Establishment of Kinetics Models for Batch Fermentation Process of β-mannase with Bacillus licheniformis HDYM-04

In order to improve the yield of β-mannase and to investigate the rules of fermentation production, a high-yield β-mannase producing strain, Bacillus licheniformis HDYM-04, was used to investigate the kinetics models based on the optimal fermentation conditions： HDYM-04 strain was fermented at 37℃ for 30 h with agitation speed at 300 r/min and aeration rate at 3 L/min in a 5 L fermenter, the initial addition amount of konjac flour was 2%（w/v）, the initial pH of medium was 8.0, and the inoculum concentration was 6.7%（v/v）. Three batch fermentation kinetic models were established （cell growth kinetic model, substrate consumption kinetic model, product formation kinetic model） bases on Logistic and Luedeking-Piret equations. To be specific, cell growth kinetic model was dX/dt =0.431X （1- X/ 15.522 ）, substrate consumption kinetic model was -ds/dt =1.11 dX/dt ＋0.000 2 dP/dt ＋0.000 8X, and product formation kinetic model was dP/dt=133.1 dX ＋222.87X. The correlation coefficients R^2 of the three equations were 0.990 21, 0.989 08 and 0.988 12, respectively, which indicated a good correlation between experimental values and models. Therefore, the three equations could be used to describe the processes of cell growth, enzyme synthesis and substrate consumption during batch fermentation using B. licheniformis strain HDYM-04. The establishment of batch fermentation kinetic models （cell growth kinetic model, substrate depletion kinetic model, product formation kinetic model） could lay the theoretical foundation and provide practical reference for the applica- tion of HDYM-04 in fermentation industry.     

Influence of Climate and Socio-Economic Factors on the Spatio-Temporal Variability of Soil Organic Matter： A Case Study of Central Heilongjiang Province,China

For the scientific management of farmland, it is significant to understand the spatio-temporal variability of soil organic matter and to study the influences of related factors. Using geostatistical theory, GIS spatial analysis, trend analysis and a Geographically Weighted Regression （GWR） model, this study analyzed the response of soil organic matter to climate and socio-economic factors in central Heilongjiang Province during the past 25 years. Second soil survey data of China for 1979-1985, 2005 field sampling data, climate observations and socio-economic data for 1980-2005 were analyzed. First, soil organic matter in 2005 was spatially interpolated using the Co-Kriging method along with auxiliary data sets of soil type and pH. The spatio-temporal variability was then studied by comparison with the 1980s second soil census data. Next, the temporal trends in climate and socio-economic factors over the past 25 years were investigated. Finally, we examined the variation of the response of soil organic matter to climate and socio-economic factors using the GWR model spatially and temporally. The model showed that 53.82% area of the organic matter content remained constant and 29.39% has decreased during the past 25 years. The impact of precipitation on organic matter content is mainly negative, with increasing absolute values of the regression coefficient. The absolute value of regression coefficient of annual average temperature has decreased, and more areas are now under its negative effects. In addition, the areas of positive regression coefficient of annual sunshine hours have northward shifted, with the increasing absolute value of positive coefficient and decreasing absolute value of negative coefficient. The areas of positive regression coefficient of mechanized farming as a socio-economic factor have westward shifted, with the increasing absolute value of negative coefficient and decreasing absolute value of positive coefficient. The area of regions with the positive regression coefficient of irrigatio     

Prediction of Repair and Maintenance Costs of Two-wheel Drive Tractors in Iran

Predicting of repair and maintenance （R＆M） costs of tractors in any mechanized farm is necessary for owners and managers to obtain information on overall costs and to control financial balance and production economy. In this context a study was conducted to predict accumulated R＆M costs （Y） of two-wheel drive （2WD） tractors based on accumulated usage hours （X） in Misagh-e-Sabz Agribusiness Company in Iran. Recorded data of the company were used to determine regression models for predicting accumulated R＆M costs （as percentage of initial purchase price） based on accumulated usage hours. The statistical results of the study indicated that in order to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or less the power regression model Y=0.013 （X/100）1.677 with R2=0.976, and to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or more the polynomial regression model Y=0.004 （X/100）2-0.181 （X/1 00）＋4.373 with R2=0.998 can be strongly suggested.     

Estimation of Cucumber Evapotranspiration in Solar Greenhouse in Northeast China

The solar greenhouse without heating system has been widely used for vegetable production in Northeast China since the 1980s. The experiment was conducted in the solar greenhouse to study the relationship between evapotranspiration （ET） of cucumber and climatic factors. Reference evapotranspiration （ET0） and pan evaporation （Ep） were applied to determine cucumber evapotranspiration by regression methods. Results showed that the ET of cucumber increased with the increasing of solar radiation, air temperature and vapor pressure. The solar radiation was the most important factor that influences ET among environmental parameters. The determination coefficient （R2） was 0.865 between ET and Ep, higher than that between ET and ET0 （application of a constant vegetation coefficient, R2 = 0.46）. The pan coefficient （kp, determined from the ratio of ET to Ep） and the crop coefficients （kc, determined from the ratio of ET to ET0） showed considerable variability and no obvious systematic pattern could be described throughout the study period. Ep was linearly related to ET and 20 cm pan can be well used to determine the water requirement of cucumber under subsurface drip irrigation in this type of solar greenhouse.     

Gillnet Selectivity and Length at Maturity of Nile Tilapia （Oreochromis niloticus L.） in a Tropical Reservoir （Amerti： Ethiopia）

The selectivity of gillnets for Oreochromis niloticus in Amerti reservoir （9°63′ N, 37°23′ E） was determined from gillnets with four mesh sizes （60, 80, 100 and 120 mm）. Four selectivity models （a normal model assuming fixed spread, a normal model assuming that spread is proportional to mesh size, a lognormal model and a gamma model） were fitted to the data by using the share each length＇s catch total （SELECT） method. A total of 657 specimens of Oreochromis niloticus were caught （12.0-35.5 cm total length, TD. The sizes at first sexual maturity were 21.5 cm TL and 18.9 cm TL, respectively, for male and female Oreochromis niloticus. The lognormal selectivity curve provided the best fit to the data according to model deviance estimates with optimum selectivity of 16.66, 22.26, 27.78 and 33.38 cm TL for the 60, 80, 100 and 120 mm mesh sizes, respectively.     

Application of Fuzzy Regression Model to the Prediction of Field Mouse Occurrence Rate

Expressions were given to describe the closeness between the estimated value and observed value for two asymmetric exponential fuzzy numbers. Based on that, the model was given to solve the question of fuzzy multivariable regression with fuzzy input, fuzzy output and crisp coefficients. Finally, with this model, the prediction of field mouse occurrence rate had been done and the satisfied result was obtained.     

Genetic variation of yellow pigment and its components in foxtail millet(Setaria italica(L.) P.Beauv.) from different eco-regions in China

Kernel color is an important trait for assessing the commercial and nutritional quality of foxtail millet.Yellow pigment content(YPC)and carotenoid components(lutein and zeaxanthin)of 270 foxtail millet accessions,including 50 landraces and 220improved cultivars,from four different eco-regions in China were surveyed using spectrophotometry and high performance liquid chromatography methods.Results indicated that YPC had rich variance,ranging from 1.91 to 28.54 mg kg~(–1),with an average value of 17.80 mg kg~(–1).The average YPC of improved cultivars(18.31 mg kg~(–1))was significantly higher than that of landraces(15.51 mg kg~(–1)).The YPC in cultivars from the Loess Plateau spring sowing region(LPSSR)was the highest(20.59 mg kg~(–1)),followed by the North China summer sowing region(NCSSR,18.25 mg kg~(–1)),the northeast spring sowing region(NSSR,17.25 mg kg~(–1)),and the Inner Mongolia Plateau spring sowing region(IMPSSR,13.92 mg kg~(–1)).The variation coefficients of YPC in cultivars from NSSR,LPSSR,and IMPSSR were higher than that from NCSSR.A similar carotenoid profile was also obtained for 270 foxtail millet cultivars.Lutein and zeaxanthin accounted for approximately 55–65%of YPC in accessions.The lutein content was higher than zeaxanthin content in all cultivars.The ratio of lutein to zeaxanthin ranged from 1.51 to 6.06 with an average of 3.34.YPC was positively correlated with lutein(r=0.935,P0.01),zeaxanthin(r=0.808,P0.01),and growth duration(r=0.488,P0.01),whereas it was negatively correlated with grain protein(r=-0.332,P0.01)and 1 000-kernel weight(r=-0.153,P0.05).Our study is useful for screening and selecting cultivars with high levels of yellow pigment and for enhancing phytochemical concentrations in breeding programs.     

