Management Zone Delineation for Variable-Rate Seeding in Production Soybeans

Soybean seeding rate (SR) is selected according to planting date, maturity group, soil properties, and yield goal. Even though one SR is applied in most fields, site-specific adjustments with variable-rate seeding (VRS) technology can help optimize production. The project goal was to determine if VRS could be beneficial to soybean producers in Arkansas. The project objectives were to i) assess planter performance and soybean yield response to five seeding rate treatments, ii) characterize the drivers of yield variability, and iii) create a-posteriori prescription maps for VRS. Five SR treatments (185,000, 247,000, 309,000, 370,000 and 432,000 seeds ha-1) were applied using a randomized complete block strip design in two site-years referred to as production fields A (2021) and B (2022) in Lincoln County in Arkansas. As-applied SR were collected from the planter. Plant population was calculated from stand counts collected at the four to five trifoliate stages. Yield monitor data were collected at harvest. As-applied SR, plant population, and yield data were averaged by strip and analyzed using mixed-effect models. While significant differences in as-applied SR and plant population (P=0.05) were observed between treatments, there was no difference in yield. Yet, the within treatment yield variability calculated as a coefficient of variation ranged from 4% to 14% and further analysis was computed to identify the drivers of in-field variability. Soil mapping unit (SMU) information was downloaded from the Soil Survey Geographic database. Soil samples were collected in 91 and 80 locations in fields A and B to characterize soil pH, potassium (K), phosphorus (P), and soil texture defined by both the textural class and percent sand, silt, and clay. Digital elevation models (DEM) were downloaded from the United States Geological Survey public data repository and used to compute flow accumulation. A total of 3,586 and 2,153 grid points were created in field A and B. Soil texture, pH, K, and P, SMU, elevation, and flow accumulation were estimated in each grid point using interpolation or extraction. A 100-fold cross-validation with a 10% calibration/90%validation data split was computed to identify the model that best describes site-specific relationships between yield, SR, and soil properties in each field. The best model described yield as a function of the interaction between SR and both soil pH and soil K in field A. The best model described yield as a function of SMU, percent sand – both linear and quadratic effects-, percent clay, and the interaction between SR and percent clay in field B. As the interaction between SR and other parameters were significant in both fields, a-posteriori prescription maps were created using the following approach. Yield was predicted for each SR treatment and grid point using the best models. Grid points were organized in groups of 4 to create 896 and 538 management zones (MZ) in fields A and B, respectively. Analysis of variance and post-hoc analyses were computed to identify the optimum SR in each MZ. Results were summarized into prescription maps. Future research may include comparison of results between growing seasons, economic analysis, implementation, and on-farm validation

