Spring oat (Avena sativa) is produced for grain, hay, and green manure and can be integrated into a cropping system as a cover crop. Twenty-eight oat genotypes (G1, G2, G3, …., G28), selected for their adaptability t...Spring oat (Avena sativa) is produced for grain, hay, and green manure and can be integrated into a cropping system as a cover crop. Twenty-eight oat genotypes (G1, G2, G3, …., G28), selected for their adaptability to the Southwestern United States, were evaluated for their yield performance under sprinkler irrigation during four growing seasons (2005-2008) at the Agricultural Science Center at Farmington, New Mexico State University. The genotypes were arranged in randomized complete blocs design with four replications. Irrigation scheduling was based on evapotranspiration and the depletion criterion of 40% to 45% total available water (TAW) was practiced to prevent the plants from experiencing any water stress. Crop evapotranspiration estimated by the FAO crop coefficient and reference evapotranspiration approach was low about 2 mm/day during crop initial stage and increased with plant growth and reached the maximum during crop mid-season or reproductive stage. It decreased during crop late season. Daily crop evapotranspiration varied from 0.5 to 12.6 mm in 2008 and the seasonal Spring oat evapotranspiration varied from 535.8 to 591 mm. Averaged across the four growing seasons, oat evapotranspiration was 570.4 mm. The results showed that Spring oat plant height varied significantly with genotypes and ranged from 59.1 to 100.8 cm. Oat grain yield significantly varied with years and genotypes. Grain yield varied from 3386 to 6498 kg/ha and average yield was 4245, 4265, 5477, and 4025 kg/ha during the 2005, 2006, 2007 and 2008, respectively. The best performing genotypes were G1, G2, G7, G19, G20, G21 and G23 with average yield greater than 4800 kg/ha while G3, G13, G17 and G27 showed the lowest yield among the genotypes. Oat crop water use efficiency (CWUE) varied with genotype and years and ranged from 0.53 to 1.07 kg/m3 and averaged 0.65, 0.78, 0.91 and 0.70 kg/m3 in 2005, 2006, 2007 and 2008, respectively. The highest CWUE was achieved by G19 and the lowest CWUE was obtained by G13. Irrigation water use efficiency (IWUE) which represents the quantity of yield produced per cubic meter of water, varied from 0.57 to 1.20 kg/m3 while evapotranspiration water use efficiency (ETWUE) varied with genotype and year and ranged from 0.57 to 1.21 kg/m3 with the overall IWUE mean of 0.83 kg/m3 and ETWUE mean of 0.81 kg/m3.展开更多
Soybean hulls, an abundant byproduct of soybean processing, contain rich phytochemicals, fibers, proteins, and minerals. Currently soybean hulls are primarily used as animal feeds. For value-added soybean hull utiliza...Soybean hulls, an abundant byproduct of soybean processing, contain rich phytochemicals, fibers, proteins, and minerals. Currently soybean hulls are primarily used as animal feeds. For value-added soybean hull utilization, 25% soybean hulls were substituted for amaranth or whole oat flour (WOF) in novel gluten-free cookies. Composition, nutritional values, water-holding capacities, correlation between properties, and pasting and rheological properties of soybean hulls, amaranth, and WOF were appraised in comparison to wheat flour. Water loss, cookie texture, and geometrical properties of the cookies were examined. The results disclosed that soybean hulls, amaranth and WOF contain higher protein content, minerals, fiber, special