Improved Prediction and Reduction of Sampling Density for Soil Salinity by Different Geostatistical Methods

The spatial estimation for soil properties was improved and sampling intensities also decreased in terms of incorporated auxiliary data. In this study, kriging and two interpolation methods were proven well to estimate auxiliary variables： cokriging and regression-kriging, and using the salinity data from the first two stages as auxiliary variables, the methods both improved the interpolation of soil salinity in coastal saline land. The prediction accuracy of the three methods was observed under different sampling density of the target variable by comparison with another group of 80 validation sample points, from which the root-mean-square error （RMSE） and correlation coefficient （r） between the predicted and measured values were calculated. The results showed, with the help of auxiliary data, whatever the sample size of the target variable may be, cokriging and regression-kriging performed better than ordinary kriging. Moreover, regression-kriging produced on average more accurate predictions than cokriging. Compared with the kriging results, cokriging improved the estimations by reducing RMSE from 23.3 to 29% and increasing r from 16.6 to 25.5%, regression-kriging improved the estimations by reducing RMSE from 25 to 41.5% and increasing r from 16.8 to 27.2%. Therefore, regression-kriging shows promise for improved prediction for soil salinity and reduction of soil sampling intensity considerably while maintaining high prediction accuracy. Moreover, in regression-kriging, the regression model can have any form, such as generalized linear models, non-linear models or tree-based models, which provide a possibility to include more ancillary variables.     

Experimental Study on Working Performance of Rice Rope Direct Seeding Machine

Structure and sowing principles of rice rope direct seeding machine are introduced. In order to test the machine＇ s working performance, such as compacting effect, sowing depth, influence of sowing device to rice rope, etc., field experiments were conducted. It is concluded that mean slip ratio of compacting wheel 1 is 4.44%, wheel 2 is 5.58%, wheel 3 is 7.81%, and wheel 4 is 6.96%; mean depth of planting is 29.72 mm, and mean variability coefficient of planting depth is 6.39%. Maximum variability coefficient of planting depth is 8.40%. Rice rope＇s snapping is closely related with the machine＇s speed and guide thread wheel by sowing device orthogonal experiments. Test results show that the machine has a rational design, safe work and meets to the requirements of planting. This study has laid the foundation for further studying the project.     

Responses of the antioxidant system to fluroxypyr in foxtail millet (Setaria italica L.) at the seedling stage

Foxtail millet(Setaria italica L.) is an important food and fodder crop in semi-arid areas. However, there are few herbicides suitable for use on weed control in field-grown foxtail millet during the post-emergence herbicides stage. The present study was conducted using four concentrations(0.5, 1, 2, and 4 L ai ha–1) of foliar-applied fluroxypyr, and the effect of fluroxypyr on selected metabolic and stress-related parameters in foxtail millet were assessed after 15 days. In this study, increasing concentrations decreased plant height and accumulation of chlorophylls. Our results also showed that malondialdehyde(MDA) accumulated in response to fluroxypyr application, demonstrating increased lipid peroxidation due to excessive reactive oxygen species production. In response to this oxidative stress, the activities of antioxidant enzymes were generally enhanced. Non-enzymatic antioxidant defense systems, which function in concert with antioxidant enzymes, can also protect plant cells from oxidative damage by scavenging reactive oxygen species(ROS). In conclusion, the hybrid variety(Zhangzagu) exhibited a greater tolerance to fluroxypyr than did the conventional variety Jingu 21, which might be associated with the antioxidant mechanisms of Zhangzagu hybrid millet.     

