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Background: Many developing countries are experiencing a rapid nutrition transition in urban areas. Objective: To investigate whether a nutrition transition was occurring in a rural area by examining the dietary patterns of women in rural Tanzania. Methods: A total of 252 women aged 16 to 45 years from three districts of northeastern and central Tanzania participated. During three different seasons in 2006-2007, the women were interviewed with the use of a structured, interviewer-administered questionnaire, including a 24-hour dietary recall. From these recalls, the mean intakes of 12 main food groups were calculated and used to establish five dietary patterns by principal component analysis. Data were also obtained on attitudes toward obesity, body mass index (BMI), hemoglobin level, and measures of socioeconomic status and analyzed for associations with dietary patterns. Results: The five dietary patterns were "traditional-coast," characterized by fruits, nuts, starchy plants, and fish; "traditional-inland," characterized by cereals, oils and fats, and vegetables; "purchase," characterized by bread and cakes (usually fried in oil), sugar, and black tea; "pulses," characterized mainly by pulses, with few or no vegetables; and "animal products," characterized by a high consumption of meat, eggs, and/or milk. Significant positive associations were found, among others, between the purchase pattern and BMI (p = 0.192, p = .005) and between the animal products pattern and wealth (p = 0.168, p = .002). Conclusions: Differences between traditional and modern nutritional food patterns were evident. This study found the"traditional-inland" pattern to be the most healthy, while the "purchase" food pattern was the most prevalent. The purchase pattern, in particular, may provide some evidence for early stages of the nutrition transition in rural Tanzania. [ABSTRACT FROM AUTHOR]

Under-utilised orphan crops hold the key to diversified and climate-resilient food systems. Here, we report on orphan crop genomics using the case of Lablab purpureus (L.) Sweet (lablab) - a legume native to Africa and cultivated throughout the tropics for food and forage. Our Africa-led plant genome collaboration produces a high-quality chromosome-scale assembly of the lablab genome. Our assembly highlights the genome organisation of the trypsin inhibitor genes - an important anti-nutritional factor in lablab. We also re-sequence cultivated and wild lablab accessions from Africa confirming two domestication events. Finally, we examine the genetic and phenotypic diversity in a comprehensive lablab germplasm collection and identify genomic loci underlying variation of important agronomic traits in lablab. The genomic data generated here provide a valuable resource for lablab improvement. Our inclusive collaborative approach also presents an example that can be explored by other researchers sequencing indigenous crops, particularly from low and middle-income countries (LMIC)., (© 2023. The Author(s).)

Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean ( Phaseolus vulgaris L.), cowpea ( Vigna unguiculata (L.) Walp.] and lablab [ Lablab purpureus (L.) Sweet] were selected to assess their agricultural potential with respect to climate variability and change along the Machakos-Makueni transect in semi-arid Eastern Kenya. This was undertaken using measured data [a water response trial conducted during 2012/13 and 2013/14 in Machakos, Kenya] and simulated data using the Agricultural Production System sIMulator (APSIM). The APSIM crop model was calibrated and validated to simulate growth and development of short-season grain legumes in semi-arid environments. Water use efficiency (WUE) was used as indicator to quantify the production potential. The major traits of adaptation include early flowering and pod and seed set before the onset of terminal drought. Early phenology together with adapted canopy architecture allowed more optimal water use and greater partitioning of dry matter into seed (higher harvest index). While common bean followed a comparatively conservative strategy of minimizing water loss through crop transpiration, the very short development time and compact growth habit limited grain yield to rarely exceed 1,000 kg ha -1 . An advantage of this strategy was relatively stable yields independent of in-crop rainfall or season length across the Machakos-Makueni transect. The growth habit of cowpea in contrast minimized water loss through soil evaporation with rapid ground cover and dry matter production, reaching very high grain yields at high potential sites (3,000 kg ha -1 ) but being highly susceptible to in-season drought. Lablab seemed to be best adapted to dry environments. Its canopy architecture appeared to be best in compromising between the investment in biomass as a prerequisite to accumulate grain yield by minimizing water loss through soil evaporation and crop transpiration. This lead to grain yields of up to 2,000 kg ha -1 at high potential sites and >1,000 kg ha -1 at low potential sites. The variance of observed and simulated WUE was high and no clear dependency on total rainfall alone was observed for all three short-season grain legumes, highlighting that pattern of water use is also important in determining final WUE biomass and WUE grain . Mean WUE grain was lowest for cowpea (1.5-3.5 kg grain ha -1 mm -1 ) and highest for lablab (5-7 kg grain ha -1 mm -1 ) reflecting the high susceptibility to drought of cowpea and the good adaptation to dry environments of lablab. Results highlight that, based on specific morphological, phonological, and physiological characteristics, the three short-season grain legumes follow different strategies to cope with climate variability. The climate-smart site-specific utilization of the three legumes offers promising options to design more resilient and productive farming systems in semi-arid Eastern Kenya.

Background: For many developing countries, obesity and its sequelae have become a challenge of a magnitude similar to hunger and undernutrition. The main objective of this study was, therefore, to investigate the weight status of women in rural Tanzania with reference to season as well as the link between women's weight, food consumption, and attitudes toward obesity., Methods: Three cross-sectional surveys in 3 different seasons within 1 year interviewed the same 210 women, ages 17-45 years, from 3 rural districts of northeastern and central Tanzania. These surveys assessed body mass index (BMI), food intake, and dietary diversity through 24-hour recalls, women's attitudes toward obesity, vegetable production, and socioeconomic status., Results: Although 71% of the women had a normal BMI, 7% were underweight, 16% overweight, and 6% obese. The BMI was correlated with the Dietary Diversity Score (DDS), the Food Variety Score (FVS), with the consumption of foods from the food groups "bread/cakes," "sugar," and "tea," and with the production of exotic vegetables. In a multiple regression model, FVS was directly associated with BMI. When asked to describe the typical characteristics of an obese person, women mentioned more negative than positive characteristics., Conclusion: The prevalence of overweight and obesity was 3 times higher than that of underweight. Apparently, even in rural areas of Tanzania, a nutrition transition is underway. No direct association was identified between vegetable consumption and BMI. Although this study did not assess behavioral factors, such behavioral factors as activity levels as well as attitudes need to be considered, even in rural settings, to address all facets of malnutrition.

There is uncertainty on how generally applicable near-infrared reflectance spectroscopy (NIRS) calibrations are across genotypes and environments, and this study tests how well a single calibration performs across a wide range of conditions. We also address the optimization of NIRS to perform the analysis of crude protein (CP) content in a variety of cowpea accessions (n = 561) representing genotypic variation as well as grown in a wide range of environmental conditions in Tanzania and Uganda. The samples were submitted to NIRS analysis and a predictive calibration model developed. A modified partial least-squares regression with cross-validation was used to evaluate the models and identify possible spectral outliers. Calibration statistics for CP suggests that NIRS can predict this parameter in a wide range of cowpea leaves from different agro-ecological zones of eastern Africa with high accuracy (R (2)cal = 0.93; standard error of cross-validation = 0.74). NIRS analysis improved when a calibration set was developed from samples selected to represent the range of spectral variability. We conclude from the present results that this technique is a good alternative to chemical analysis for the determination of CP contents in leaf samples from cowpea in the African context, as one of the main advantages of NIRS is the large number of compounds that can be measured at once in the same sample, thus substantially reducing the cost per analysis. The current model is applicable in predicting the CP content of young cowpea leaves for human nutrition from different agro-ecological zones and genetic materials, as cowpea leaves are one of the popular vegetables in the region.