Estimating the variability of tillage forces on a chisel plough shank by modeling the variability of tillage system parameters

In this paper, a probabilistic approach is proposed for quantifying the variability of the tillage forces for the shank of a chisel plough with narrow tines and to estimate the failure probability. An existing three-dimensional analytical model of tool forces from McKyes was used to model the interaction between the tillage tools and the soil. The variability of tillage forces was modeled, taking into account the variability of soil engineering properties, tool design parameters and operational conditions. The variability of the soil engineering properties was modeled by means of experimental observations. The dispersion effect of each tillage system parameter on the tillage forces was determined by a sensitivity analysis. The results show that the variability of the horizontal and vertical forces follows a lognormal distribution (μ = 0.872, ξ = 0.449; μ = 0.004, ξ = 0.447) and the relationship between these forces is positive and quasi-linear (ρ(P_H, P_v) = 0.93).This lognormal variability was integrated into the estimation of the failure probability for the shank by using Monte Carlo simulation (MCS) and the first-order reliability method (FORM). The results obtained by these two methods, with the assumption of non-correlation between the horizontal and vertical forces, were almost identical. However, the FORM method was faster and simpler, compared to the MCS technique. Furthermore, the correlation between the horizontal and vertical forces has no significant effect on the failure probability, regardless of the correlation strength. Therefore, it is concluded that the FORM method can be used to estimate the failure probability without considering the correlation between horizontal and vertical forces.     

Digital image analysis to estimate the live weight of broiler

Computer assisted digital image analysis was performed to investigate the possibility of estimating body weight of live broiler. To achieve the stated objective, 100 Arbor acres broiler chicks were reared under standard rearing condition and 1200 digital images were captured from 20 randomly selected broilers during the 7-42 days growing period. The captured images were analyzed by raster image analysis software (IDRISI 32) to determine the broiler body surface area and developed a linear equation to estimate weights of the broiler from its body surface-area pixels. The developed weight predicted equation based on surface-area pixels was log W = 1.060406(log P) + 0.173756(log A) − 2.029268 (W = estimated body weight, P = surface-area pixels and A = age at weighing) and the degree of goodness of fit of this equation was 0.999. The relative error in weight estimation of broiler chicken by image analysis, expressed in terms of percent error of the residuals from surface-area pixels was in between 0.04 and 16.47. On the other hand, the estimated body weights were not significantly (p > 0.05) difference from manually measured body weights up to 35 days of age. Thus, the development of a practical imaging system for weighing live broiler is feasible.     

Development of model based sensors for the supervision of a solar dryer

Solar dryers are increasingly used in developing countries as an alternative to drying in open air, however the inherent variability of the drying conditions during day and along year drive the need for achieving low cost sensors that would enable to characterize the drying process and to react accordingly. This paper provides three different and complementary approaches for model based sensors that make use of the psychrometric properties of the air inside the drying chamber and the temperature oscillations of the wood along day. The simplest smart sensor, Smart-1, using only two Sensirion sensors, allows to estimate the accumulated water extracted from wood along a complete drying cycle with a correlation coefficient of 0.97. Smart-2 is a model based sensor that relays on the diffusion kinetics by means of assesing temperature and relative humidity of the air inside the kiln. Smart-2 model allows to determine the diffusivity, being the average value of D for the drying cycle studied equal to 5.14 × 10⁻¹⁰ m² s⁻¹ and equal to 5.12 ×  10⁻¹⁰ m² s⁻¹ for two experiments respectively. The multidistributed supervision of the dryer shows up the lack of uniformity in drying conditions supported by the wood planks located in the inner or center of the drying chamber where constant drying rate kinetics predominate. Finally, Smart-3 indicates a decreasing efficiency along the drying process from 0.9 to 0.2     

Assessing effect of wind tunnel sizes on air velocity and concentration boundary layers and on ammonia emission estimation using computational fluid dynamics (CFD)

