Background Anemia is one of the most common conditions that affect pregnancies, with dietary iron deficiency being its most common cause. Maternal anemia has been associated with increased risks of both maternal and neonatal adverse outcomes. This study aimed to analyze the maternal and neonatal outcomes in women with third-trimester anemia. Methods This was a retrospective report from a Pakistani public hospital. It included data records of the childbirths in the hospital, with at least one record that documented the hemoglobin (Hb) level in women in the first or second trimester and one in the third trimester. The duration of the study was from January 1, 2019 to June 30, 2019. Women with Hb level of <10mg/dL in the third trimester were categorized as anemic, and those with Hb level of >10mg/dL were categorized as non-anemic. Pregnancy outcomes were assessed for both mothers and babies. All data were processed through SPSS version 21.0 for Windows (IBM Corp., Armonk, NY). Results The study evaluated 235 (37.8%) anemic and 387 (62.2%) non-anemic women. Adverse maternal outcomes were compared between the two groups. In anemic women, gestational hypertension (56% vs. 27%; p: <0.0001), preeclampsia (65% vs. 25%; p: <0.0001), antepartum hemorrhage (32% vs. 19%; p: =0.0001), postpartum hemorrhage (79% vs. 28%; p: <0.0001), transfusions (94% vs. 5%; p: <0.0001), prolonged/obstructed labor (49% vs. 20%; p: <0.000), urgent induction of labor (24% vs. 2%; p: <0.0001), and urgent caesarean section (CS) (45% vs. 29%; p: 0.0001) were significantly more common as compared to non-anemic women. Adverse neonatal outcomes such as low birth weight (LBW) (59% vs. 29%; p: <0.0001), small-for-gestational-age (SGA) (73% vs. 23%; p: <0.0001), preterm delivery (39% vs. 15%; p: <0.0001), stillbirth (8% vs. 3%; p: 0.01), and early neonatal death (9% vs. 2%; p: 0.000) were associated more with anemia. There was no report of maternal mortality in either group. Conclusion: Anemia in the third trimester of pregnancy is associated with adverse maternal and neonatal outcomes including neonatal death. Efforts are required to ensure adequate maternal nutritional status in order to prevent poor outcomes.
Fat hen is a dominating weed of wheat and several important crops around the globe. Interference of this weed has not only caused substantial yield reduction in associated crops but also negatively influenced the succeeding crops in rotation pattern. Residual effects of fat hen infested soils were investigated in a bioassay at glass house, Department of Agronomy, Bahauddin Zakariya University, Multan during 2021. Rhizosphere soil along with fat hen incorporated soils were included in experiment while, for comparison sand and clay loam soils were also used as control treatments. Data regarding germination indices like time taken to 50 percent germination, mean emergence time, final emergence percentage, germination index, germination energy and seedling growth parameters like shoot/root length, shoot/root dry weight all indicated that fat hen incorporated soils exhibited a strong negative effect on the test crops (mungbean and maize). Whereas, rhizosphere soil also showed inhibitory effect on both test crops in comparison to sand and clay loam soils. However, the negative effects of incorporated soils are more prominent than the rhizosphere soil of fat hen. Rich allelochemicals profile of fat hen could be the possible reason of these negative influences. Findings of this investigation were used for planning of crop rotation pattern because farmers incorporate the standing fat hen into the soil after harvesting of their crops. So, farmers should avoid incorporation of fat hen in to the soil to avoid the possible negative effect on the succeeding crops.
Fodder yield and quality must be improved for sustainable livestock production. A lack of or low application of phosphorus (P) and potassium (P) are among the leading constraints of lower fodder yield and quality of sorghum [most cultivated fodder crop during kharif season (crop cultivation in summer and harvesting during winter] in Aridisol of Pakistan. Therefore, this two-year field study evaluated the role of different P and K levels on fodder yield and quality of sorghum cultivar ‘Ijar-2002’ planted in Multan and Okara districts, Punjab, Pakistan. Seven P-K (kg ha−1) levels, i.e., T1 (40–0), T2 (80–0), T3 (0–40), T4 (0–60), T5 (40–40), T6 (80–40), T7 (60–80) and an untreated T0 (control) were included in the study. Results indicated that individual effects of years, locations and P-K levels had a significant effect on fodder yield and quality. All treatments received an equal amount of nitrogen (i.e., 120 kg ha−1). Application of P-K in Aridisols at both locations significantly improved fodder yield, dry matter yield, and ether contents during both years. The T6 (80–40 kg ha−1) significantly improved yield and quality traits of sorghum fodder except for crude fiber (CF) and acid and neutral detergent fiber (ADF and NDF) at both locations during both years of study. Moreover, fodder harvested from Multan observed significantly higher CF, ADF, NDF, cellulose and hemicellulose contents than Okara. However, sorghum grown in Okara harvested more fodder yield due to more plant height and ether contents. In conclusion, planting sorghum in Aridisols, fertilized with 80–40 kg ha−1 P-K seemed a viable option to harvest more fodder yield of better quality.
Crop growth models can be valuable tools for researchers, academia, extension educators, and policy makers/planners for the evaluation of sustainable and long-term husbandry practices. Determining the optimum sowing window, which can be determined using crop growth models, is imperative under changing climate conditions. Thus, the main objectives herein were to 1) assess the performance of the cropping system model-crop environment resource synthesis-maize model for hybrids and sowing dates in the spring and autumn, and 2) determine the optimum sowing window in 15 districts of Punjab, Pakistan. In the spring experiment, 3 hybrids (P-33M15, M-DK6525, and S-NK8441) were planted in the main plots and then on 5 different sowing dates (January 15th, February 5th, February 25th, March 15th, and April 5th), they were planted in the subplots. In the autumn experiment, 3 hybrids (P-30R50, M-DK6714, and S-NK6621) were planted in the main plots and then on 5 different sowing dates (June 15th, July 5th, July 25th, August 15th, and September 5th), they were planted in the subplots. Model calibration and evaluation results were better in the spring and autumn. Performance of the model was good for the grain yield in the autumn (mean percentage difference (MPD): 7.47% to 8.90%) compared to the spring (MPD: 9.42% to 11.72%). Model evaluation was good for the early sowing dates (January 15th and February 5th) (error range: 6.26% to 9.65%) compared to the delayed dates (February 25th to April 5th) (error range: 9.34 to 14.91%). In the autumn, the model showed better performance for the delayed sowing dates (February 25th and August 15th) (error range: 5.22% to 9.43%) compared to the early dates (June 15th and July 5th) (error range: 8.56% to 11.27%). The model simulated good growth, development, grain yield, and yield components in the spring and autumn and of both 2016 and 2017. For the model application simulation of data over the long-term (1980 to 2017), the optimum sowing window in the spring was January 15th to March 5th and for the autumn it was July 23rd to August 27th for the 15 districts in Punjab, Pakistan. Simulation of the sowing dates for the whole year indicated that the spring was better compared to the autumn for obtaining the maximum grain yield. The results of the model were in line with the recommendations of the agricultural extension department for the sowing window for spring and autumn maize. It is therefore suggested that farmers should complete the sowing of spring and autumn maize within the sowing window to attain a higher yield of maize in arid and semiarid areas of Punjab, Pakistan.
Phenological development determines the period of vegetative and reproductive growth, assimilate partitioning and dry matter production. Planting time and density are the major factors affecting phenological development, assimilate partitioning and yield of faba bean. The aim of this study was to evaluate the effect of planting date and plant density on phenological development, assimilate partitioning and yield of faba bean. Faba bean was planted on eight dates from September 20 to December 27, 1999 with 14 days interval maintaining 4 density (150,000, 300,000, 450,000, 600,000 plants ha -1 ) at New Developmental Farm, NWFP Agricultural University, Peshawar. Planting dates and population density significantly affected days to flowering, days to maturity, grains pod -1 , plant height and grain yield ha -1 . However, days to emergence and maturity were only affected by planting date. Crop planted on September 20 took minimum days to emergence (5 days) and maximum days to flowering (57.6), maturity (204), produced more grains pod -1 (3.4) and taller plants (176.9 cm). Crop planted on October 4, 1999 produced maximum grain yield (4153 kg ha -1 ). Plant density of 450,000 plants ha -1 took maximum days to flowering (54.2), more grain pod -1 (3.2) and produced maximum grain yield (2498 kg ha -1 ), while population density of 600,000 plants ha -1 produced tallest plants (146.3 cm). It can be concluded that faba bean can be planted up to October 4 at 450,000 plants ha -1 to obtain maximum yield.
Salinity exerts significant negative impacts on growth and productivity of crop plants and numerous management practices are used to improve crop performance under saline environments. Micronutrients, plant growth promoting bacteria and biochar are known to improve crop productivity under stressful environments. Maize (Zea mays L.) is an important cereal crop and its productivity is adversely impacted by salinity. Although boron (B) application, seed inoculation with boron-tolerant bacteria (BTB) and biochar are known to improve maize growth under stressful environments, there is less information on their combined impact in enhancing maize productivity on saline soils. This study investigated the impact of B seed coating combined with seed inoculation with BTB + biochar on maize productivity under saline soil. Four B seed coating levels [0.0 (no seed coating), 1.0, 1.5, 2.0 g B kg-1 seed], and individual or combined application of 5 % (w/w) maize stalk biochar, and seed inoculation with Bacillus sp. MN-54 BTB were included in the study. Different growth and yield attributes and grain quality were significantly improved by seed coating with 1.5 B kg-1 seed coupled with biochar + BTB. Seed coating with 1.5 B kg-1 seed combined with biochar + BTB improved stomatal conductance by 32 %, photosynthetic rate by 15 %, and transpiration ratio by 52 % compared to seed coating (0 B kg-1 seed) combined with biochar only. Similarly, the highest plant height (189 cm), number of grain rows cob-1 (15.5), grain yield (54.9 g plant-1), biological yield (95.5 g plant-1), and harvest index (57.6 %) were noted for B seed coating (1.5 g B kg-1 seed) combined with biochar + BTB inoculation. The same treatment resulted in the highest grain protein and B contents. It is concluded that B seed coating at 1.5 g B kg-1 seed combined with biochar + BTB inoculation could significantly improve yield and quality of maize crop on saline soils. However, further field experiments investigating the underlying mechanisms are needed to reach concrete conclusions and large-scale recommendations.
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