Sugar beet（Beta vulgaris L.） is an industrial crop, grown worldwide for sugar production. In Pakistan, sugar is mostly extracted from sugarcane, soil and environmental conditions are equally favorable for sugar beet...Sugar beet（Beta vulgaris L.） is an industrial crop, grown worldwide for sugar production. In Pakistan, sugar is mostly extracted from sugarcane, soil and environmental conditions are equally favorable for sugar beet cultivation. Beet sugar contents are higher than sugarcane sugar contents, which can be further increased by potassium（K） fertilization. Total K concentration is higher in Pakistani soils developed from mica minerals, but it does not represent plant available K for sustainable plant growth. A pot experiment was conducted in the wire-house of Institute of Soil and Environmental Sciences at University of Agriculture Faisalabad, Pakistan. K treatments were the following： no K（K_0）, K application at 148 kg ha^（–1）（K_1） and 296 kg ha^（–1）（K_2）. Irrigation levels were used as water sufficient at 60% water holding capacity and water deficient at 40% water holding capacity. The growth, yield and beet quality data were analyzed statistically using LSD. The results revealed that increase in the level of K fertilization at water sufficient level significantly increased plant growth, beet yield and industrial beet sugar content. The response of K fertilization under water deficient condition was also similar, however overall sugar production was less than that in water sufficient conditions. It is concluded from this study that K application could be used not only to enhance plant growth and beet yield but also enhance beet sugar content both under water-deficient as well as water-sufficient conditions.展开更多
Accurate pre-harvest prediction of sugar beet yield is vital for effective agricultural management and decision-making.However,traditional methods are constrained by reliance on empirical knowledge,time-consuming proc...Accurate pre-harvest prediction of sugar beet yield is vital for effective agricultural management and decision-making.However,traditional methods are constrained by reliance on empirical knowledge,time-consuming processes,resource intensiveness,and spatial-temporal variability in prediction accuracy.This study presented a plot-level approach that leverages UAV technology and recurrent neural networks to provide field yield predictions within the same growing season,addressing a significant gap in previous research that often focuses on regional scale predictions relied on multi-year history datasets.End-of-season yield and quality parameters were forecasted using UAV-derived time series data and meteorological factors collected at three critical growth stages,providing a timely and practical tool for farm management.Two years of data covering 185 sugar beet varieties were used to train a developed stacked Long Short-Term Memory(LSTM)model,which was compared with traditional machine learning approaches.Incorporating fresh weight estimates of aboveground and root biomass as predictive factors significantly enhanced prediction accuracy.Optimal performance in prediction was observed when utilizing data from all three growth periods,with R^(2)values of 0.761(rRMSE=7.1%)for sugar content,0.531(rRMSE=22.5%)for root yield,and 0.478(rRMSE=23.4%)for sugar yield.Furthermore,combining data from the first two growth periods shows promising results for making the predictions earlier.Key predictive features identified through the Permutation Importance(PIMP)method provided insights into the main factors influencing yield.These findings underscore the potential of using UAV time-series data and recurrent neural networks for accurate pre-harvest yield prediction at the field scale,supporting timely and precise agricultural decisions.展开更多
Tolerance of carrot and red beet to s-metolachlor at three application timings—pre-emergence to crop (PRE), early postemergence (crop at two to four leaf stage-EPOST), and late postemergence (crop at five to seven le...Tolerance of carrot and red beet to s-metolachlor at three application timings—pre-emergence to crop (PRE), early postemergence (crop at two to four leaf stage-EPOST), and late postemergence (crop at five to seven leaf stage-LPOST) —was determined from 2008 to 2010. LPOST applications of s-metolachlor reduced carrot above ground plant dry weight, marketable yield and grower payment, but did not affect carrot length. PRE and LPOST applications of s-metolachlor reduced red beet above ground plant dry weight, total marketable yield, yield of No. 2 and No. 3 red beet, and grower payment. Our findings indicate that while carrot may be tolerant to PRE applications of s-metolachlor, applications made after the 5 leaf stage reduced plant dry weight enough to impact marketable yield and grower payment. In red beet, the potential reduction in growth, yield and grade would not justify the utility of a PRE or LPOST applica- tion timing.展开更多
Nowadays the dye lasers play as an important tool and are used in many applications including spectroscopy, medicine and dermatology. This research was carried out to study the possibility of using the beet dyes as a ...Nowadays the dye lasers play as an important tool and are used in many applications including spectroscopy, medicine and dermatology. This research was carried out to study the possibility of using the beet dyes as a laser gain medium. The fluorescence quantum yield was determined by the comparative method with rodamine b as an organic dye standard. The value of the fluorescence quantum yield was found about (0.14) and the fluorescence quantum yield was developed until reaching about (0.323). The increasing of fluorescence quantum yield of dye solution as a result of increasing the viscosity of solvent was observed clearly. The study concluded that the beet dyes are so sensitive to fluorescence and it is very suitable to be used as a laser gain medium.展开更多
The experiment of glutamate synthase activity (GOGATA) in both leaf blades and roots under different nitrogen levels was carried out at Northeast Agricultural University in 1993. The result showed that GOGATA rose rap...The experiment of glutamate synthase activity (GOGATA) in both leaf blades and roots under different nitrogen levels was carried out at Northeast Agricultural University in 1993. The result showed that GOGATA rose rapidly to reach its peak from seedling stage to foliage rapid growth stage, and then declined gradually. GOGATA was enhanced with increasing nitrogen levels and had significant positive correlation with nitrogen levels at the middle stage of growth GOGATA in leaf blades was the strongest compared with crowns, petioles and roots, thus, it could represent the highest enzyme activity of the whole plant. GOGATA had quadratic curvilinear correlation with root yield and sugar production. GOGATA in leaf blades had significant positive correlation with α-NH 2-N at the foliage rapid growth stage while GOGATA in roots existed this relation at the latter stage of growth. GOGATA in roots had significant negative correlation with sugar content at harvest.展开更多
文摘Sugar beet（Beta vulgaris L.） is an industrial crop, grown worldwide for sugar production. In Pakistan, sugar is mostly extracted from sugarcane, soil and environmental conditions are equally favorable for sugar beet cultivation. Beet sugar contents are higher than sugarcane sugar contents, which can be further increased by potassium（K） fertilization. Total K concentration is higher in Pakistani soils developed from mica minerals, but it does not represent plant available K for sustainable plant growth. A pot experiment was conducted in the wire-house of Institute of Soil and Environmental Sciences at University of Agriculture Faisalabad, Pakistan. K treatments were the following： no K（K_0）, K application at 148 kg ha^（–1）（K_1） and 296 kg ha^（–1）（K_2）. Irrigation levels were used as water sufficient at 60% water holding capacity and water deficient at 40% water holding capacity. The growth, yield and beet quality data were analyzed statistically using LSD. The results revealed that increase in the level of K fertilization at water sufficient level significantly increased plant growth, beet yield and industrial beet sugar content. The response of K fertilization under water deficient condition was also similar, however overall sugar production was less than that in water sufficient conditions. It is concluded from this study that K application could be used not only to enhance plant growth and beet yield but also enhance beet sugar content both under water-deficient as well as water-sufficient conditions.