The objective of this study was to investigate the effect of different geometric sizes of wind tunnels on aerial boundary layers above the emission surface and therefore their effect on ammonia emission using CFD tool. Five wind tunnels of different sizes were used for the CFD simulation. Detail experimental measurements on air velocity and concentration profiles above the emission surface were realised using average inlet velocities of 0.1, 0.2, 0.3, and 0.4 m s⁻¹ in two wind tunnels under isothermal condition. The TAN (Total Ammoniacal Nitrogen) and pH of ammonia aqueous solution were kept constant during the experiments. The boundary conditions necessary for the CFD study were obtained from the measured experimental data. The CFD model used for simulations was first validated using the data from the two wind tunnel experiments. For assessing the effects of wind tunnel size, the air velocity range of 0.1-0.6 m s⁻¹ was used in CFD investigations. It was found that the velocity and concentration boundary layer thickness decreased with the increase of inlet air velocity where the concentration boundary was thinner than the corresponding velocity boundary layer. Wind tunnel sizes affected both velocity and concentration boundary layer thicknesses (P < 0.001). The velocity and concentration boundary layer was thicker in a wind tunnel with larger heights than in small height. The over estimation of ammonia emission of smaller wind tunnels were observed comparing to the largest wind tunnel or open field situation (P < 0.001). Non-linear regression equations were developed using four wind tunnels data for velocity boundary layer thickness (δ_u), concentration boundary layer thickness (δ_c), and ammonia mass transfer coefficient (k_G) as a function of wind tunnel height (H) and average inlet velocity (u_m), which given clear quantitative indication of effects of H, and u_m on δ_u, δ_c, and k_G, respectively.     

Vibration analysis during grass harvesting according to ISO vibration standards

This research evaluated the working efficiency and comfort of operation by measuring vibration acceleration of tractors during grass harvesting. A real-time kinematic global positioning system and an inertial measurement unit installed in a tractor normally used by farmers during grass harvesting were used to acquire tractor vibration acceleration data. Analysis of the position and vibration acceleration data of tractors by a Fourier transformation yielded a power spectrum of vibration acceleration at each frequency (1-10 Hz) and position. The root mean square of vibration acceleration at each frequency (1-10 Hz) was calculated with the center frequency of the 1/3 octave bands (1.0, 1.25, 1.6, 2.0, 2.5, 3.15, 4, 5, 6.3, 8, and 10 Hz) based on ISO standards. To evaluate the working efficiency in the grassland, geographical information system maps were generated using the power spectrum of vibration acceleration and the limit on working time for each frequency that negatively affected the tractor driver. The vibration acceleration in the longitudinal (a_x) and lateral (a_y) directions at the center frequency of the 1/3 octave band below 2.0 Hz exceeded the fatigue-decreased proficiency and reduced the comfort boundaries stipulated in ISO 2631 (1974). In the area where working characteristics are severe, the vibration acceleration in the vertical direction (a_z) is high. The vibration acceleration in the a_z direction at the center frequency of the 1/3 octave band (5-10 Hz) clearly indicates discomfort during grass harvesting and a decrease in the work efficiency beyond 1 h. The total vibration acceleration (a_ν) at the center frequency of 5.0 Hz of the 1/3 octave band served to evaluate comfort in the whole field during grass harvesting—the a_ν value is higher than that at other frequencies. The area with severe working characteristics showed a higher a_ν value at the center frequency of 8.0 Hz than that at other frequencies.     

A web-based model for simulating whole-farm beef cattle systems

This paper details the rationale and procedures included in a web-based simulator containing production of beef cattle and cash crops. All biophysical and economical definitions including management in terms of rules constitute user-defined scenarios, which can be saved, retrieved, modified and deleted. Herbage growth may be either provided by the user or estimated from daily climate information. Scenarios are simulated and their outcomes are sent to the user's e-mail as a spreadsheet file, including data and pre-designed graphs to facilitate the interpretation of results. An example simulation study of a grazing-based finishing beef steers with a cycle of 12 months is presented, where new weaners enter the system in the autumn. Increased stocking rates, SR (150, 170, 190 and 210 heads in a 100-ha farm) and different summer maize feeding (SMF) rates were compared (SMF₀ = control and SMF₁ = intermittent rule-driven maize feeding during summer). In this simulation study, “deviations” from user-defined targets are simplified into two associated rules (a) average farm herbage mass deviation to adjust herbage allowance, and (b) target animal live weight deviation, associated to SMF₁. The proportion of unfinished steers at 28th February increased linearly (p ≤ 0.01) with higher stocking rates and became zero at any stocking rate where the SMF rule was operating (SMF₁). The economic response of SR × SMF interaction was significant for gross margin, indicating a positive linear association (p ≤ 0.05) of SMF₁ treatment (rule activated) when SR increases. The potential use of the web simulator as a flexible tool for investigation, training and decision making are discussed.     

Determination of visual quality of tomato paste using computerized inspection system and artificial neural networks

An artificial neural network (ANN) integrated computerized inspection system (CIS) was developed to determine tomato paste color in CIE L^∗, a^∗, and b^∗ color format and the number and size of dark specks which exist in the product. The usability of CIS in the determination of the number and the size of dark specks in tomato paste were investigated by comparing the results of CIS and human inspectors. While the inspectors had difficulties not only in determination of the specks having a diameter less than 0.2 mm but also in correct diameter measurement for all specks, the CIS had good determination and measurement capability. In 99 tomato paste samples, the number of the specks having diameter more than 0.2 mm were found by human inspectors and CIS as 233 and 235, respectively. However, the manual inspection gave inaccurate results for the diameter measurement of the specks. In the color evaluation of the tomato paste, strong correlations (R) were found between the results estimated from ANN-integrated CIS and those obtained from colorimeter (0.889, 0.958, 0.907 and 0.987 for L^∗, a^∗, b^∗ and a^∗/b^∗, respectively). The whole system is adapted to a graphical user interface (GUI) for use by a non-skilled person working in the tomato paste sector. While manual methods need approximately 5 min, GUI needs 20-25 s to determine, count and classify the dark specks and to measure the product color.     

Quantitative analysis of minerals and electric conductivity of red grape homogenates by near infrared reflectance spectroscopy

The use of near infrared (NIR) reflectance spectroscopy to measure the concentration of minerals and electric conductivity (EC) in red grape homogenates was investigated. Wine grape samples (n = 209) from two vintages, representing a wide range of varieties and regions were analysed by Inductively Coupled Plasma Optical Emission Spectrometry (ICPOES) for the concentrations of calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), sulphur (S), iron (Fe), and manganese (Mn) and scanned in reflectance in a NIR instrument (400-2500 nm). The spectra were pre-processed using multiple scatter correction (MSC) before developing the calibration models using partial least squares (PLS) regression and cross validation. Coefficients of determination in cross validation (R²) and the standard errors of cross validation (SECV) obtained were for Fe (0.60 and 1.49 mg kg⁻¹), Mn (0.71 and 0.41 mg kg⁻¹), Ca (0.75 and 60.89 mg kg⁻¹), Mg (0.84 and 12.93 mg kg⁻¹), K (0.78 and 285.34 mg kg⁻¹), P (0.70 and 40.19 mg kg⁻¹), S (0.88 and 14.45 mg kg⁻¹) and EC (0.87 and 7.66 mS). The results showed that Mg, S and EC in grape berries might be measured by NIR reflectance spectroscopy.     

Aerodynamic analysis and CFD simulation of several cellulose evaporative cooling pads used in Mediterranean greenhouses

The present work makes an aerodynamic analysis and computational fluid dynamics (CFD) simulation of the four commercial models of corrugated cellulose evaporative cooling pads that are most widely used in Mediterranean greenhouses. The geometric characteristics of the pads have been determined as well as the volume of water they retain at different flows of water, thus obtaining the mean thickness of the sheet of water which runs down them and their porosity. By means of low velocity wind tunnel experiments, the pressure drop produced by the pads has been recorded at different wind speeds and water flows. In this way it has been possible to obtain the relationship of the permeability and the inertial factor with pad porosity using a cubic type equation. Finally, a CFD simulation with a 3D model has been carried out for both dry pads (Q_w = 0 l s⁻¹ m⁻²) and wet ones (Q_w = 0.256 l s⁻¹ m⁻²), finding good correlation between the simulated and experimental pressure drop, with maximum differences of 9.08% for dry pads and 15.53% for wet ones at an airspeed of 3 m s⁻¹.     

