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Nitrogen Fixation by Groundnut and Cowpea for Productivity Improvement in Drought Conditions in the Sahel. Selection of drought tolerant and high nitrogen fixing varieties of groundnut and cowpea could improve their productivity and that of the cereals grown in association or rotation. Groundnut and cowpea varieties were assessed in field and in pots for response to drought using 4 fertilizer treatments. For cowpea, drought conditions decreased most of studied parameters, especially nodule number (40%) and pod weight (30%); while the root dry matter increased up to 10%. Nitrogen and/or Phosphorus fertilization increased pod weight up to 81%. Varieties IT93-503-1, IT93-693-2, UC-CB46 and Mouride were tolerant to drought conditions and very good nitrogen fixers. Nodule number, pod weight and root dry matter of groundnut decreased up to 12, 20 and 27% respectively due to drought conditions. Varieties ICGV-00350, ICGV-86015, ICGV-97183 and ICGVSM-87003 had the highest pod weight and the highest nodule number under drought conditions. Groundnut varieties ICGV-00350, ICGV-86015, ICGV-97183 and ICGVSM-87003 improved soil fertility and increased biomass (20%) of Pearl millet (SOSAT C88 variety) grown with them in rotation.

In semi-arid regions, particularly in the Sahel, water and high-temperature stress are serious constraints for groundnut production. Understanding of combined effects of heat and drought on physiological traits, yield and its attributes is of special significance for improving groundnut productivity. Two hundred and sixty-eight groundnut genotypes were evaluated in four trials under both intermittent drought and fully irrigated conditions, two of the trial being exposed to moderate temperature, while the two other trials were exposed to high temperature. The objectives were to analyse the component of the genetic variance and their interactions with water treatment, year and environment (temperature) for agronomic characteristics, to select genotypes with high pod yield under hot- and moderate-temperature conditions, or both, and to identify traits conferring heat and/or drought tolerance. Strong effects of water treatment (Trt), genotype (G) and genotype-by-treatment (GxTrt) interaction were observed for pod yield (Py), haulm yield (Hy) and harvest index (HI). The pod yield decrease caused by drought stress was 72 % at high temperature and 55 % at moderate temperature. Pod yield under well-watered (WW) conditions did not decrease under high-temperature conditions. Haulm yield decrease caused by water stress (WS) was 34 % at high temperature and 42 % under moderate temperature. Haulm yield tended to increase under high temperature, especially in one season. A significant year effect and genotype-by-environment interaction (GxE) effect were also observed for the three traits under WW and WS treatments. The GGE biplots confirmed these large interactions and indicated that high yielding genotypes under moderate temperature were different to those at high temperature. However, several genotypes with relatively high yield across years and temperature environments could be identified under both WW and WS conditions. Correlation analysis between pod weight and traits measured during plant growth showed that the partition rate, that is, the proportion of dry matter partitioned into pods, was contributing in heat and drought tolerance and could be a reliable selection criterion for groundnut breeding programme. Groundnut sensitivity to high-temperature stress was in part related to the sensitivity of reproduction. [ABSTRACT FROM AUTHOR]

Groundnut production is limited in Sub-Saharan Africa and water deficit or "drought," is often considered as the main yield-limiting factor. However, no comprehensive study has assessed the extent and intensity of "drought"-related yield decreases, nor has it explored avenues to enhance productivity. Hence, crop simulation modeling with SSM (Simple Simulation Modeling) was used to address these issues. To palliate the lack of reliable weather data as input to the model, the validity of weather data generated by Marksim, a weather generator, was tested. Marksim provided good weather representation across a large gradient of rainfall, representative of the region, and although rainfall generated by Marksim was above observations, run-off from Marksim data was also higher, and consequently simulations using observed or Marksim weather agreed closely across this gradient of weather conditions (root mean square of error = 99 g m -2 ; R 2 = 0.81 for pod yield). More importantly, simulation of yield changes upon agronomic or genetic alterations in the model were equally predicted with Marksim weather. A 1° × 1° grid of weather data was generated. "Drought"-related yield reduction were limited to latitudes above 12-13° North in West Central Africa (WCA) and to the Eastern fringes of Tanzania and Mozambique in East South Africa (ESA). Simulation and experimental trials also showed that doubling the sowing density of Spanish cultivars from 20 to 40 plants m -2 would increase yield dramatically in both WCA and ESA. However, increasing density would require growers to invest in more seeds and likely additional labor. If these trade-offs cannot be alleviated, genetic improvement would then need to re-focus on a plant type that is adapted to the current low sowing density, like a runner rather than a bush plant type, which currently receives most of the genetic attention. Genetic improvement targeting "drought" adaptation should also be restricted to areas where water is indeed an issue, i.e., above 12-13°N latitude in WCA and the Eastern fringes of Tanzania and Mozambique.

Rapid leaf area development may be attractive under a number of cropping conditions to enhance the vigor of crop establishment and allow rapid canopy closure for maximizing light interception and shading of weed competitors. This study was undertaken to determine (1) if parameters describing leaf area development varied among ten peanut ( Arachis hypogeae L.) genotypes grown in field and pot experiments, (2) if these parameters were affected by the planting density, and (3) if these parameters varied between Spanish and Virginia genotypes. Leaf area development was described by two steps: prediction of main stem number of nodes based on phyllochron development and plant leaf area dependent based on main stem node number. There was no genetic variation in the phyllochron measured in the field. However, the phyllochron was much longer for plants grown in pots as compared to the field-grown plants. These results indicated a negative aspect of growing peanut plants in the pots used in this experiment. In contrast to phyllochron, there was no difference in the relationship between plant leaf area and main stem node number between the pot and field experiments. However, there was genetic variation in both the pot and field experiments in the exponential coefficient (PLAPOW) of the power function used to describe leaf area development from node number. This genetic variation was confirmed in another experiment with a larger number of genotypes, although possible G × E interaction for the PLAPOW was found. Sowing density did not affect the power function relating leaf area to main stem node number. There was also no difference in the power function coefficient between Spanish and Virginia genotypes. SSM (Simple Simulation model) reliably predicted leaf canopy development in groundnut. Indeed the leaf area showed a close agreement between predicted and observed values up to 60000 cm 2  m -2 . The slightly higher prediction in India and slightly lower prediction in Niger reflected GxE interactions. Until more understanding is obtained on the possible GxE interaction effects on the canopy development, a generic PLAPOW value of 2.71, no correction for sowing density, and a phyllochron on 53 °C could be used to model canopy development in peanut.