Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperatur...Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperature, and precipitation will affect grain protein contents and these factors usually cannot be monitored accurately by remote sensing data from single image. In this research, the relationships between wheat protein content at maturity and wheat agronomic parameters at different growing stages were analyzed and multi-temporal images of Landsat TM were used to estimate grain protein content by partial least squares regression. Experiment data were acquired in the suburb of Beijing during a 2-yr experiment in the period from 2003 to 2004. Determination coefficient, average deviation of self-modeling, and deviation of cross- validation were employed to assess the estimation accuracy of wheat grain protein content. Their values were 0.88, 1.30%, 3.81% and 0.72, 5.22%, 12.36% for 2003 and 2004, respectively. The research laid an agronomic foundation for GPC （grain protein content） estimation by multi-temporal remote sensing. The results showed that it is feasible to estimate GPC of wheat from multi-temporal remote sensing data in large area.展开更多
The study was carried out to assess the effect of management practices on agronomic parameters of cocoa agroecosystems in the peripheral zone of Ebo Forest Reserve. Purposive random sampling was conducted to establish...The study was carried out to assess the effect of management practices on agronomic parameters of cocoa agroecosystems in the peripheral zone of Ebo Forest Reserve. Purposive random sampling was conducted to establish experimental plots on the farms of willing farmers. Demonstration plots were established and agronomic parameters were monitored for “farmers’ practice (FP) and integrated crop pest and disease management (ICPM) practice” using indicators of Cocoa agro-ecosystem analysis (AESA). The FP and ICPM treatments were replicated in ten sites. From AESA records of agronomic parameters, the “observe, learn, decide and act” (OLDA) model was implemented in the ICPM treatments only. The effects of management practices were analyzed using a two-way analysis of variance (ANOVA), and treatment means compared using Turkey’s T-test at 5% probability. Results of ANOVA between the two Management practices showed that over 50% of the response variables were statistically significant. Means separated through GLM ANOVA with Tukey pairwise comparisons at α = 0.05 showed that 14 (53.8%) out of 26 response variables monitored were statistically significant between the two management practices. Pruning, shade management, phytosanitary harvest, rational use of pesticides, farm sanitation, pod harvesting, breaking, fermentation of beans and drying were regular in the ICPM treatment and time-bound in the FP treatment. The average total production varied from 385.83 kg/ha in FP treatment to 572.8 kg/ha in the ICPM treatment, still below the average standard of 1000 kg/ha. The OLDA model applied in ICPM treatment following AESA is a relevant tool to enhance sustainability in the management of cocoa agroecosystems. Farmers should be sensitized and trained on appropriate farm management techniques and enhance access to extension services as well as make available improved and grafted planting materials to ensure appropriate productivity levels.展开更多
Several studies conducted in recent years in Côte d’Ivoire reveal that agriculture is increasingly affected by the adverse effects of climate variability. The present study aims at evaluating the effect of t...Several studies conducted in recent years in Côte d’Ivoire reveal that agriculture is increasingly affected by the adverse effects of climate variability. The present study aims at evaluating the effect of the zone and the year of cultivation on the productivity of maize in the Central and North-Central zones of Cote d’Ivoire. It was carried out for two years (2020 and 2021). The experimental design used was a completely randomized block design with three replications. Observations were made on 12 agronomic parameters (plant size, internode size, collar diameter, number of leaves, number of internodes, cob insertion level, cob length, cob diameter, total kernels, cob dry weight, kernel dry weight, yield). The results showed that all agronomic traits of maize were significantly influenced by locality, except for the number of leaves. The highest values of the traits were observed in the locality of Bouaké. However, the year of cultivation did not influence the agronomic parameters of maize. This study will help to avoid yield decreases due to rainfall disturbances as a consequence of climate change.展开更多
Several methods have been developed in the literature which allow the maturity of composts to be assessed before it is used in agriculture. The objective of this study is to assess the maturity of the composts produce...Several methods have been developed in the literature which allow the maturity of composts to be assessed before it is used in agriculture. The objective of this study is to assess the maturity of the composts produced at the platform of the NGO ENPRO in Lomé on the growth and agronomic parameters of maize (<i>Zea mays</i> L., var. IKENE). To do so, three types of compost (gargabe, fruit waste, animal litter) were made for at least 3 months. The chemical analysis, phytotoxicity and agronomic tests carried out made it possible to assess the maturity of these composts. Indeed, the evolution of the C/N ratio, of the electrical conductivity, the phytotoxicity tests and the growth parameters of the composts show that the composts N°1 and N°2 are mature at the end of the 3<sup>rd</sup> month of composting while the compost N°3 can only be considered mature at the end of the 5<sup>th</sup> month of composting. But, with a yield of 2.39 ± 0.28 t/ha and a mass of 1000 grains of 346 ± 4 g, the treatment at 5 t/ha of compost N°3, has the best agronomic parameters compared to other types of compost and treatment without organic amendment. These results also show that compost with a high electrical conductivity has an inhibitory effect on the growth of corn plants (<i>Zea mays</i> L., var. IKENE). Basic chemical analysis, phytotoxicity tests and height growth of maize (<i>Zea mays</i> L., var. IKENE) are relatively efficient methods for evaluating the maturity of composts.展开更多
基金the National Natural Science Foundation of China (41171281, 40701120)the Beijing Nova Program, China (2008B33)
文摘Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperature, and precipitation will affect grain protein contents and these factors usually cannot be monitored accurately by remote sensing data from single image. In this research, the relationships between wheat protein content at maturity and wheat agronomic parameters at different growing stages were analyzed and multi-temporal images of Landsat TM were used to estimate grain protein content by partial least squares regression. Experiment data were acquired in the suburb of Beijing during a 2-yr experiment in the period from 2003 to 2004. Determination coefficient, average deviation of self-modeling, and deviation of cross- validation were employed to assess the estimation accuracy of wheat grain protein content. Their values were 0.88, 1.30%, 3.81% and 0.72, 5.22%, 12.36% for 2003 and 2004, respectively. The research laid an agronomic foundation for GPC （grain protein content） estimation by multi-temporal remote sensing. The results showed that it is feasible to estimate GPC of wheat from multi-temporal remote sensing data in large area.