Thin-layer Drying Characteristics and Modeling of Two Varieties Green Malt

Malting process includes steeping, germination and kilning of cereal grains in controlled conditions. The Kilning process is the most expensive stage of malting industry. In the present study, drying behavior of green malt of two different barley varieties （Sahra and Dasht） were evaluated at air temperatures ranging from 40 to 85 ℃, at constant air velocity of 6 m/s. The main objective of this research was to select the best drying equations, in order to use them for the calculation of drying time and energy consumption. For that the experimental data was fitted to five thin layer drying equations （Lewis, Henderson and Pabis, Page, Modified page and Two-term）. The coefficients of the equations were compared by three statistical parameters as residual sum of squares, standard error of estimate and mean relative deviation. The effect of temperature on the coefficients of the five selected equations was evaluated by linear regression. The results show that The Page model was found to be most suitable in describing the drying characteristics of green barley malt because of that has the lowest statistical parameters. The color of green barley malt was determined after drying using a spectro-colorimeter （Hunter Lab） in terms of Hunter L, a, and b values. Color measurement indicated that the AE index increased with an increase in drying air temperature.     

Spatiotemporal Characteristics of Reference Evapotranspiration and Its Sensitivity Coefficients to Climate Factors in Huang-Huai-Hai Plain,China

Climate change will have important implications in water shore regions,such as Huang-Huai-Hai（3H） plain,where expected warmer and drier conditions might augment crop water demand.Sensitivity analysis is important in understanding the relative importance of climatic variables to the variation in reference evapotranspiration（ET 0）.In this study,the 51-yr ET 0 during winter wheat and summer maize growing season were calculated from a data set of daily climate variables in 40 meteorological stations.Sensitivity maps for key climate variables were estimated according to Kriging method and the spatial pattern of sensitivity coefficients for these key variables was plotted.In addition,the slopes of the linear regression lines for sensitivity coefficients were obtained.Results showed that ET 0 during winter wheat growing season accounted for the largest proportion of annual ET 0,due to its long phenological days,while ET 0 was detected to decrease significantly with the magnitude of 0.5 mm yr-1in summer maize growing season.Solar radiation is considered to be the most sensitive and primarily controlling variable for negative trend in ET 0 for summer maize season,and higher sensitive coefficient value of ET 0 to solar radiation and temperature were detected in east part and southwest part of 3H plain respectively.Relative humidity was demonstrated as the most sensitive factor for ET 0 in winter wheat growing season and declining relativity humidity also primarily controlled a negative trend in ET 0,furthermore the sensitivity coefficient to relative humidity increased from west to southeast.The eight sensitivity centrals were all found located in Shandong Province.These ET 0 along with its sensitivity maps under winter wheat-summer maize rotation system can be applied to predict the agricultural water demand and will assist water resources planning and management for this region.     

Comparison of Near Infrared Spectroscopy Models for Determining Protein and Amylose Contents Between Calibration Samples of Recombinant Inbred Lines and Conventional Varieties of Rice

The near infrared spectra of 178 recombinant inbred lines （RILs） from the cross of Ⅱ-32B/Yuezaoxian 6 （YZX6） and 511 varieties in rice were acquired. A total of 80 RILs and 96 cultivars were selected as modeling samples by comparing the spectra similarity primarily. Three partial least square （PLS） regression models were developed, based on the RILs （RIL-model）, the varieties （Var-model） and their mixture （Mix-model）, for protein content （PC） and amylose content （AC）, respectively. Cross validation and outer prediction showed that the models were largely influenced by the range and distribution of modeling samples. The regression model of PC based on the cultivars and the model of AC based on RILs had higher coefficient of determination （r^2 ≥ 0.9） and lower root mean square error of cross validation （RMSECVs）. The disadvantages of RIL samples for PC model and variety samples for AC model were probably caused by the narrow range of variance. Aberrant predictions were obtained for outer sample with PC or AC outside the range or within the distribution gap of modeling samples. The Mix-models gave more reliable prediction as the distribution of RIL and variety modeling samples were complementary to each other.     

