Switchgrass (Panicum virgatum L.) is a native warm-season grass and it is one of potential bioenergy crops. The objectives of this study were to: 1) assess the best performing switchgrass genotype suitable for Kansas ...Switchgrass (Panicum virgatum L.) is a native warm-season grass and it is one of potential bioenergy crops. The objectives of this study were to: 1) assess the best performing switchgrass genotype suitable for Kansas soil and climatic condition in the USA, 2) determine the correlation between plant height or tiller numbers per plant and dry biomass of various switchgrass genotypes, and 3) assess a bioconversion efficiency of certain varieties of switchgrass. Twenty-two different genotypes of seedlings were allowed to grow in cones for 30 days under controlled environments. The genotype Cave-in-Rock was the shortest among the genotypes. Significant difference in number of tillers per plant was observed among the genotypes. The genotypes Alamo recorded the highest numbers of tiller plant-1 and the genotype Cave-in-Rock had the lowest numbers of tiller plant-1 compared with other genotypes. The genotypes Alamo, NL 94 C2-2, NL 94 C2-3, NSL 2009-1 and NSL 2009-2 had increased above ground biomass compared with other genotypes. The correlation study indicates that there was a significant positive correlation between number of tillers per plant and per plant dry weight (R2 = 0.93), number of tillers per plant and plant height (R2 = 0.94), and plant height and per plant dry weight (R2 = 0.82). Based on the biomass composition, the SWG 2007-2 genotype was the promising switchgrass line for the bioconversion through the sugar platform route due to high carbohydrate and low lignin content. On the other hand, the high biomass yield per unit area of field in NL 94 C2-1 led this genotype with the highest total carbohydrate yield per unit area of field despite the lowest total carbohydrate content in the genotype. These results are pertinent for crop breeders to develop the most promising switchgrass line with high biomass yield and high bioconversion efficiency to produce biofuel through the sugar platform route.展开更多
Nitrogen concentration in the ear leaf is a good indicator of corn (Zea mays L.) N nutrition status during late growing season. This study was done to examine the relationship of late-season ear leaf N concentration w...Nitrogen concentration in the ear leaf is a good indicator of corn (Zea mays L.) N nutrition status during late growing season. This study was done to examine the relationship of late-season ear leaf N concentration with early- to mid- season plant height of corn at Milan, TN from 2008 to 2010 using linear, quadratic, square root, logarithmic, and exponential models. Six N rate treatments (0, 62, 123, 185, 247, and 308 kg·N·ha-1) repeated four times were implemented each year in a randomized complete block design under four major cropping systems: corn after corn, corn after soybean [Glycine max (L.) Merr.], corn after cotton [Gossypium hirsutum (L.)], and irrigated corn after soybean. The relationship of ear leaf N concentration determined at the blister growth stage (R2) with plant height measured at the 6-leaf (V6), 10-leaf (V10), and 12-leaf (V12) growth stages was statistically significant and positive in non-irrigated corn under normal weather conditions. However, the strength of this relationship was weak to moderate with the determination coefficient (R2) values ranging from 0.21 to 0.51. This relationship was generally improved as the growing season progressed from V6 to V12. Irrigation and abnormal weather seemed to have adverse effects on this relationship. The five regression models performed similarly in the evaluation of this relationship regardless of growth stage, year, and cropping system. Our results suggest that unlike the relationship of corn yield at harvest with plant height measured during early- to mid-season or the relationship of leaf N concentration with plant height when both are measured simultaneously during early- to mid-season, the relationship of late-season ear leaf N concentration with early- to mid-season plant height may not be strong enough to be used to develop algorithms for variable-rate N applications on corn within a field no matter which regression model is used to describe this relationship.展开更多
文摘Switchgrass (Panicum virgatum L.) is a native warm-season grass and it is one of potential bioenergy crops. The objectives of this study were to: 1) assess the best performing switchgrass genotype suitable for Kansas soil and climatic condition in the USA, 2) determine the correlation between plant height or tiller numbers per plant and dry biomass of various switchgrass genotypes, and 3) assess a bioconversion efficiency of certain varieties of switchgrass. Twenty-two different genotypes of seedlings were allowed to grow in cones for 30 days under controlled environments. The genotype Cave-in-Rock was the shortest among the genotypes. Significant difference in number of tillers per plant was observed among the genotypes. The genotypes Alamo recorded the highest numbers of tiller plant-1 and the genotype Cave-in-Rock had the lowest numbers of tiller plant-1 compared with other genotypes. The genotypes Alamo, NL 94 C2-2, NL 94 C2-3, NSL 2009-1 and NSL 2009-2 had increased above ground biomass compared with other genotypes. The correlation study indicates that there was a significant positive correlation between number of tillers per plant and per plant dry weight (R2 = 0.93), number of tillers per plant and plant height (R2 = 0.94), and plant height and per plant dry weight (R2 = 0.82). Based on the biomass composition, the SWG 2007-2 genotype was the promising switchgrass line for the bioconversion through the sugar platform route due to high carbohydrate and low lignin content. On the other hand, the high biomass yield per unit area of field in NL 94 C2-1 led this genotype with the highest total carbohydrate yield per unit area of field despite the lowest total carbohydrate content in the genotype. These results are pertinent for crop breeders to develop the most promising switchgrass line with high biomass yield and high bioconversion efficiency to produce biofuel through the sugar platform route.
文摘Nitrogen concentration in the ear leaf is a good indicator of corn (Zea mays L.) N nutrition status during late growing season. This study was done to examine the relationship of late-season ear leaf N concentration with early- to mid- season plant height of corn at Milan, TN from 2008 to 2010 using linear, quadratic, square root, logarithmic, and exponential models. Six N rate treatments (0, 62, 123, 185, 247, and 308 kg·N·ha-1) repeated four times were implemented each year in a randomized complete block design under four major cropping systems: corn after corn, corn after soybean [Glycine max (L.) Merr.], corn after cotton [Gossypium hirsutum (L.)], and irrigated corn after soybean. The relationship of ear leaf N concentration determined at the blister growth stage (R2) with plant height measured at the 6-leaf (V6), 10-leaf (V10), and 12-leaf (V12) growth stages was statistically significant and positive in non-irrigated corn under normal weather conditions. However, the strength of this relationship was weak to moderate with the determination coefficient (R2) values ranging from 0.21 to 0.51. This relationship was generally improved as the growing season progressed from V6 to V12. Irrigation and abnormal weather seemed to have adverse effects on this relationship. The five regression models performed similarly in the evaluation of this relationship regardless of growth stage, year, and cropping system. Our results suggest that unlike the relationship of corn yield at harvest with plant height measured during early- to mid-season or the relationship of leaf N concentration with plant height when both are measured simultaneously during early- to mid-season, the relationship of late-season ear leaf N concentration with early- to mid-season plant height may not be strong enough to be used to develop algorithms for variable-rate N applications on corn within a field no matter which regression model is used to describe this relationship.
