turity. These three developmental stages were similarly eastern Nebraska to determine how environment (location, year, water described for pearl millet by Maiti and Bidinger (1981).regime) influences number of panicles per square meter, kernel weight,For grain sorghum and pearl millet, potential kernel and kernels per panicle in determining grain yield of pearl millet and number is set during GS2 and kernel weight is deter- (Eastin et al., 1983). Yield component studies with grain Saeed et al., 1986; Rajewski et al., 1991), row number of panicles per square meter and kernels per spacing and plant population (Stickler and Wearden, panicle. Variation in kernel weight allows for a degree 1965), and soil water storage differences (Norwood, of yield compensation late in the life cycle. Increases 1992). Yield component studies with pearl millet have in kernels per panicle and in kernel weight may help shown the number of panicles per plant to be the yield compensate for low plant populations or limited tillercomponent most associated with yield changes with ing. As a result of this compensatory power, grain yield plant population, but because of profuse tillering, the in cereals is relatively insensitive to plant population number of panicles per square meter may decrease (van (Anderson, 1986); however, this compensation is less Oosterom et al., 2002) or remain nearly constant (Carthan perfect in grain sorghum (Kiniry, 1988) This research was conducted to determine the effect The treatment structure was a 4 ϫ 2 factorial at both locaof environment (year, location, water regime) on the tions. Factor one consisted of four water regimes chosen to yield components of grain sorghum and pearl millet, Great Plains production environments. The research two consisted of two crops: a pearl millet hybrid (68A ϫ 086R) focus was on western Nebraska where this experiment and an early maturing grain sorghum hybrid (DK 28E). These was conducted to determine the potential for pearl milwere the best-adapted hybrids available for the Sidney localet and grain sorghum as crops. The eastern Nebraska tion on the basis of performance tests. The experimental designs were different at the two locations becaue of a difference location provided a reference point for a region where in irrigation systems available at the two sites. At Sidney, grain sorghum is widely grown. Our hypotheses were where the irrigation system was a lateral-move system with that environment would alter those yield components drop-nozzle booms, the experiment was conducted as a ranthat are most closely associated with grain yield in pearl domized complete block design with four replications. Plot millet and grain sorghum, and that (i) under limited size was 9.1 m (12 rows 76 cm apart) wide and 9.1 m long with water stress, the number of panicles per square meter 3-m alleys between plots. At Mead, where a furrow irrigation would be the most important yield contributor for both system was used, the experiment was conducted as a randomcrops, (ii) since kernel number is ...

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tion (ET) limit the number of crops grown in this region. Corn (Zea mays L.), sunflower (Helianthus annuus L.), Pearl millet [Pennisetum glaucum (L.) R. Br.] is a drought-tolerant soybean [Glycine max (L.) Merr.], and proso millet crop that may serve as an alternative summer crop in Nebraska. Field (Panicum miliaceum L.) are possible crops for inclusion experiments were conducted in 2000 and 2001 near Sidney and Mead, NE, to determine the water use efficiency (WUE) and yield response in more intensive cropping systems. Grain sorghum was to water supply at critical developmental stages of pearl millet and found to be more suitable than corn, soybean, or sungrain sorghum [Sorghum bicolor (L.) Moench]. Four water regimes flower due to greater and more consistent yields. were used: (i) no irrigation, (ii) single irrigation at boot stage, (iii) Pearl millet, with its short growth cycle and drought single irrigation at mid-grain fill, and (iv) multiple irrigations. Pearl tolerance, may be a better alternative crop than grain millet grain yields were 60 to 80% that of grain sorghum. Average sorghum for western Nebraska and a possible diversifigrain yields at Mead were 5.1 Mg ha Ϫ1 for pearl millet and 6.1 Mg cation crop in eastern Nebraska cropping systems. Plett ha Ϫ1 for grain sorghum. At Sidney, average pearl millet yields were et al. (1991) indicated that pearl millet did not perform 1.9 and 3.9 Mg ha Ϫ1 in 2000 and 2001, respectively, and average grain sorghum yields were 4.1 and 5.0 Mg ha Ϫ1 in 2000 and 2001, respectively. well compared with grain sorghum and corn when grown Both crops used a similar amount of water (336 and 330 mm in 2000 in western Nebraska. However, those hybrids were exand 370 and 374 mm in 2001 for pearl millet and grain sorghum, perimental, and cool night temperatures resulted in respectively) and responded to irrigation with a linear increase in problems with seed set. Progress has been made in pearl grain yield as water use increased. Grain sorghum had greater WUE millet breeding, and hybrids less sensitive to cold night than pearl millet (12.4-13.4 kg vs. 5.1-10.4 kg grain ha Ϫ1 mm Ϫ1 ). Pearl temperatures have been developed. Pearl millet is usumillet, with lower and less stable yields, does not currently have the ally grown as a rainfed crop on sandy soil in the semiarid potential to be a substitute crop for grain sorghum in Nebraska.

SUMMARYPearl millet [Pennisetum glaucum (L) R. Br.] is an important cereal crop in Niger, West Africa and a potential crop for the United States of America (USA). Only a few studies have been conducted in either country to identify the optimum planting dates for high and stable yields, in part because planting date experiments are resource-intensive. Crop simulation models can be an alternative research tool for determining optimum planting dates and other management practices. The objectives of the present study were to evaluate the performance of the Cropping System Simulation Model (CSM)–CERES-Millet model for two contrasting environments, including Mead, Nebraska, USA and Kollo, Niger, West Africa and to use the model for determining the optimum planting dates for these two environments. Field experiments were conducted in both environments to study the impact of nitrogen fertilizer on grain yield of three varieties in Kollo and three hybrids in Mead and their associated growth and development characteristics. The CSM–CERES-Millet model was able to accurately simulate growth, development and yield for millet grown in these two contrasting environments and under different management practices that included several genotypes and different nitrogen fertilizer application rates. For Kollo, the optimum planting date to obtain the maximum yield was between 13 and 23 May for variety Heini Kirei, while for the other varieties the planting dates were between 23 May and 2 June. For Mead, the planting date analysis showed that the highest simulated yield was obtained, on average, between 19 and 29 June for hybrid 59022A×89-083 and 1361M×6Rm. Further studies should focus on evaluation and application of the millet model for other agroclimatic regions where pearl millet is an important crop.

SUMMARYPearl millet (Pennisetum glaucum L.) is an important grain crop for millions of poor farmers and consumers in the semi-arid region of West Africa. During the past 40 years, much research on pearl millet production practices and adoption in this region has been conducted, but an attempt to summarize these results has not been previously completed and these research results are not readily available to many West African scientists. This review was completed to address this need and integrate knowledge, and at the same time identify research needs for the future and extension priorities for semi-arid West African agro-ecological zones. Research has shown that selection of improved varieties and cropping systems, appropriate cultural practices, and recommended integrated soil, nutrient, residue and pest management can greatly increase grain and stover yields of pearl millet. However, adoption by farmers has been minimal due to limited profitability, high risk and labour demand, limited input supply, market availability and appropriate public policy. This review has 196 articles included as in-text citations (Table 1) compared to 149 articles in the reference list, indicating that only one in four articles integrated two or more topics in the research. The obvious conclusion is that most of the past research has not addressed the ‘system’ but rather one or two management practices. In addition, most studies have interpreted responses in terms of yield without addressing other important considerations for farmer adoption. Recent conservation agriculture research moves closer to addressing the larger integrative types of research needed. Such research is complex and requires sustained funding for field and laboratory activities, but also for computer simulation modelling and economic assessment.