Adaptation of potato production to climate change by optimizing sowing date in the Loess Plateau of central Gansu,China

Potato grows in most part of China, it achieves higher yield and better quality in Gansu Province than in others. With global warming, its growth duration has been prolonged and sowing date become earlier than before. Therefore, to regulate its sowing date and growing period is of great significance for better harvest. In this study, experiments were conducted with six sowing-date treatments of potato in Dingxi, which is in the Loess Plateau of central Gansu Province in Northwest China in 2010. The growth period, morphological index and change in yield and their relationships with temperature, precipitation, and other climatic factors were investigated for each treatment. Results show that the crop with different sowing dates experienced different climate conditions, leading to distinct growth duration, plant height, and leaf area index. The growth duration was shortened due to a delay in sowing date. For each 15-day delay in sowing, the growth duration was reduced by 12 days on average. A significant linear relationship was found between numbers of days either from seeding to emergence or from flowering to harvest and mean temperature over the corresponding period. Dry matter accumulation, tuber fresh weight, and final yield were all decreased because of insufficient cumulative temperature over the shorter growing periods. Marked differences in tuber yield were discovered among the six treatments of sowing date, the potato planted on May 27 giving the highest yield. The potato planted either earlier or later would produce invariably lower yield than the treatment of May 27. Late May therefore can be taken as the optimum sowing time of potato in this region because the crop can fully utilize thermal resource. We conclude that to postpone sowing time is a good practice for potato production to adapt to climate warming in the Loess Plateau of central Gansu, China.     

Prediction of net energy value of corn and soybean meal for broiler chicken

Net energy （NE） is the most accurate and unbiased way in characterizing the energy content of feed. Comparatively speaking, research on NE prediction is still limited and under development. Therefore, it is important to correctly assess NE for further study. In this study, an energy balance trial and a fasting metabolism trial were used to measure the net energy for production （NEp） and the net energy for maintenance （NEm）, respectively. Meanwhile, a backward method of multiple linear regression was applied to establish prediction equations for NE. The results showed that corn NE is about 2 times higher than that of soybean meal, due to the efficiency of ME （k） utilization by the ingredients. Meanwhile, AME and acid detergent fiber （ADF） were found to be better predictors for the NE of corn and soybean meal, respectively. Furthermore, Equations 1（R^2=0.993, RSD=0.0091） and 12 （R^2=0.999, RSD=0.0008） were found to be better prediction equations in multiple linear regression analyses for corn and soybean meal, respectively. However, considering the cost of the analytical procedures, the accuracy of the prediction （RSD）, and the additional variability or errors due to interlaboratory variance, Equation 4 （R^2=0.990, RSD=0.0109） and Equation 20 （R^2=0.996, RSD=0.0043） were better models for corn and soybean meal, respectively. Nevertheless, these equations for corn and soybean meal should be applied only under similar experimental conditions.     

