared (adjusted for d.f.) = 96.6875 percent Standard Error of Est = 0.014083 Mean absolute error = 0.00870296 Durbin-Watson statistic = 2.774 (P=0.6370) Lag residual autocorrelation = -0.479894 The StatAdvisor The output shows the results of fitting a double square root model to describe the relationship between V and A The equation of the fitted model is V = (-0.152058 + 0.157013*sqrt(A))^2 Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between V and A at the 95.0% confidence level The R-Squared statistic indicates that the model as fitted explains 97.5156% of the variability in V after transforming to a logarithmic scale to linearize the model The correlation coefficient equals 0.9875, indicating a relatively strong relationship between the variables The standard error of the estimate shows the standard deviation of the residuals to be 0.014083 This value can be used to construct prediction limits for new observations by selecting the Forecasts option from the text menu The mean absolute error (MAE) of 0.00870296 is the average value of the residuals The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level zz Phụ lục HÌNH SỐ F1.3 TỪ CÁC CÂY GIẢI TÍCH * Cây giải tích 1: Hvn = 14.3 Hmt = 14.7 Năm trồng: 2008 vị trí 1.3 11 12 13 D1 9.6 8.2 7.9 7.5 7.1 6.8 6.1 5.5 5.2 4.3 3.3 2.5 1.9 D2 9.8 8.3 8.2 7.7 7.2 6.7 6.3 5.7 5.1 3.3 2.3 1.8 Dtb 9.7 8.25 8.05 7.6 7.15 6.75 6.2 5.9 5.3 4.6 3.8 2.8 2.15 tổng gtb g 0.0073861 0.0053429 0.005087 0.0045342 0.0040131 0.0035767 0.0030175 0.0027326 0.0022051 0.0016611 0.0011335 0.0006154 0.0003629 0.036581 0.0028139 V V viên trụ f1.3 0.040239 0.072744 0.55 aaa * Cây giải tích 2: Hvn = 13.7 Hmt = 14.1 Năm trồng: 2008 vị trí 1.3 10 11 12 D1 8.7 7.8 7.4 7.1 6.5 6.1 5.1 4.5 4.2 3.4 2.8 2.3 1.8 D2 8.2 7.7 7.6 7.1 6.9 6.6 5.7 4.4 3.9 3.2 2.8 2.2 1.9 Dtb 8.45 7.85 7.7 7.25 6.55 5.9 5.05 4.45 4.05 3.3 2.8 2.25 1.85 tổng gtb g 0.00561 0.00484 0.00465 0.00413 0.00385 0.00337 0.00273 0.00200 0.00155 0.00129 0.00085 0.00062 0.00040 0.00027 0.03150 0.00262 V V viên trụ f1.3 0.0359579 0.0637634 0.56 bbb * Cây giải tích 3: Hvn = 12.8 Hmt = 13.0 Năm trồng: 2009 vị trí D1 1.3 10 11 D2 8.1 7.6 7.4 7.2 6.6 6.4 5.7 4.5 3.1 2.8 2.4 2.1 1.8 Dtb 8.6 7.7 7.3 7.1 6.5 6.3 5.7 4.4 3.1 2.7 2.4 1.8 V V viên trụ f1.3 8.35 7.65 7.4 7.15 6.55 6.35 5.7 4.45 3.1 2.75 2.4 2.05 1.8 tổng gtb g 0.005473 0.004594 0.004241 0.004013 0.003368 0.003165 0.00255 0.001554 0.000754 0.000594 0.000452 0.00033 0.000254 0.027103 0.002464 0.031538 0.054282 0.581004 ccc ... dụng điện đạt 90% Hệ thống điện lưới có 02 tuyến: 20KW kéo dài từ trung tâm huyện đến trung tâm xã tuyến 35KW kéo từ xã đến trung đoàn Tuy chưa hoàn thiện nhìn chung bước đầu đáp ứng nhu cầu... nhẹ, tầng đất dày, tơi xốp, có độ phì cao + Đất xám phù sa cổ phân bố tập trung phía Bắc sơng EA H’Leo, thành phần giới thịt trung bình thịt nhẹ + Đất xám cát đá: loại đất chiếm phần lớn diện tích... tháng 10 - Mùa khô từ tháng 11 đến tháng năm sau 13 Nhiệt độ trung bình 24oC, cao vào tháng (26,5oC), thấp vào tháng (21oC) Độ ẩm trung bình 78,7%, cao vào tháng (82%), thấp vào tháng tháng (75%)