Location-specific Recommendations Research Articles

Variety × Environment interactions for essential oil yield and cultivar recommendations of lemongrass in drought-prone areas

Lemongrass (Cymbopogon spp.), is a well-known aromatic grass distinguished by its unique lemon scent. The importance of lemongrass in gastronomic, pharmacological, and cosmetic uses is examined in this research paper. The chemical makeup of lemongrass is discussed, emphasizing the presence of citral and other bioactive chemicals that give the herb its flavor, aroma, and medicinal qualities. The study highlights the possible advantages of growing lemongrass in semi-arid areas like Lalitpur (U.P.) and Datia (M.P.) in the Indian state of Bundelkhand, since it may flourish there with little water and improve soil fertility. Five lemongrass varieties—Nima, Praman, CIMAP-Suwarna, Krishna, and CIM-Shikhar—are compared in the study according to their morphological traits, oil yield, herb yield, and citral content. Results demonstrate that the total citral content and essential oil output of the two kinds, LG1 and LG4, are constant between the two genotypes, LG3 and LG5, respectively, across the locations. Regarding the stable types, the location-specific recommendations for essential oil yield were LG1 and LG3, while LG2 and LG4 were suggested for the total citral content. With a few exceptions in the first and second locations, where some traits showed low to medium heritability, most traits in the different sites had broad-sense heritability that was generally high. In all three locations, there were substantial percentages of genetic advance over mean (GAM) for specific features. The retention of genotype stability depends on these characteristics. These cultivars possess advantageous characteristics for growing in the Bundelkhand area, potentially providing farmers with financial gains and improving land in semi-arid regions. The findings highlight the importance of lemongrass as a useful plant with a wide range of applications and aid in the selection of cultivars that are appropriate for a certain area.

Mapping the spatial dimension of food insecurity using GIS-based indicators: A case of Western Kenya

Food insecurity elimination is a major focus of the Sustainable Development Goals and addresses one of the most pressing needs in developing countries. With the increasing incidence of food insecurity, poverty, and inequalities, there is a need for realignment of agriculture that aims to empower especially the rural poor smallholders by increasing productivity to improving food security conditions. Repositioning the agricultural sector should avoid general statements about production improvement, instead, it should tailor to location-specific recommendations that fully acknowledge the local spatial diversity of the natural resource base that largely determines production potentials under current low input agriculture. This paper aims to deconstruct the complex and multidimensional aspect of food insecurity and provides policymakers with an approach for mapping the spatial dimension of food insecurity. Using a set of GIS-based indicators, and a small-area approach, we combine Principal Component Analysis and GIS spatial analysis to construct one composite index and four individual indices based on the four dimensions of food security (access, availability, stability, and utilization) to map the spatial dimension of food insecurity in Vihiga County, Kenya. Data were collected by the use of a geocoded household survey questionnaire. The results reveal the existence of a clear and profound spatial disparity of food insecurity. Mapping food insecurity using individual dimension indices provides a more detailed picture of food insecurity as compared to the single composite index. Spatially disaggregated data, a small area approach, and GIS-based indicators prove valuable for mapping local-level causative factors of household food insecurity. Effective policy approaches to combat food insecurity inequalities should integrate spatially targeted interventions for each dimension of food insecurity.

Disparities in Socio-economic Development in Kerala: A Disaggregated Analysis

The socio-economic development of each district is crucial for the overall development of a State which improves the quality of life of people. In this context, this paper examines the level of development of different districts in Kerala with the help of Weighted Mean Development Index (WMDI). The study covered all fourteen districts of the state. The level of development was examined separately for population, health, education, transportation and communication, industries, agriculture, animal husbandry, tourism, banking, crime and overall socio-economic development using district-level data for the year 2019-20 on forty-five socio-economic indicators including ten major sectors. Findings show that the composite indices of overall socio-economic development ranged between 0.21 and 0.70 with the district of Ernakulam ranked first and the least ranked district was Pathanamthitta. Ernakulam and Thiruvananthapuram were the most developed districts whereas, Kasargode, Wayanad and Pathanamthitta were the least developed. The level of development in different districts of the state has shown wide disparities. It would be useful to investigate and evaluate the level of development at a lower level, such as Tehsil or block level, in order to make location-specific recommendations, as most low-developed districts have areas that are better developed than others.

