The Decision Support System for Agrotechnology Transfert (DSSAT) is a software comprising crop simulation models. The aim of this study was to: Calibrate the CROPGRO-cowpea model of DSSAT for four cowpea varieties, and Validate the model using a data set collected under drought stress For this purpose, experiments were carried out in 2020 and 2021 dry seasons in Burkina Faso at Kamboinsin in the Centre of Environmental and Agricultural Research and Training (CREAF). The model calibration was done using data including days to 50% flowering, days to maturity, above-ground biomass, and grain yield per hectare collected from an experiment without water and nutrient stress, and the GenCalc software was used for estimating the genetic coefficients of the varieties. Data from two drought stress treatments, such as D1: drought at seedling stage, and D2: drought at flowering stage, were used for validating the model. The results of the calibration showed that the model excellently simulated the days to flowering with a normalized root mean square error (nRMSE) of less than 10% and a high degree of agreement for all the varieties. The simulation of the days to physiological maturity was excellent for 50% of the varieties (nRMSE<10%) and good for the others (10 < nRMSE < 20%). The simulation of the grain yield per hectare ranged from excellent to good. Poor prediction of the above-ground biomass was attained for 75% of the varieties (nRMSE ≥ 40%), while the fair simulation was recorded for 25% (nRMSE=27%) during the model calibration. The statistics of the validation process showed an excellent simulation of the days to flowering (nRMSE= 1.85%; R2=0.98; d-index=0.99) and a good prediction of the days to maturity (nRMSE=13.82; R2=0.87; d-index=0.53) for all the varieties. Simulated above-ground biomass was in poor agreement with the observed values (nRMSE=106.62%; R2=0.92; d-index=0.36). Fair prediction of the grain yield by the model was achieved during the validation (nRMSE = 27%). From these results, it can be concluded that the DSSAT model can be considered an efficient tool for predicting cowpea phenology, growth, and yield in optimum conditions of development. However, in drought stress conditions, the sensitivity or tolerance status to the drought of the variety can reduce the accuracy of the grain yield prediction by the model.

Weed is a serious constraint to rice production which resulted from continuous rice cropping and this allows weeds to emerge in successive flushes. Identification of weeds is the basic step for planning sound weed management programme. Depending upon the weed species, different weed management options are given keeping in view their susceptibility when growing in a crop (Walia, 2006). Cultural and/or chemical methods are generally employed to control weeds. Manual weeding though effective is getting increasingly difficult due to labor scarcity, rising wages and its dependence on weather conditions. Thus, herbicides usage seems indispensable for weed management in direct seeded rice (Azmi et al., 2005). Weed management in direct seeded systems is more critical than transplanted systems as weeds in direct seeded system can emerge at the same time or before the rice plants, resulting in a serious problem of competition (Johnson et al., 2004). Weed species resistant to herbicides have been reported in countries with high adoption rates and this might be as a result of the use of the same herbicides for long time. Nigeria has the potential to be self-sufficient in rice production, both for food and industrial raw material needs and for export. However, a number of constraints have been identified as limiting to rice production efforts by farmers. Ukungwu and Abo (2004) reported that weed is the greatest bottleneck to increased yields and quality of rice in Nigeria, particularly in the upland ecology and rank only second to drought stress. Accurate estimates of weed population's abundance and distribution variables are very important if we are to manage agricultural land for higher productivity. The objectives of this study were to determine the efficacy of some pre and post emergence herbicides at different levels for effective weed control in upland rice production system 2. Experimental Sites The experiments were conducted in 2016 and 2017 raining seasons at (11 0 39'N;08'02E) in Audu Bako College of Agriculture Dambatta research farm in Kano State of Nigeria within the Sudan savanna agro-ecological zone of Nigeria.