Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Jean Mianikpo Sogbedji is active.

Publication


Featured researches published by Jean Mianikpo Sogbedji.


Plant and Soil | 2006

Evaluation of the PNM model for simulating drain flow nitrate-N concentration under manure-fertilized maize

Jean Mianikpo Sogbedji; Harold M. van Es; Jeff Melkonian; Robert R. Schindelbeck

Mathematical models may be used to develop management strategies that optimize the use of nutrients from complex sources such as manure in agriculture. The Precision Nitrogen Management (PNM) model is based on the LEACHN model and a maize N uptake/growth and yield model and focuses on developing more precise N management recommendations. The PNM model was evaluated for simulating drain flow nitrate-nitrogen (NO3-N) in a 3-yr study involving different times of liquid manure application on two soil textural extremes, a clay loam and a loamy sand under maize (Zea mays, L.) production. The model was calibrated for major N transformation rate constants including mineralization, nitrification and denitrification, and its performance was tested using two different calibration scenarios with increasing levels of generalization: (i) separate sets of rate constants for each individual soil type and (ii) a single set of rate constants for both soil types. When calibrated for each manure application treatment for each soil type, the model provided good simulations of monthly and seasonal drain flow NO3-N concentrations. The correlation coefficient (r) and Willmott’s index of agreement (d) ranged from 0.63 to 0.96 and 0.72 to 0.92, respectively. The calibrated model performed reasonably well when rate constant values averaged over manure application treatment for each soil type were used, with r and d values between 0.54 and 0.97, and 0.70 and 0.94, respectively, and greater accuracy for the clay loam soil. When rate constant values were averaged over manure application treatments and soil types, model performance was reasonably accurate for the fall time manure application on the clay loam (r and d of 0.60 and 0.91 and 0.72 and 0.92, respectively) and satisfactory for the spring time on the clay loam and the fall and spring times for the loamy sand soil (r and d between 0.56 and 0.90 and 0.58 and 0.84, respectively). The use of the model for predicting N dynamics under manure-fertilized maize cropping appears promising.


IOSR Journal of Agriculture and Veterinary Science | 2017

Land Degradation and Climate Change Resilient Soil and Crop Management Strategies for Maize Production in Coastal Western Africa

Jean Mianikpo Sogbedji; Kodjovi Sotomè Detchinli; Mihikouwè Mazinagou; Ruth Atchoglo; Komi Agbémébia Bona

A 2-yr (four cropping seasons) trial was conducted with nine maize (Zea mays L.) varieties and four fertilization treatments in three replicates to determine the appropriate variety-fertilization combinations. Fertilization treatments were: no fertilization (T1), 6 t ha -1 of farmyard manure (FYM) (T2), the national recommendation of 200 kg N15P15K15 plus 100 kg urea (46% N) ha -1 (T3) and 3 t of FYM plus 100 kg N15P15K15 plus 50 kg urea ha -1 (T4). Across fertilization treatments, 2-yr average grain yields were highest (6.41 to 6.76 t ha -1 ) for Bassar, TZEE and Obatampa varieties and lowest (4.63 and 5.07 t ha -1 ) for Wahala3 and Agoèbli in the first cropping season. TZEE, Dapaong, Obatampa and Bassar performed better (4.0 to 4.39 t ha -1 ) during the second season. Across varieties, grain yields for T4, T3 and T2 increased by 92 to 58, 69 to 42 and 57 to 34% in comparison with T1, respectively, those under T4 and T3 were 22.6 to 18 and 8 to 6% higher than that for T2, respectively, and the yield for T4 was 11 to 13.5% superior over that for T3. Fertilization treatment T4 proved suitable for improved grain yield and five varieties were no more recommended for the second cropping season.


Journal of Environmental Quality | 2000

Nitrate leaching and nitrogen budget as affected by maize nitrogen rate and soil type.

Jean Mianikpo Sogbedji; Harold M. van Es; Charissa L. Yang; Larry D. Geohring; Fred R. Magdoff


Journal of Environmental Quality | 2006

Effect of manure application timing, crop, and soil type on nitrate leaching.

Harold M. van Es; Jean Mianikpo Sogbedji; Robert R. Schindelbeck


Agronomy Journal | 2006

Cover cropping and nutrient management strategies for maize production in western Africa

Jean Mianikpo Sogbedji; H.M. van Es; K. L. Agbeko


Plant and Soil | 2010

Carbon losses and primary productivity decline in savannah soils under cotton-cereal rotations in semiarid Togo

K. Kintché; H. Guibert; Jean Mianikpo Sogbedji; Jean Lévêque; Pablo Tittonell


Nutrient Cycling in Agroecosystems | 2006

Modeling nitrogen dynamics under maize on ferralsols in Western Africa

Jean Mianikpo Sogbedji; Harold M. van Es; Kofi L. Agbeko


American Journal of Agriculture and Forestry | 2014

Assessment of the Profitability and the Effects of Three Maize-Based Cropping Systems on Soil Health in Western Africa

Kodjovi Sotomè Detchinli; Jean Mianikpo Sogbedji


Journal of Plant Sciences | 2015

Sustaining Improved Cassava Production on West African Ferralsols Through Appropriate Varieties and Optimal Potassium Fertilization Schemes

Jean Mianikpo Sogbedji; Lakpo Kokou Agboyi; Kodjovi Sotomè Detchinli; Ruth Atchoglo; Mihikouwè Mazinagou


European Scientific Journal, ESJ | 2015

YIELD PERFORMANCE AND ECONOMIC RETURN OF MAIZE AS AFFECTED BY NUTRIENT MANAGEMENT STRATEGIES ON FERRALSOLS IN COASTAL WESTERN AFRICA

K. S. Detchinli; Jean Mianikpo Sogbedji

Collaboration


Dive into the Jean Mianikpo Sogbedji's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Wilson A. Agyare

Kwame Nkrumah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge