DSpace Collection: Crop Production

Development of mathematical model for optimal rice production in Niger State, Nigeria

Mon, 01 Jan 2024 00:00:00 GMT

Title: Development of mathematical model for optimal rice production in Niger State, Nigeria Authors: Yahaya, A. A.; Hakimi, D.; Shehu, M. D.; Daniya, E. Abstract: Rice is a staple food and a critical crop for food security and economic stability in Niger State, Nigeria. However, achieving optimal production levels is challenged by various factors, including environmental variability, land use inefficiency, and rising production costs. Mathematical modeling offers a systematic approach to understanding and optimizing these factors to enhance yields and promote sustainable agricultural practices. A mathematical model to optimize rice production by integrating key agronomic, environmental, and economic factors were formulated. This research paper aims to predict optimal rice yields based on input variables such as rainfall, temperature, humidity, land area use and production cost using a multivariate linear regression (MLR) method. The developed model is validated with real-world data from agricultural research stations. It was observed from the analysis that predicted values were not significantly different from the observed values. The results show that R-square, Mean Square Error (MSE) and Root Mean Square Errors (RMSE) values were 0.96345, 0.0249 and 0.1578 respectively; indicating that approximately 96.35% of the variance in rice production can be explained by the independent variables. Due to its high level of accuracy in predicting rice yield; it can be concluded that the model can be used to determine optimum rice production in Niger state, Nigeria and provide a decision-support tool for farmers and policymakers.

Rhizobium inoculant integration with organic and mineral fertilizer: Impact on weed infestation, soybean growth and yield in southern Guinea savanna, Nigeria

Sun, 01 Jan 2023 00:00:00 GMT

Title: Rhizobium inoculant integration with organic and mineral fertilizer: Impact on weed infestation, soybean growth and yield in southern Guinea savanna, Nigeria Authors: Daniya, E.; Aguwa, N.; Osunde, A. O.; Kolo, M. G. M. Abstract: To evaluate the effect of integrating Rhizobium inoculant, organic and inorganic fertilizer on weed infestation, growth and yield of soybean, an on-farm experiment was conducted in the 2015 and 2016 rainy seasons in Paikoro Local Government Area of Niger State, Nigeria. The treatments were control (no input), inoculant (I ) only, I + phosphorus (P), I + P + potassium (K), I + P + K + micronutrients (M), and I + P + K + M + cow dung (CD) replicated three times in a randomized complete block design. Data collected were weed species composition, weed density and dry weight, nodule dry weight, pods per plant, grain weight and grain yield of soybean. Results indicated that weeds with highest relative density values across all the nutrient combinations were Ageratum conyzoides and Kyllinga sp., and other notable species included Mitracarpus villosus, Oldenlandia corymbosa, Sida rhombifolia, Paspalum scrobiculatum, Cynodon dactylon, Digitaria horizontalis Cyperus rotundus and Cyperus difformis. Years had a significant effect on weed density, weed dry weight, nodule dry weight, number of pods per plant and grain weight, number of pods per plant and grain weight of soybean. Weed density and dry weight, and weight of nodules, number of pods and grain weight of soybean were lower in 2015 compared to 2016. Among the treatments, I + P + K + M reduced weed dry weight better than I + P + K + M + CD. Average over the years, soybean grain yield was enhanced with the integration of I + P, I + P + K, I + P + K + M, I + P + K + M. However, the highest grain yield was obtained with the integration of I + P +K + M + CD which is recommended for soybean production in this agroecology of Nigeria.

Weed control and productivity of maize (Zea mays L.) interseeded with Jointvetch (Aeschynomene histrix Poir.) at different sowing arrangements

Sun, 01 Jan 2023 00:00:00 GMT

Title: Weed control and productivity of maize (Zea mays L.) interseeded with Jointvetch (Aeschynomene histrix Poir.) at different sowing arrangements Authors: Daniya, E.; Mohammed, A. B.; Onyenuforo, C. C. Abstract: The use of forage legume with cereals offers a potential for increasing food and forage production. Field study was conducted during the rainy seasons of 2015 and 2016 to determine the effect of interseeding Jointvetch (Aeschynomene histrix) at different sowing arrangements on weed control, growth and yield of maize. The treatments were one hoe weeding at 3 weeks after sowing (WAS) followed by (fb) one row of Jointvetch drilled by the side of the ridge at 3 WAS, one hoe weeding at 3 WAS fb two rows of Jointvetch drilled by the sides of the ridge at 3 WAS, one hoe weeding at 3 WAS fb one row of Jointvetch drilled within the furrow at 3 WAS, one hoe weeding at 3 WAS fb two rows of Jointvetch drilled within the furrow at 3 WAS, one hoe weeding at 3 WAS fb Jointvetch broadcast within the plot at 3 WAS, two hoe weeding at 3 and 6 WAS and a weedy check arranged in a randomized complete block design (RCBD) and replicated three times. Data collected on weed dry weight, plant height, cob length, cob diameter and grain yield were subjected analysis of variance (ANOVA) at P ≤ 0.05. Weed dry weight, plant height, cob length, cob diameter and grain yield were significantly (p≤0.05) influenced by Jointvetch arrangement. The magnitude of weed suppression was lowest in the plot with Jointvetch broadcast, which also produced taller plants, longer cobs, wider cobs and highest grain yield compared to the weedy check. Grain yield in plots interseeded with Jointvetch and two hoe weeding at (3 and 6 WAS) were comparable and higher than that in the weedy check. Our findings demonstrated that one hoe weeding at 3 WAS fb Jointvetch broadcast can reduce weed growth and increase grain yield of maize.

Genetic parameters and correlation coefficient study of some quantitative traits in soybean [Glycine max (L.) Merill]

Sat, 01 Jan 2022 00:00:00 GMT

Title: Genetic parameters and correlation coefficient study of some quantitative traits in soybean [Glycine max (L.) Merill] Authors: Akinyele, M. O.; Gana, A. S.; Daniya, E.; Tolorunse, K. D. Abstract: Selection is a continuous activity in plant breeding programs that must be carried out by plant breeders in order to obtain superior plant genotypes 50 genotypes of soybean were evaluated through alpha lattice incomplete design with three replications in 2019 and 2020 rain seasons to determine the extent of genetic parameters and correlation coefficient for genotypes improvement in 12 agro-morphological traits: Plant height at 4weeks, Plant height at 8weeks, Plant height at 12weeks, Days to 50 % flowering, Number of branches, Days to maturity, Above ground biomass, Pods per plant, Seeds per pod, Seed yield per plot, 100 seed weight and Harvest index. Data from the two years trials were subjected to analysis of variance following the procedure of Statistical Tools for Agricultural Research (STAR 2.0.1) and Plant Breeding Tools (PBTools 1.3, 2014). Significance means separation was done using Least Significant Difference (LSD) at P < 0.05. The results showed there were significant differences between genotypes. Phenotypic coefficient of variation (PCV) were higher than genotypic coefficient of variation (GCV) for the traits studied. Broad sense heritability ranges from low (value <30) to high (value>60). Combined correlation coefficient for the two cropping seasons revealed that the yield components exhibited varying trends of correlation relationship between themselves, Seed yield had significant positive correlation with Number of branches, Pods per plant and Harvest Index with correlation coefficient values of 0.477, 0.525 and 0.639 respectively. The results obtained suggested that, Number of branches, Pods per plant and Harvest index were the most important traits that determined seed yield and could be used for future yield improvement in soybean breeding programme