文摘The study was carried out to assess the effect of management practices on agronomic parameters of cocoa agroecosystems in the peripheral zone of Ebo Forest Reserve. Purposive random sampling was conducted to establish experimental plots on the farms of willing farmers. Demonstration plots were established and agronomic parameters were monitored for “farmers’ practice (FP) and integrated crop pest and disease management (ICPM) practice” using indicators of Cocoa agro-ecosystem analysis (AESA). The FP and ICPM treatments were replicated in ten sites. From AESA records of agronomic parameters, the “observe, learn, decide and act” (OLDA) model was implemented in the ICPM treatments only. The effects of management practices were analyzed using a two-way analysis of variance (ANOVA), and treatment means compared using Turkey’s T-test at 5% probability. Results of ANOVA between the two Management practices showed that over 50% of the response variables were statistically significant. Means separated through GLM ANOVA with Tukey pairwise comparisons at α = 0.05 showed that 14 (53.8%) out of 26 response variables monitored were statistically significant between the two management practices. Pruning, shade management, phytosanitary harvest, rational use of pesticides, farm sanitation, pod harvesting, breaking, fermentation of beans and drying were regular in the ICPM treatment and time-bound in the FP treatment. The average total production varied from 385.83 kg/ha in FP treatment to 572.8 kg/ha in the ICPM treatment, still below the average standard of 1000 kg/ha. The OLDA model applied in ICPM treatment following AESA is a relevant tool to enhance sustainability in the management of cocoa agroecosystems. Farmers should be sensitized and trained on appropriate farm management techniques and enhance access to extension services as well as make available improved and grafted planting materials to ensure appropriate productivity levels.
文摘Several studies conducted in recent years in Côte d’Ivoire reveal that agriculture is increasingly affected by the adverse effects of climate variability. The present study aims at evaluating the effect of the zone and the year of cultivation on the productivity of maize in the Central and North-Central zones of Cote d’Ivoire. It was carried out for two years (2020 and 2021). The experimental design used was a completely randomized block design with three replications. Observations were made on 12 agronomic parameters (plant size, internode size, collar diameter, number of leaves, number of internodes, cob insertion level, cob length, cob diameter, total kernels, cob dry weight, kernel dry weight, yield). The results showed that all agronomic traits of maize were significantly influenced by locality, except for the number of leaves. The highest values of the traits were observed in the locality of Bouaké. However, the year of cultivation did not influence the agronomic parameters of maize. This study will help to avoid yield decreases due to rainfall disturbances as a consequence of climate change.
文摘Several methods have been developed in the literature which allow the maturity of composts to be assessed before it is used in agriculture. The objective of this study is to assess the maturity of the composts produced at the platform of the NGO ENPRO in Lomé on the growth and agronomic parameters of maize (<i>Zea mays</i> L., var. IKENE). To do so, three types of compost (gargabe, fruit waste, animal litter) were made for at least 3 months. The chemical analysis, phytotoxicity and agronomic tests carried out made it possible to assess the maturity of these composts. Indeed, the evolution of the C/N ratio, of the electrical conductivity, the phytotoxicity tests and the growth parameters of the composts show that the composts N°1 and N°2 are mature at the end of the 3<sup>rd</sup> month of composting while the compost N°3 can only be considered mature at the end of the 5<sup>th</sup> month of composting. But, with a yield of 2.39 ± 0.28 t/ha and a mass of 1000 grains of 346 ± 4 g, the treatment at 5 t/ha of compost N°3, has the best agronomic parameters compared to other types of compost and treatment without organic amendment. These results also show that compost with a high electrical conductivity has an inhibitory effect on the growth of corn plants (<i>Zea mays</i> L., var. IKENE). Basic chemical analysis, phytotoxicity tests and height growth of maize (<i>Zea mays</i> L., var. IKENE) are relatively efficient methods for evaluating the maturity of composts.