Use of ground based hyperspectral remote sensing for detection of stress in cotton caused by leafhopper (Hemiptera: Cicadellidae)

Detection of crop stress is one of the major applications of hyperspectral remote sensing in agriculture. Many studies have demonstrated the capability of remote sensing techniques for detection of nutrient stress on cotton with only few on pest damage but none so far on leafhopper (LH) severity. Subsequent to introduction of Bt cotton, leafhopper is emerging as a key pest in several countries. In view of its wide host range, geographical distribution and damage potential, a study was initiated to characterise leafhopper stress on cotton, identify sensitive bands, and derive hyperspectral vegetation indices specific to this pest. Cotton plants with varying levels of LH severity were selected from three locations across major cotton growing regions of India. About 57-58 cotton plants from each location exhibiting different levels of LH damage symptoms were selected. Reflectance measurements in the spectral range of 350-2500 nm were made using hyperspectral radiometer. Simultaneously chlorophyll (Chl) and relative water content (RWC) were also estimated from the selected plants. Reflectance from healthy and leafhopper infested plants showed a significant difference in VIS and NIR regions. Decrease in Chl a pigment was more significant than Chl b in the infested plants and the ratio of Chl a/b showed a decreasing trend with increase in LH severity. Regression analysis revealed a significant linear relation between LH severity and Chl (R² = 0.505^∗∗), and a similar fit was also observed for RWC (R² = 0.402^∗∗). Plotting linear intensity curves between reflectance at each waveband with infestation grade resulted in six sensitive bands that exhibited maximum correlation at different regions of the electromagnetic spectrum (376, 496, 691, 761, 1124 and 1457 nm). Regression analysis of several ratio indices formulated with two or more of these sensitive bands led to the identification of new leaf hopper indices (LHI) with a potential to detect leafhopper severity. These new indices along with 20 other stress related hyperspectral indices compiled from literature were further tested for their ability to detect LH severity. Two novel indices LHI 2 and LHI 4 proposed in this study showed significantly high coefficients of determination across locations (R² range 0.521 to 0.825^∗∗) and hence have the potential use for detection of leafhopper severity in cotton.     

The vegetation classification in coal mine overburden dump using canopy spectral reflectance

The canopy spectral characteristics of typical plants in the overburden of the Fuxin coal mine dump were measured and analyzed. The reflectance of Leymus chinensis was affected by the soil, with a slight shift from green (550 nm) to the near infrared (NIR) region. Changes in chlorophyll and water absorption were not significant in the red (670 nm) and NIR bands, respectively. The reflectance curve trend for Artemisia lavandulaefolia was similar to those of Sophora japonica and Ulmus pumila, while the reflectance of S. japonica and U. pumila fluctuated in the NIR region (760-1200 nm), especially with greater water absorption around 930 and 1120 nm. In contrast, the reflectance of A. lavandulaefolia fluctuated slightly around 930 nm and a significant peak appeared at 1127 nm. In addition, the spectral reflectance of S. japonica was lower than for the other species in the visible band (400-700 nm). However, it was higher than for L. chinensis in the NIR region (780-1200 nm). Three classifiers, the self-organizing map (SOM), learning-vector quantization (LVQ), and a probabilistic neural network (PNN), were used to classify the vegetation and the results of all classifiers were compared based on total spectral reflectance data from 400 to 1200 nm. The PNN was the best classifier in terms of training and testing accuracy. The first difference reflectance was calculated, and the red edge parameter was able to classify the herbs (L. chinensis and A. lavandulaefolia) and the arbores (S. japonica and U. pumila) with an accuracy of 77 and 84%, respectively, although it did not perform as well for detail species. A mixing parameter matrix was built based on the sensitive wavelengths (550, 674, 810, 935, and 1125 nm), the vegetation indices (SAVI and NDGI), and the water absorption slope. High classification accuracy was obtained by applying the mixing parameter matrix. This method could be used for revegetation monitoring and in decision making.     

Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat

Hyperspectral data sets contain useful information for characterizing vegetation canopies not previously available from multi-spectral data sources. However, to make full use of the information content one has to find ways for coping with the strong multi-collinearity in the data. The redundancy directly results from the fact that only a few variables effectively control the vegetation signature. This low dimensionality strongly contrasts with the often more than 100 spectral channels provided by modern spectroradiometers and through imaging spectroscopy. With this study we evaluated three different chemometric techniques specifically designed to deal with redundant (and small) data sets. In addition, a widely used 2-band vegetation index was chosen (NDVI) as a baseline approach. A multi-site and multi-date field campaign was conducted to acquire the necessary reference observations. On small subplots the total canopy chlorophyll content was measured and the corresponding canopy signature (450-2500 nm) was recorded (n_obs = 42). Using this data set we investigated the predictive power and noise sensitivity of stepwise multiple linear regression (SMLR) and two ‘full spectrum’ methods: principal component regression (PCR) and partial least squares regression (PLSR). The NDVI was fitted to the canopy chlorophyll content using an exponential relation. For all techniques, a jackknife approach was used to obtain cross-validated statistics. The PLSR clearly outperformed all other techniques. PLSR gave a cross-validated RMSE of 51 mg m⁻² for canopy chlorophyll contents ranging between 38 and 475 mg m⁻² (0.99 ≤ LAI ≤ 8.74 m² m⁻²). The lowest accuracy was achieved using PCR (RMSE_cv = 82 mg m⁻² and ). The NDVI, even using chlorophyll optimized band settings, could not reach the accuracy of PLSR. Regarding the sensitivity to artificially created (white) noise, PCR showed some advantages, whereas SMLR was the most sensitive chemometric technique. For relatively small, highly multi-collinear data sets the use of partial least square regression is recommended. PLSR makes full use of the rich spectral information while being relatively insensitive to sensor noise. PLSR provides a regression model where the entire spectral information is taken - in a weighted form - into account. This method seems therefore much better adapted to deal with potentially confounding factors compared to any 2-band vegetation index which can only avoid the most harmful factor of variation.     

Sensors for detecting and logging spatial distribution of urine patches of grazing female sheep and cattle

Urine excreted in patches by grazing livestock accounts for much of the nitrogen (N) loss to the environment in grazing systems. These losses arise mainly through N leaching to ground water and gaseous losses to the atmosphere. Models of grazing systems ideally require data on urination frequency, N load in each urination event and spatial distribution patterns of urine. To date there has been a lack of suitable equipment for obtaining information on urination characteristics of grazing animals. This paper describes a urine sensor that detects and logs each urination event of female sheep and cattle. A thermistor suspended below the vulva continuously measures ambient temperature except when urine passes over it, causing the temperature to rise to near body temperature. Field validation showed 85% and 78% of sensor-detected urination events by sheep and cattle sensors, respectively, were seen by the observer. Some of the urination events identified by the sensor but not seen by the observer were confirmed by video footage. For cattle, only one observed urination event was not detected by the urine sensor, giving a 4% error rate of detection. Daily urination frequencies (ewes: 13-23 events day⁻¹; cows: 11-26 events day⁻¹) were similar to published data for these species. A custom-made GPS unit worn on the rump of the ewe and on the collar of the cow logged animal position continuously so that urine patch position could be determined. Examples of urine distribution patterns by ewes and beef cows in large, hilly paddocks clearly show campsite locations where a disproportionate number of urination events occurred. For sheep, the correlation between time spent in an area and the number of urination events in the same area was r = 0.82, but this correlation was weaker for cattle (r = 0.54).     