Planning with justice: Using spatial modelling to incorporate justice in electricity pricing – The case of Tanzania

Universal electrification by 2030 is an important goal of Sustainable Development Goal (SDG) 7. Electricity provision no longer relies only on centralized grid expansion, but also on off-grid and mini-grid systems. Although this technological diversity holds promise, the technologies differ both physically and institutionally in electricity delivery. These differences raise equity and justice concerns around how they are implemented. For example, how can electricity be kept affordable for all consumers when access is provided by various technologies operated under different business models? This paper addresses this aspect of affordability and sheds light on how the SDG7 target could be met more equitably and fairly. We use a novel analytical methodology to apply two different principles of justice – equality and equity – to incorporate affordability into electricity pricing. Using a geospatial electrification model and Tanzania as a case study, we first arrive at price levels based on the principle(s) of justice. Then, we produce location-specific recommendations for subsidy levels needed to ensure those price levels. We find that the equity approach benefits a bigger section of the population than the equality approach. Moreover, the former costs significantly less per capita than the latter. Having said that, the equity approach is complex and therefore harder to implement. The methodological framework proposed in this study acts as a proof-of-concept for examining concerns around distributive justice using quantitative energy modelling tools and drawing policy relevant insights for energy planning in developing countries. Additionally, by focusing on the spatial aspects of energy access and the issue of fairness, the study also contributes to the growing conceptualizations of energy justice.

Pengujian Rekomendasi Pemupukan Spesifik Lokasi dan Sistem Tanam terhadap Hasil Padi Sawah di Desa Temega, Kecamatan Abang, Karangasem

Evaluation of Specific Location Fertilizer Recommendations and Plant System on Rice Yield Temega Village, Abang District, Karangasem. This study aims to determine the response of specific location fertilizer recommendations and planting system on rice yields in Temega Village, Abang District, Karangasem Regency. The method was used Factorial Randomized Block Design (RBD). The treatment tried consisted of two factors. The first factor was fertilization recommendations (R): R1 = location specific recommendation (250 kg Urea/ha, 100 SP36/ha and 50 kg KCl/ha); R2 = Location specific recommendation + Compost (230 kg Urea/ha, 100 SP36/ha, 50 kg KCl/ha + 5 t compost/ha), R3 = Farmer method (300 kg Urea/ha, 125 SP36/ha and 75 kg KCl/ha). The second factor was planting system (TL) : T = Tegel (20 cm x 20 cm) and L = Jajar Legowo 2 : 1. Combination of treatments into 6 treatments and each treatment was replicated 4 times so that there were 24 plots of research. The results showed that location specific fertilizer recommendations resulted in oven dry grain weight m-2 of 0.84 kg compare to that of farmers (0.85 kg). The application of location specific fertilizer recommendations can save as much as 50 kg Urea/ha, 25 kg SP36/ha and 25 kg KCl/ha. Jajar Legowo planting system can produce grain contain m-2 of 1.14 kg or an increase of 78.13% compared to tegel planting system (0.64 kg).

Assessment of CROPGRO-Bellpepper model under different nitrogen levels through fertigation

Application of optimum quantity of nitrogen during the crop growing period is essential for maximizing the yield profit as well as for reducing the environmental pollution. Regional based blanket application of N should be replaced by location specific recommendations for higher productivity and increasing the nitrogen use efficiency. Keeping on this view, the present investigation has been carryout during 2014-2016 to assessment of CROPGRO-Bell pepper model under various nitrogen levels through fertigation in subtropical India at Kharagpur, India. The crop growth model was calibrated and well validated under field condition and later the performance was evaluated at increasing temperature. From the field experiments conducted in two years, it was observed the maximum growth attributes, yield and yield attributes were recorded in N100 kg ha -1 which is significantly higher than the remaining treatments. The sub lethal doses of N levels were at par and the control recorded the lowest values. The crop growth model showed that the effect of increasing temperature upto 1.5°C on crop yield is meagre. Crop performance under controlled condition has to be studied.