amino acids, and critical vitamins (C and K) than wheat flour. Considerably higher total amino acid content was found in soybean hulls (18.33%) than wheat flour (12.77%). Water-holding capacities increased by replacing amaranth and WOF with soybean hulls. Soybean hulls exhibited higher rheological elastic properties than amaranth, WOF and wheat flours. The soybean hulls utilized in amaranth or WOF cookies greatly improved their nutritional value, the water retention and moisture content along with acceptable physical properties when compared to wheat flour cookies. This study explored the feasibility and potential of utilizing soybean hulls with amaranth and WOF in gluten-free bakery products and other food applications.展开更多
[目的]探究不同灌溉方式和灌水量对土壤水盐变化规律及燕麦生长特征的影响,为提高盐碱地作物的生产效能和土壤水分管理提供科学参考。[方法]采用盆栽试验,设置3种灌溉方式:常规灌溉、固定单侧灌溉(fixed unilateral root zone irrigatio...[目的]探究不同灌溉方式和灌水量对土壤水盐变化规律及燕麦生长特征的影响,为提高盐碱地作物的生产效能和土壤水分管理提供科学参考。[方法]采用盆栽试验,设置3种灌溉方式:常规灌溉、固定单侧灌溉(fixed unilateral root zone irrigation,FURI)、交替灌溉(alternative partial root zone irrigation,APRI),3组灌水量:W_1(60%θ_f~70%θ_f,θ_f为田间持水率),W_2(70%θ_f~80%θ_f)和W_3(80%θ_f~90%θ_f),以常规灌溉作为对照,共9组交互处理。[结果](1)不同灌溉方式下,土壤各层含水率变化趋势基本一致,随灌水量增加洗盐效果越显著,常规灌溉的深层含水率总体高于其他两种灌溉方式。(2)燕麦株高、叶绿素相对含量(relative chlorophyll content of leaves,SPAD)、品质随灌水量的增加而上升,与常规灌溉相比,W_2灌溉水平下,分根交替灌溉处理的粗脂肪,粗蛋白,β-葡聚糖含量分别增加7.02%,3.76%,6.06%,但降低了燕麦叶片的SPAD值,影响其光合能力。(3)随着燕麦生育期的推进,土壤盐分均呈现不同程度的累积,分根交替灌溉的积盐率最低,同时对燕麦根系生长、水分利用效率及产量影响显著,其中根系总长、根系总表面积、根系总体积较相同灌水量(W_2)的常规灌溉分别增加6.75%,6.92%,12.5%,水分利用效率提高17.32%。[结论]采用分根交替灌溉方式下的中等灌水量(W_2)有利于提高燕麦的生产效能,对盐分累积的控制效果较好。展开更多
Although many sensitivity analyses using the soil and water assessment tool(SWAT) in a complex watershed have been conducted, little attention has been paid to the application potential of the model in unique plots. I...Although many sensitivity analyses using the soil and water assessment tool(SWAT) in a complex watershed have been conducted, little attention has been paid to the application potential of the model in unique plots. In addition, sensitivity analysis of percolation and evapotranspiration with SWAT has seldom been undertaken. In this study, SWAT99.2 was calibrated to simulate water balance components for unique plots in Southern China from 2000 to 2001, which included surface runoff, percolation, and evapotranspiration. Twenty-one parameters classified into four categories, including meteorological conditions, topographical characteristics, soil properties, and vegetation attributes, were used for sensitivity analysis through one-at-a-time(OAT) sampling to identify the factor that contributed most to the variance in water balance components. The results were shown to be different for different plots, with parameter sensitivity indices and ranks varying for different water balance components. Water balance components in the broad-leaved forest and natural grass plots were most sensitive to meteorological conditions, less sensitive to vegetation attributes and soil properties, and least sensitive to topographical characteristics. Compared to those in the natural grass plot, water balance components in the broad-leaved forest plot demonstrated higher sensitivity to the maximum stomatal conductance(GSI) and maximum leaf area index(BLAI).展开更多
灌区水资源优化配置中存在众多不确定性因素,而考虑不确定性因素的优化模型往往存在结构复杂、不确定性参数考虑有限、计算精度和效率较低等问题。本文将LH-OAT(Latin hypercube-One factor at a time)方法与灌区用水优化模型耦合,构建...灌区水资源优化配置中存在众多不确定性因素,而考虑不确定性因素的优化模型往往存在结构复杂、不确定性参数考虑有限、计算精度和效率较低等问题。本文将LH-OAT(Latin hypercube-One factor at a time)方法与灌区用水优化模型耦合,构建了灌区用水优化模型参数敏感性分析与不确定性优化方法,并以黑河流域中游典型灌区为案例研究区,对模型中6类共25个不确定性参数进行了全局敏感性分析。计算获得了模型中25个不确定性参数的敏感度排序,并从中筛选出10个高敏感性参数,以高敏感性参数作为优化模型不确定性参数输入,获得了不确定性下的灌区用水优化结果。案例分析表明,该方法有效筛选出优化模型中高敏感的关键参数,综合考虑了不确定性参数对模型优化结果的影响,大大减少了模型不确定性参数的表征数量,降低了模型复杂性,有效提高了模型计算效率,可为灌区水资源优化配置问题提供方法参考。展开更多