Management Zone Delineation for Variable-Rate Seeding in Production Soybeans

Soybean seeding rate (SR) is selected according to planting date, maturity group, soil properties, and yield goal. Even though one SR is applied in most fields, site-specific adjustments with variable-rate seeding (VRS) technology can help optimize production. The project goal was to determine if VRS could be beneficial to soybean producers in Arkansas. The project objectives were to i) assess planter performance and soybean yield response to five seeding rate treatments, ii) characterize the drivers of yield variability, and iii) create a-posteriori prescription maps for VRS. Five SR treatments (185,000, 247,000, 309,000, 370,000 and 432,000 seeds ha-1) were applied using a randomized complete block strip design in two site-years referred to as production fields A (2021) and B (2022) in Lincoln County in Arkansas. As-applied SR were collected from the planter. Plant population was calculated from stand counts collected at the four to five trifoliate stages. Yield monitor data were collected at harvest. As-applied SR, plant population, and yield data were averaged by strip and analyzed using mixed-effect models. While significant differences in as-applied SR and plant population (P=0.05) were observed between treatments, there was no difference in yield. Yet, the within treatment yield variability calculated as a coefficient of variation ranged from 4% to 14% and further analysis was computed to identify the drivers of in-field variability. Soil mapping unit (SMU) information was downloaded from the Soil Survey Geographic database. Soil samples were collected in 91 and 80 locations in fields A and B to characterize soil pH, potassium (K), phosphorus (P), and soil texture defined by both the textural class and percent sand, silt, and clay. Digital elevation models (DEM) were downloaded from the United States Geological Survey public data repository and used to compute flow accumulation. A total of 3,586 and 2,153 grid points were created in field A and B. Soil texture, pH, K, and P, SMU, elevation, and flow accumulation were estimated in each grid point using interpolation or extraction. A 100-fold cross-validation with a 10% calibration/90%validation data split was computed to identify the model that best describes site-specific relationships between yield, SR, and soil properties in each field. The best model described yield as a function of the interaction between SR and both soil pH and soil K in field A. The best model described yield as a function of SMU, percent sand – both linear and quadratic effects-, percent clay, and the interaction between SR and percent clay in field B. As the interaction between SR and other parameters were significant in both fields, a-posteriori prescription maps were created using the following approach. Yield was predicted for each SR treatment and grid point using the best models. Grid points were organized in groups of 4 to create 896 and 538 management zones (MZ) in fields A and B, respectively. Analysis of variance and post-hoc analyses were computed to identify the optimum SR in each MZ. Results were summarized into prescription maps. Future research may include comparison of results between growing seasons, economic analysis, implementation, and on-farm validation

Two Dimensional Lattice Gauge Theory with and without Fermion Content

Quantum Chromo Dynamics (QCD) is a relativistic field theory of a non-abelian gauge field coupled to several flavors of fermions. Two dimensional (one space and one time) QCD serves as an interesting toy model that shares several features with the four dimensional physically relevant theory. The main aim of the research is to study two dimensional QCD using the lattice regularization. Two dimensional QCD without any fermion content is solved analytically using lattice regularization. Explicit expressions for the expectation values of Wilson loops and the correlation of two Polyakov loops oriented in two different directions are obtained. Physics of the QCD vacuum is explained using these results. The Hamiltonian formalism of lattice QCD with fermion content serves as an approach to study quark excitations out of the vacuum. The formalism is first developed and techniques to numerically evaluate the spectrum of physical particles, namely, meson and baryons are described. The Hybrid Monte Carlo technique was used to numerically extract the lowest meson and baryon masses as a function of the quark masses. It is shown that neither the lowest meson mass nor the lowest baryon mass goes to zero as the quark mass is taken to zero. This numerically establishes the presence of a mass gap in two dimensional QCD

Effect of Mineral Ions on the Functional Properties of Starch Films

Essential minerals are indispensable inorganic micronutrients that modulate vital physiological functions at the molecular level. Their deficiency, though required in small amounts, impairs health significantly. Their supplementation through diet is prudent and carbohydrates standout as favorable choice. Carbohydrates, starches and polysaccharides, exhibit unique chemical structures and functionalities, and interact with mineral ions in several ways. The aim of this research is to investigate the effect of mineral ions on the physicochemical properties, tensile strength and in vitro starch digestion of starch-films. Corn starch and potato starch along with Fe2+, Mn2+, Cu2+ and Zn2+ ions have been chosen as model starch and mineral ions, respectively. The complexes have been prepared by treating 2% starches with 10% mineral ions. The X-ray powder diffraction and FTIR analyses confirm the starch-mineral complex formation. The maximum mineral loading is 56.5, 68.5, 44 and 15.7 mg of Fe2+, Mn2+, Cu2+ and Zn2+ ions, respectively, per gram of starch. The starch-mineral films have been prepared by mixing 1.4% (w/v) of starch, 0.1% (w/v) starch-mineral complex and 0.5% (w/v) sodium alginate in the presence of 1% (v/v) glycerol and casting films in a petri dish. The films are transparent, thin, flexible and homogeneous. The presence of Mn2+ and Fe2+ ions impart brownish to yellowish tint leading to higher color difference (Δ) and yellowness index (YI) and in turn lower the films transparency. The water solubility and moisture absorption increase substantially compared to the control starch films. The potato starch films possess higher water vapor permeability of 1.8 x10-10 gm-1s-1Pa-1 and tensile strength of 7.76 MPa and increase with mineral ions addition. The starch digestion increases with the presence of mineral ions. The outcome sets the stage for further research on mineral-carbohydrate complexes to develop novel functional foods and to mitigate the micronutrient malnutrition and improve nutritious living