Recognizing production options for pearl millet in Pakistan under changing climate scenarios

Climate change is making the lands a harsher environment all over the world including Pakistan. It is expected to oppose us with three main challenges:increase in temperature up to 2–5°C(heat stress),increasing water stress and severe malnourishment due to climate change. It has been foreseen that there will be a 10% increase of dryland areas with climate change in the world,with more variability and incidences of short periods of extreme events(drought and heat stress). Pearl millet is a hardy,climate smart grain crop,idyllic for environments prone to drought and heat stresses. The crop continues to produce highly nutritious grain sustainably,thereby encouraging the fight against poverty and food insecurity due to its resilience. The crop is more responsive to good production options(planting time,planting density,inter/intra row spacing,nitrogen application and irrigation). It has high crop growth rate,large leaf area index and high radiation use efficiency that confers its high potential yield. In most of the cases,pearl millet is remained our agricultural answer to the climate calamity that we are facing,because it is selected as water saving,drought tolerant and climate change complaint crop. In view of circumstances,pearl millet cultivation must be retrieved by recognizing production options in context to changing climate scenarios of Pakistan using crop modeling techniques.     

Mathematical Modeling and Effect of Various Hot-Air Drying on Mushroom （Lentinus edodes）

An experimental study was performed to determine the characteristics and drying process of mushroom （Lentinus edodes） by 6 different hot-air drying methods namely isothermal drying, uniform raise drying, non-uniform raise drying, uniform intermittent drying, non-uniform intermittent drying and combined drying. The chemical composition （dry matter, ash, crude protein, crude fat, total sugars, dietary fiber, and energy）, color parameters （L, a＊, b＊, c＊, and h~） and rehydration capacities were determined. Among all the experiments, non-uniform intermittent drying reached a better comprehensive results due to the higher chemical composition, better color quality associated with high bright （26.381＋5.842）, high color tone （73.670＋2.975）, low chroma （13.349a：3.456） as well as the highest rehydration （453.76% weigh of dried body）. Nine kinds of classical mathematical model were used to obtained moisture data and the Midili-kucuk model can be described by the drying process with the coefficient （R2 ranged from 0.99790 to 0.99967）, chi-square （X2 ranged from 0.00003 to 0.00019） and root mean square error （RMSE ranged from 0.000486 to 0.0012367）.     

Selecting the Packaging System for Liquid Foods Using an ANP Model

This paper provides a model to identify the most appropriate packaging system （i.e. the industrial process by which the product is hygienically coupled with the container） for different liquid foods. The model developed is grounded on the Analytic Network Process （ANP） methodology, a powerful and flexible tool used in decision making. To select the appropriate packaging system, the model takes into account several factors, including packaging material, cost, safety, performance （e.g., speed and accuracy）, plant reliability and flexibility, which may directly or indirectly affect the suitability of the process. Moreover, the chemical and physical properties of commercial liquid foods, and the packaging technology are included in the model as further variables to be considered for the final choice. We try to answer the following research questions： is a filling system appropriate for a given liquid food？ Is it compatible with a defined packaging technology？ When several filling systems are available for a given liquid food, how can the most appropriate one be selected？ The ease of application of the model and the robustness of the results provided have been tested on a sample of 59 commercial liquid foods, for which the model allowed to identify the most suitable packaging system, providing useful practical guidelines. The model was developed in close collaboration with a panel of experts, operating in the beverage bottling industry, and validated by the same experts; thus, the resulting tool is suitable for use as a decision support system by food and bottling industries.     

Some Engineering Properties of Sunflower Seed and Its Kernel

Some engineering properties of sunflower seed and its kernel, Shahroodi variety as a case study, were investigated at various moisture content levels （3-14% d.b.） for three size categories （large, medium and small）. With increase of moisture content from 3 to 14% d.b., all the main dimensions （length, width and thickness）, geometric mean diameter, porosity, true density, terminal velocity and static coefficient of friction increased while bulk density and rupture force for both sunflower seed and its kernel decreased for all size categories. The results showed that the highest value of static coefficient of friction for both seed and kernel was on the rubber surface, followed by plywood, polyethylene, galvanized iron, and finally aluminium surfaces. The seeds required less compressive force to dehull when loaded under the horizontal as compared to the vertical orientation. But for kernels, the trend was the opposite. Also, the compressive forces needed to initiate rupture of sunflower seed hulls were higher （47.1-94.72 N） than those required to rupture the kernel （8.5-13.4 N） in both orientations.