Assessment of New Herbicide Programs for Cowpea Production

Cowpea is a major specialty crop in the southern US. In recent years, no new herbicide programs have been evaluated for cowpea despite additional herbicide registrations. Studies were conducted from 2014 to 2016 at Fayetteville and Kibler, Arkansas to assess new herbicide programs for cowpea production. The herbicide programs included: three commercial standard programs; fomesafen (PPL, 0.21 kgha−1)-, flumioxazin (PPL, 0.21 kgha−1)-, and halosulfuron (PPL, 0.054 kgha−1)-based programs with or withoutS-metolachlor (1.12 kgha−1) fb imazethapyr (0.07 kgha−1); and two sets of sulfentrazone (PPL/PRE)-based programs applied alone (0.21 kgha−1) or as a pre-mixture with carfentrazone (0.11 kgha−1+0.01 kgha−1) with or withoutS-metolachlor (1.12 kgha−1). The sulfentrazone-based programs included POST applications of imazethapyr fb sethoxydim (0.32 kgha−1) or fluthiacet-methyl (0.0067 kgha−1) and sethoxydim as necessary. In 2014 and 2015, crop stand loss was minimal and crop injury was generally low (<20%). Weed control from sulfentrazone- and flumioxazin-based programs was excellent (>90%). In 2016, with heavy rainfall around planting time, sulfentrazone-containing programs reduced cowpea yield 45% to 60%. Flumioxazin-based programs caused >85% injury at Kibler early-season, which lasted until harvest. Heavy rainfall also reduced efficacy of residual herbicides. In general, the sulfentrazone- and flumioxazin-based treatments consistently yielded similar to the weed-free controls. The majority of the programs had <60% weed control in Fayetteville early in the season. POST herbicides improved weed control to >90% in most treatments. Palmer amaranth and annual grass control was generally better in Kibler, with >80% control at harvest. Sulfentrazone is registered for cowpea and is effective on Palmer amaranth, but growers need to be careful about where and when to use it. Flumioxazin should be considered for registration in cowpea once its use pattern and location-specific recommendations are well defined.

Forecasting model for Pea seed-borne mosaic virus epidemics in field pea crops in a Mediterranean-type environment

An empirical model was developed to forecast Pea seed-borne mosaic virus (PSbMV) incidence at a critical phase of the annual growing season to predict yield loss in field pea crops sown under Mediterranean-type conditions. The model uses pre-growing season rainfall to calculate an index of aphid abundance in early-August which, in combination with PSbMV infection level in seed sown, is used to forecast virus crop incidence. Using predicted PSbMV crop incidence in early-August and day of sowing, PSbMV transmission from harvested seed was also predicted, albeit less accurately. The model was developed so it provides forecasts before sowing to allow sufficient time to implement control recommendations, such as having representative seed samples tested for PSbMV transmission rate to seedlings, obtaining seed with minimal PSbMV infection or of a PSbMV-resistant cultivar, and implementation of cultural management strategies. The model provides a disease forecast risk indication, taking into account predicted percentage yield loss to PSbMV infection and economic factors involved in field pea production. This disease risk forecast delivers location-specific recommendations regarding PSbMV management to end-users. These recommendations will be delivered directly to end-users via SMS alerts with links to web support that provide information on PSbMV management options. This modelling and decision support system approach would likely be suitable for use in other world regions where field pea is grown in similar Mediterranean-type environments.

Toward A Location Based Service for Assessing and Recommending Landscape Views

GIScience 2016 Short Paper Proceedings Toward A Location Based Service for Assessing and Recommending Landscape Views S. Soleimani 1 , M. R. Malek 1 , G. Sinha 2 Geodesy & Geomatics Department, K.N.Toosi University of Technology, Tehran, Iran Email: {ssoleimani; mrmalek}@kntu.ac.ir Department of Geography, Ohio University, Athens, Ohio, 45701, USA Email: sinhag@ohio.edu Abstract The rationale and initial design considerations are presented for a location based service (LBS) that will offer people personalized recommendations for aesthetically desirable places. This will be based on people’s personal characteristics and environmental factors known to affect landscape perception. A prototype user-interface has been designed for eliciting users’ perceptions of landscape elements and colors they perceive from photographs of landscape views. In the long-term, a VGI repository database will be maintained to make personalized location specific recommendations about suitable landscape views for user-specified locations. A prototype fuzzy logic recommendation system comprising 72 rules has also been designed to model how personal factors (gender, age, health status) and perceived colors likely determine the aesthetic suitability of landscape views. An initial trial revealed some limitations and stressed the need for further testing of the feasibility of fuzzy logic as the reasoning framework for this LBS for recommending suitable landscape views. 1. Introduction As urbanity imposes psychological demands that become excessive, people seek stress- reducing (especially natural) environments where they can recreate and relax. The investigation of the ecological and visual aspects of physical landscapes is critical for understanding and addressing many of the psychosomatic disorders of urban dwellers. In this paper, we focus on visual perception of people’s everyday environments. Human-beings engage in a wide variety of important decisions in their everyday lives, based on visual properties of the geographic environment and their geographical knowledge. Examples include coping with environmental visual pollution, finding one’s way in spatially extended areas, and finding a landscape view appropriate to one’s emotional status. Color, shape, composition, and configuration of objects are important components of visual stimuli that should be studied to understand our perceptions of and reactions to physical landscapes in urban environments. In this short paper, we present the rationale and initial design considerations for a prototype Location Based Service (LBS) for landscape view assessment. This LBS will ultimately offer people personalized recommendations for places (near their chosen location(s)) that are most likely to appeal to them aesthetically. The LBS is designed to make such personalized recommendations based on available knowledge of how people’s personal characteristics affects landscape perception. A prototype user-interface has been designed for eliciting users’ perceptions about the types of landscape elements and the colors they perceive in images showing landscape views. An important goal of this project is to maintain a large database of people’s perception of landscape views, based on volunteered geographic information (VGI) generated from people tagging images uploaded by them and/or others.