The Interplay of TVET and Formal Education

TVET and formal education have no formal relationship till these days especially in developing countries. In this way, they can’t develop adequate and efficient manpower that are needed for them. We need to establish the relationship between these two methods of education; then only we can produce better manpower. We need to produce transferable manpower by providing both educations to a person. Mainly, traditional practices of TVET models need some improvement as it can’t allow learner to move further to admit in higher education. This article aims to promote both education systems by analyzing it using secondary sources. Keywords: TVET, formal education, transferable skill

Informal settlement segmentation using VHR RGB and height information from UAV imagery: a case study of Nepal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesInformal settlement in developing countries are complex. They are contextually and radiometrically very similar to formal settlement. Resolution offered by Remote sensing is not sufficient to capture high variations and feature size in informal settlements in these situations. UAV imageries offers solution with higher resolution. Incorporating UAV image and normalized DSM obtained from UAV provides an opportunity of including information on 3D space. This can be a crucial factor for informal settlement extraction in countries like Nepal. While formal and informal settlements have similar texture, they differ significantly in height. In this regard, we propose segmentation of informal settlement of Nepal using UAV and normalized DSM, against traditional approach of orthophoto only or orthophoto and DSM. Absolute height, normalized DSM(nDSM) and vegetation index from visual band added to 8 bit RGB channels are used to locate informal settlements. Segmentation including nDSM resulted in 6 % increment in Intersection over Union for informal settlements. IoU of 85% for informal settlement is obtained using nDSM trained end to end on Resnet18 based Unet. Use of threshold value had same effect as using absolute height, meaning use of threshold does not alter result from using absolute nDSM. Integration of height as additional band showed better performance over model that trained height separately. Interestingly, benefits of vegetation index is limited to settlements with small huts partly covered with vegetation, which has no or negative effect elsewhere

Localization of TVET in Developing Countries

TVET stands as an important factor for developing and developed countries equally for the production of skilled manpower in these days. The system of these two countries is quite different while making it systematic. The developed countries have got optimum benefit from it due to adequate development of industries, investment and government policies. However, developing countries have been lagging behind for the implementation of this system. They have lack of budget and policy constrains to develop it in a systematic manner. This article suggests adopting local approach of TVET to institutionalize traditional apprenticeship and RPL into mainstream of education in these countries. Localization of TVET can be a better solution for those countries which have no developed industries, adequate investment and well developed policies. Secondary sources have been used to prepare this article which has analyzed the situations of localization of TVET in developing countries. The developing countries need to recognize their ground-realities that would be better for the promotion of localization. Localization can be a better solution for these countries to access development tasks

Rural Industrialization Through TVET

The perspective of alternative development has been becoming a slogan of all the nations since there was mismatch between urban and rural development. Rural industrialization has become necessary to empower the people of rural areas. A good chunk of population of developing countries has been residing in rural areas practicing traditional skills which have no commercial value. Vocational education can make them able to recognize their possibilities as it is area and need based education. It is imperative to have connection between vocational education and rural industrialization so that people would get more benefit utilizing local/natural resources. The key of development lies in local based industries so that the promotion of such industries would help to increase national economy. Certainly there is high chance of progression of developing countries recognizing and utilizing their potentialities through vocational education. Keywords: rural industrialization, vocational education, formal education, alternative developmen