Performance evaluation of a crop/weed discriminating microsprayer

An intelligent real-time microspraying weed control system was developed. The system distinguishes between weed and crop plants and a herbicide (glyphosate) is selectively applied to the detected weed plants. The vision system captures 40 RGB images per second, each covering 140 mm by 105 mm with an image resolution of 800 × 600 pixels. From the captured images the forward velocity is estimated and the spraycommands for the microsprayer are calculated. Crop and weed plants are identified in the image, and weed plants are sprayed. Performance of the microsprayer system was evaluated under laboratory conditions simulating field conditions. A combination of maize (Zea mays L.), oilseed rape (Brassica napus L.) and scentless mayweed (Matricaria inodora L.) plants, in growth stage BBCH10, was placed in pots, which were then treated by the microspray system. Maize simulated crop plants, while the other species simulated weeds. The experiment were conducted at a velocity of 0.5 m/s. Two weeks after spraying, the fraction of injured plants was determined visually. None of the crop plants were harmed while 94% of the oilseed rape and 37% of the scentless mayweed plants were significantly limited in their growth. Given the size and shape of the scentless mayweed plants and the microsprayer geometry it was calculated that the microsprayer could only hit 64% of the scentless mayweed plants. The system was able to effectively control weeds larger than 11 mm × 11 mm.     

Evaluation of a wireless infrared thermometer with a narrow field of view

Many agricultural studies rely on infrared sensors for remote measurement of surface temperatures for crop status monitoring and estimating sensible and latent heat fluxes. Historically, applications for these non-contact thermometers employed the use of hand-held or stationary industrial infrared thermometers (IRTs) wired to data loggers. Wireless sensors in agricultural applications are a practical alternative, but the availability of low cost wireless IRTs is limited. In this study, we designed prototype narrow (10°) field of view wireless infrared sensor modules and evaluated the performance of the IRT sensor by comparing temperature readings of an object (T_obj) against a blackbody calibrator in a controlled temperature room at ambient temperatures of 15 °C, 25 °C, 35 °C, and 45 °C. Additional comparative readings were taken over plant and soil samples alongside a hand-held IRT and over an isothermal target in the outdoors next to a wired IRT. The average root mean square error (RMSE) and mean absolute error (MAE) between the collected IRT object temperature readings and the blackbody target ranged between 0.10 and 0.79 °C. The wireless IRT readings also compared well with the hand-held IRT and wired industrial IRT. Additional tests performed to investigate the influence of direct radiation on IRT measurements indicated that housing the sensor in white polyvinyl chloride provided ample shielding for the self-compensating circuitry of the IR detector. The relatively low cost of the wireless IRT modules and repeatable measurements against a blackbody calibrator and commercial IR thermometers demonstrated that these wireless prototypes have the potential to provide accurate surface radiometric temperature readings in outdoor applications. Further studies are needed to thoroughly test radio frequency communication and power consumption characteristics in an outdoor setting.     

A new integrated CFD modelling approach towards air-assisted orchard spraying—Part II: Validation for different sprayer types

A computational fluid dynamics (CFD) model to simulate airflow from air-assisted orchard sprayers through pear canopies was validated for three different sprayers; single-fan (Condor V), two-fan (Duoprop) and four-fan sprayers (AirJet Quatt). The first two sprayers are widely used in Belgium and the latter one is a new design. Validation experiments were carried out in an experimental orchard (pcfruit, Velm, Belgium) in spring 2008. Ultrasonic anemometers were used to measure the time-averaged velocity components at different vertical positions before the tree and after the tree when the sprayers were driven through the orchard. The model was able to predict accurately the peak jet velocity, U_m from all the sprayers considered at all distances from the sprayer centre and vertical positions. More than 95% of the local relative errors of U_m were below 20%. Average relative errors, E, and root mean square errors, E_RMS, were all less than 11.04% and 1.68 m s⁻¹, respectively. The regions of high- (up to 18.0 m s⁻¹ upstream) and low (down to 2.8 m s⁻¹ downstream)-air velocity zones for all the sprayers were accurately predicted. The simulation results showed that the Condor V sprayer had a highly disturbed vertical jet velocity profile, especially at higher heights. The Duoprop sprayer had high jet velocities at the two-fan positions and lower jet velocity in between the two fans. Within the canopy height the AirJet Quatt sprayer showed a more uniform distribution of air than the other two sprayers except the minor peaks at the fan positions. These situations were all confirmed by the measurements.     