基金supported by the Science and Technology projects Inner Mongolia(Grant No.2019ZD024)National Center of Pratacultural Technology Innovation(under preparation)Special fund for innovation platform construction(CCPTZX2023K03).
文摘Accurate pre-harvest prediction of sugar beet yield is vital for effective agricultural management and decision-making.However,traditional methods are constrained by reliance on empirical knowledge,time-consuming processes,resource intensiveness,and spatial-temporal variability in prediction accuracy.This study presented a plot-level approach that leverages UAV technology and recurrent neural networks to provide field yield predictions within the same growing season,addressing a significant gap in previous research that often focuses on regional scale predictions relied on multi-year history datasets.End-of-season yield and quality parameters were forecasted using UAV-derived time series data and meteorological factors collected at three critical growth stages,providing a timely and practical tool for farm management.Two years of data covering 185 sugar beet varieties were used to train a developed stacked Long Short-Term Memory(LSTM)model,which was compared with traditional machine learning approaches.Incorporating fresh weight estimates of aboveground and root biomass as predictive factors significantly enhanced prediction accuracy.Optimal performance in prediction was observed when utilizing data from all three growth periods,with R^(2)values of 0.761(rRMSE=7.1%)for sugar content,0.531(rRMSE=22.5%)for root yield,and 0.478(rRMSE=23.4%)for sugar yield.Furthermore,combining data from the first two growth periods shows promising results for making the predictions earlier.Key predictive features identified through the Permutation Importance(PIMP)method provided insights into the main factors influencing yield.These findings underscore the potential of using UAV time-series data and recurrent neural networks for accurate pre-harvest yield prediction at the field scale,supporting timely and precise agricultural decisions.
文摘Tolerance of carrot and red beet to s-metolachlor at three application timings—pre-emergence to crop (PRE), early postemergence (crop at two to four leaf stage-EPOST), and late postemergence (crop at five to seven leaf stage-LPOST) —was determined from 2008 to 2010. LPOST applications of s-metolachlor reduced carrot above ground plant dry weight, marketable yield and grower payment, but did not affect carrot length. PRE and LPOST applications of s-metolachlor reduced red beet above ground plant dry weight, total marketable yield, yield of No. 2 and No. 3 red beet, and grower payment. Our findings indicate that while carrot may be tolerant to PRE applications of s-metolachlor, applications made after the 5 leaf stage reduced plant dry weight enough to impact marketable yield and grower payment. In red beet, the potential reduction in growth, yield and grade would not justify the utility of a PRE or LPOST applica- tion timing.
文摘Nowadays the dye lasers play as an important tool and are used in many applications including spectroscopy, medicine and dermatology. This research was carried out to study the possibility of using the beet dyes as a laser gain medium. The fluorescence quantum yield was determined by the comparative method with rodamine b as an organic dye standard. The value of the fluorescence quantum yield was found about (0.14) and the fluorescence quantum yield was developed until reaching about (0.323). The increasing of fluorescence quantum yield of dye solution as a result of increasing the viscosity of solvent was observed clearly. The study concluded that the beet dyes are so sensitive to fluorescence and it is very suitable to be used as a laser gain medium.
文摘The experiment of glutamate synthase activity (GOGATA) in both leaf blades and roots under different nitrogen levels was carried out at Northeast Agricultural University in 1993. The result showed that GOGATA rose rapidly to reach its peak from seedling stage to foliage rapid growth stage, and then declined gradually. GOGATA was enhanced with increasing nitrogen levels and had significant positive correlation with nitrogen levels at the middle stage of growth GOGATA in leaf blades was the strongest compared with crowns, petioles and roots, thus, it could represent the highest enzyme activity of the whole plant. GOGATA had quadratic curvilinear correlation with root yield and sugar production. GOGATA in leaf blades had significant positive correlation with α-NH 2-N at the foliage rapid growth stage while GOGATA in roots existed this relation at the latter stage of growth. GOGATA in roots had significant negative correlation with sugar content at harvest.