[目的]探究不同年型下饲用燕麦产量对各生育期降水变化的响应,为饲用燕麦抗旱与高效生产提供参考。[方法]利用作物生长机理模型APSIM(agricultural production systems simulator),以山西省朔州市右玉县1980—2009年的历史气候气象数据...[目的]探究不同年型下饲用燕麦产量对各生育期降水变化的响应,为饲用燕麦抗旱与高效生产提供参考。[方法]利用作物生长机理模型APSIM(agricultural production systems simulator),以山西省朔州市右玉县1980—2009年的历史气候气象数据作为原始情景,将饲用燕麦生育期划分为4个阶段[阶段1(播种—拔节)、阶段2(拔节—抽穗)、阶段3(抽穗—灌浆)、阶段4(灌浆—收获)],并提取典型气候条件(干旱、平水、丰水)建立12个新的气候情景并进行模拟,分析饲用燕麦产量受降水变化的影响。[结果]在干旱情景(DS)中,产量与水分利用效率(water use efficiency,WUE)较原始情景分别下降了38.0%~60.9%与31.8%~16.9%(P<0.01),其中,抽穗—灌浆期采用历史数据时,指标的下降幅度最小。对于平水情景(NS)来说,产量相对原始情景的变化为-3.4%~20.0%,WUE为0~10.0%,拔节—抽穗期及灌浆—收获期采用历史数据时指标的变化显著(P<0.05)。丰水情景(WS)中,饲用燕麦产量与WUE相对原始情景均显著提升(P<0.01),幅度分别达到33.3%~60.5%与6.8%~14.8%,且播种—拔节期的降水变化对指标有相对明显的影响(R^(2)=0.3777,P<0.01)。[结论]饲用燕麦产草量和水分利用效率WUE在干旱、平水、丰水年型中都对灌浆—收获期的降水变化没有明显的敏感性;在干旱和平水年型下,饲草产量对抽穗—灌浆期的干旱更为敏感,WUE则对拔节—抽穗期及抽穗—灌浆期的干旱更为敏感;在丰水年型下,燕麦饲草产量对干旱最敏感的时期是播种—拔节期。有限的灌溉条件下,可将灌溉集中于WUE对降水变化最为敏感的阶段3(抽穗—灌浆)。展开更多
文摘Spring oat (Avena sativa) is produced for grain, hay, and green manure and can be integrated into a cropping system as a cover crop. Twenty-eight oat genotypes (G1, G2, G3, …., G28), selected for their adaptability to the Southwestern United States, were evaluated for their yield performance under sprinkler irrigation during four growing seasons (2005-2008) at the Agricultural Science Center at Farmington, New Mexico State University. The genotypes were arranged in randomized complete blocs design with four replications. Irrigation scheduling was based on evapotranspiration and the depletion criterion of 40% to 45% total available water (TAW) was practiced to prevent the plants from experiencing any water stress. Crop evapotranspiration estimated by the FAO crop coefficient and reference evapotranspiration approach was low about 2 mm/day during crop initial stage and increased with plant growth and reached the maximum during crop mid-season or reproductive stage. It decreased during crop late season. Daily crop evapotranspiration varied from 0.5 to 12.6 mm in 2008 and the seasonal Spring oat evapotranspiration varied from 535.8 to 591 mm. Averaged across the four growing seasons, oat evapotranspiration was 570.4 mm. The results showed that Spring oat plant height varied significantly with genotypes and ranged from 59.1 to 100.8 cm. Oat grain yield significantly varied with years and genotypes. Grain yield varied from 3386 to 6498 kg/ha and average yield was 4245, 4265, 5477, and 4025 kg/ha during the 2005, 2006, 2007 and 2008, respectively. The best performing genotypes were G1, G2, G7, G19, G20, G21 and G23 with average yield greater than 4800 kg/ha while G3, G13, G17 and G27 showed the lowest yield among the genotypes. Oat crop water use efficiency (CWUE) varied with genotype and years and ranged from 0.53 to 1.07 kg/m3 and averaged 0.65, 0.78, 0.91 and 0.70 kg/m3 in 2005, 2006, 2007 and 2008, respectively. The highest CWUE was achieved by G19 and the lowest CWUE was obtained by G13. Irrigation water use efficiency (IWUE) which represents the quantity of yield produced per cubic meter of water, varied from 0.57 to 1.20 kg/m3 while evapotranspiration water use efficiency (ETWUE) varied with genotype and year and ranged from 0.57 to 1.21 kg/m3 with the overall IWUE mean of 0.83 kg/m3 and ETWUE mean of 0.81 kg/m3.
文摘Soybean hulls, an abundant byproduct of soybean processing, contain rich phytochemicals, fibers, proteins, and minerals. Currently soybean hulls are primarily used as animal feeds. For value-added soybean hull utilization, 25% soybean hulls were substituted for amaranth or whole oat flour (WOF) in novel gluten-free cookies. Composition, nutritional values, water-holding capacities, correlation between properties, and pasting and rheological properties of soybean hulls, amaranth, and WOF were appraised in comparison to wheat flour. Water loss, cookie texture, and geometrical properties of the cookies were examined. The results disclosed that soybean hulls, amaranth and WOF contain higher protein content, minerals, fiber, special amino acids, and critical vitamins (C and K) than wheat flour. Considerably higher total amino acid content was found in soybean hulls (18.33%) than wheat flour (12.77%). Water-holding capacities increased by replacing amaranth and WOF with soybean hulls. Soybean hulls exhibited higher rheological elastic properties than amaranth, WOF and wheat flours. The soybean hulls utilized in amaranth or WOF cookies greatly improved their nutritional value, the water retention and moisture content along with acceptable physical properties when compared to wheat flour cookies. This study explored the feasibility and potential of utilizing soybean hulls with amaranth and WOF in gluten-free bakery products and other food applications.
文摘[目的]探究不同灌溉方式和灌水量对土壤水盐变化规律及燕麦生长特征的影响,为提高盐碱地作物的生产效能和土壤水分管理提供科学参考。[方法]采用盆栽试验,设置3种灌溉方式:常规灌溉、固定单侧灌溉(fixed unilateral root zone irrigation,FURI)、交替灌溉(alternative partial root zone irrigation,APRI),3组灌水量:W_1(60%θ_f~70%θ_f,θ_f为田间持水率),W_2(70%θ_f~80%θ_f)和W_3(80%θ_f~90%θ_f),以常规灌溉作为对照,共9组交互处理。[结果](1)不同灌溉方式下,土壤各层含水率变化趋势基本一致,随灌水量增加洗盐效果越显著,常规灌溉的深层含水率总体高于其他两种灌溉方式。(2)燕麦株高、叶绿素相对含量(relative chlorophyll content of leaves,SPAD)、品质随灌水量的增加而上升,与常规灌溉相比,W_2灌溉水平下,分根交替灌溉处理的粗脂肪,粗蛋白,β-葡聚糖含量分别增加7.02%,3.76%,6.06%,但降低了燕麦叶片的SPAD值,影响其光合能力。(3)随着燕麦生育期的推进,土壤盐分均呈现不同程度的累积,分根交替灌溉的积盐率最低,同时对燕麦根系生长、水分利用效率及产量影响显著,其中根系总长、根系总表面积、根系总体积较相同灌水量(W_2)的常规灌溉分别增加6.75%,6.92%,12.5%,水分利用效率提高17.32%。[结论]采用分根交替灌溉方式下的中等灌水量(W_2)有利于提高燕麦的生产效能,对盐分累积的控制效果较好。
基金supported by the National Natural Science Foundation of China(Grants No.51569007 and 41301289)the Natural Science Foundation of Guangxi Province,China(Grant No.2015GXNSFCA139004)+1 种基金the Fund of the IRCK by UNESCO(Grant No.KDL201601)the Project of High Level Innovation Team and Outstanding Scholar in Guangxi Colleges and Universities(Grant No.002401013001)
文摘Although many sensitivity analyses using the soil and water assessment tool(SWAT) in a complex watershed have been conducted, little attention has been paid to the application potential of the model in unique plots. In addition, sensitivity analysis of percolation and evapotranspiration with SWAT has seldom been undertaken. In this study, SWAT99.2 was calibrated to simulate water balance components for unique plots in Southern China from 2000 to 2001, which included surface runoff, percolation, and evapotranspiration. Twenty-one parameters classified into four categories, including meteorological conditions, topographical characteristics, soil properties, and vegetation attributes, were used for sensitivity analysis through one-at-a-time(OAT) sampling to identify the factor that contributed most to the variance in water balance components. The results were shown to be different for different plots, with parameter sensitivity indices and ranks varying for different water balance components. Water balance components in the broad-leaved forest and natural grass plots were most sensitive to meteorological conditions, less sensitive to vegetation attributes and soil properties, and least sensitive to topographical characteristics. Compared to those in the natural grass plot, water balance components in the broad-leaved forest plot demonstrated higher sensitivity to the maximum stomatal conductance(GSI) and maximum leaf area index(BLAI).