饲料中添加糖萜素对大菱鲆幼鱼体成分、消化酶活力、血脂及肠道组织结构的影响

为了探讨饲料中添加糖萜素对大菱鲆(Scophthalmus maximus)幼鱼体成分、消化酶活力、血脂及肠道组织结构的影响,在6组基础饲料中分别添加0(D0)、25(D25)、50(D50)、75(D75)、100(D100)和200(D200)mg/kg糖萜素,实验期64 d。结果显示:各组间全鱼与背肌水分和粗蛋白含量无显著差异(P0.05);D100和D200组全鱼粗脂肪显著低于D0组(P0.05),D75组背肌粗脂肪显著高于D0组(P0.05),D200组背肌粗脂肪显著低于D0组(P0.05);D25和D50组全鱼粗灰分含量显著低于其他各组(P0.05),D200组显著高于D25~D75组(P0.05)。各组间饱和脂肪酸和单不饱和脂肪酸含量均不受饲料糖萜素添加水平的影响(P0.05);多不饱和脂肪酸除D75组,其他添加组均显著高于D0组(P0.05)。D200组甘油三酯和总胆固醇显著低于D0组(P0.05);D50组高密度脂蛋白胆固醇显著高于D0组(P0.05),D75~D200组显著低于D0组(P0.05);各组间低密度脂蛋白胆固醇含量无显著差异(P0.05)。各添加组胰蛋白酶活性显著高于D0组(P0.05);D25~D75组脂肪酶显著高于D0组(P0.05);饲料中添加糖萜素对幼鱼肠道淀粉酶活性无显著影响(P0.05)。在石蜡组织切片中:D50组前肠微绒毛长度显著高于其他各组(P0.05);D50组黏膜厚度显著高于D200组(P0.05);D25~D100组皱襞高度显著高于D0、D200组(P0.05)。综合以上实验结果,饲料中添加50~75mg/kg糖萜素可提高背肌多不饱和脂肪酸含量、降低血脂、改善肠道生理环境。     

水稻芽期耐寒性综合评价及耐寒指标筛选

为筛选水稻芽期耐寒指标并建立可靠的水稻芽期耐寒性数学评价模型,采用49个水稻种质资源,测定发芽率(GR)、相对发芽率(RGR)、发芽势(GP)、相对发芽势(RGP)、发芽指数(GI)、种子萌发指数(PI)、平均发芽时间(MGT)、成苗率(SR)和萌发系数(GC)9个指标并进行主成分及隶属函数等分析,对水稻芽期耐寒性进行综合评价。结果表明,根据水稻芽期耐寒性综合评价值(D)可以将49个水稻品种分为5个等级,分别是耐寒性极强品种(IRIS 313-11965、IRIS 313-8956和IRIS 313-11038,D为0.790～0.830)、耐寒性强品种(IRIS 313-11944等17个品种,D为0.609～0.745)、耐寒性中等品种(IRIS 313-11049等7个品种,D为0.503～0.576)、耐寒性弱品种(IRIS313-11986等13个品种,D为0.364～0.482)和耐寒性极弱品种(IRIS 313-10891等9个品种,D为0.187～0.282)。采用逐步回归分析法建立水稻芽期耐寒性的最优回归方程:D=0.326+0.020GI+0.021SR-0.028MGT+0.025PI+0.012GR+0.137RGP,筛选出发芽率、相对发芽势、发芽指数、种子萌发指数、平均发芽时间和成苗率6个与水稻芽期耐寒性显著相关的指标。低温胁迫条件下,可通过测定这6个指标对水稻品种的芽期耐寒性进行快速准确的鉴定及评价。