文摘灌区水资源优化配置中存在众多不确定性因素,而考虑不确定性因素的优化模型往往存在结构复杂、不确定性参数考虑有限、计算精度和效率较低等问题。本文将LH-OAT(Latin hypercube-One factor at a time)方法与灌区用水优化模型耦合,构建了灌区用水优化模型参数敏感性分析与不确定性优化方法,并以黑河流域中游典型灌区为案例研究区,对模型中6类共25个不确定性参数进行了全局敏感性分析。计算获得了模型中25个不确定性参数的敏感度排序,并从中筛选出10个高敏感性参数,以高敏感性参数作为优化模型不确定性参数输入,获得了不确定性下的灌区用水优化结果。案例分析表明,该方法有效筛选出优化模型中高敏感的关键参数,综合考虑了不确定性参数对模型优化结果的影响,大大减少了模型不确定性参数的表征数量,降低了模型复杂性,有效提高了模型计算效率,可为灌区水资源优化配置问题提供方法参考。
文摘[目的]探究不同年型下饲用燕麦产量对各生育期降水变化的响应,为饲用燕麦抗旱与高效生产提供参考。[方法]利用作物生长机理模型APSIM(agricultural production systems simulator),以山西省朔州市右玉县1980—2009年的历史气候气象数据作为原始情景,将饲用燕麦生育期划分为4个阶段[阶段1(播种—拔节)、阶段2(拔节—抽穗)、阶段3(抽穗—灌浆)、阶段4(灌浆—收获)],并提取典型气候条件(干旱、平水、丰水)建立12个新的气候情景并进行模拟,分析饲用燕麦产量受降水变化的影响。[结果]在干旱情景(DS)中,产量与水分利用效率(water use efficiency,WUE)较原始情景分别下降了38.0%~60.9%与31.8%~16.9%(P<0.01),其中,抽穗—灌浆期采用历史数据时,指标的下降幅度最小。对于平水情景(NS)来说,产量相对原始情景的变化为-3.4%~20.0%,WUE为0~10.0%,拔节—抽穗期及灌浆—收获期采用历史数据时指标的变化显著(P<0.05)。丰水情景(WS)中,饲用燕麦产量与WUE相对原始情景均显著提升(P<0.01),幅度分别达到33.3%~60.5%与6.8%~14.8%,且播种—拔节期的降水变化对指标有相对明显的影响(R^(2)=0.3777,P<0.01)。[结论]饲用燕麦产草量和水分利用效率WUE在干旱、平水、丰水年型中都对灌浆—收获期的降水变化没有明显的敏感性;在干旱和平水年型下,饲草产量对抽穗—灌浆期的干旱更为敏感,WUE则对拔节—抽穗期及抽穗—灌浆期的干旱更为敏感;在丰水年型下,燕麦饲草产量对干旱最敏感的时期是播种—拔节期。有限的灌溉条件下,可将灌溉集中于WUE对降水变化最为敏感的阶段3(抽穗—灌浆)。