Comprehensive analysis of single- and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama

The research described in this paper analyzed injury severities at a disaggregate level for single-vehicle (SV) and multi-vehicle (MV) large truck at-fault accidents for rural and urban locations in Alabama. Given the occurrence of a crash, four separate random parameter logit models of injury severity (with possible outcomes of major, minor, and possible or no injury) were estimated. The models identified different sets of factors that can lead to effective policy decisions aimed at reducing large truck-at-fault accidents for respective locations. The results of the study clearly indicated that there are differences between the influences of a variety of variables on the injury severities resulting from urban vs. rural SV and MV large truck at-fault accidents. The results showed that some variables were significant only in one type of accident model (SV or MV) but not in the other accident model. Again, some variables were found to be significant in one location (rural or urban) but not in other locations. The study also identified important factors that significantly impact the injury severity resulting from SV and MV large truck at-fault accidents in urban and rural locations based on the estimated values of average direct pseudo-elasticity. A careful study of the results of this study will help policy makers and transportation agencies identify location specific recommendations to increase safety awareness related to large truck involved accidents and to improve overall highway safety.

The effect of cultivar, seeding rate and applied nitrogen onBrassica carinataseed yield and quality in contrasting environments

Pan, X., Caldwell, C. D., Falk, K. C. and Lada, R. 2012. The effect of cultivar, seeding rate and applied nitrogen on Brassica carinata seed yield and quality in contrasting environments. Can. J. Plant Sci. 92: 961–971. The unremitting growth of oilseed demand makes it necessary to explore alternative oilseed crops to meet this requirement. This study evaluated the effects of genotype, seeding rate and nitrogen (N) supply on the seed yield and quality of oilseed Brassica carinata A. Braun in three contrasting environments (Truro, NS, Harrington, PE and Saskatoon, SK). Useful genetic variation in agronomic and seed quality characteristics was found among these 10 B. carinata genotypes and genotype selection requires location specific recommendation. Line 050488EM had consistently good yield in both Nova Scotia and Prince Edward Island, while line 070768EM displayed better yield stability across 2 yr in Saskatchewan. Because of the high degree of compensatory ability to low plant population, maximum seed yield of B. carinata can be achieved over the range from 34 to 114 plants m−2. No significant difference in oil and protein content of seed due to seeding rates was observed. The linear increase in seed and oil yield with increased N rate up to 150 kg ha−1indicates that B. carinata is highly responsive to applied N. Increases in N supply resulted in a decrease in oil content and a corresponding increase in protein content in all experiments. In summary, the findings of this study provide convincing evidence of the agronomic adaptation of B. carinata to all three locations.

Linking optimization and ecological models in a decision support tool for oyster restoration and management

Restoration of ecologically important marine species and habitats is restricted by funding constraints and hindered by lack of information about trade-offs among restoration goals and the effectiveness of alternative restoration strategies. Because ecosystems provide diverse human and ecological benefits, achieving one restoration benefit may take place at the expense of other benefits. This poses challenges when attempting to allocate limited resources to optimally achieve multiple benefits, and when defining measures of restoration success. We present a restoration decision-support tool that links ecosystem prediction and human use in a flexible "optimization" framework that clarifies important restoration trade-offs, makes location-specific recommendations, predicts benefits, and quantifies the associated costs (in the form of lost opportunities). The tool is illustrated by examining restoration options related to the eastern oyster, Crassostrea virginica, which supported an historically important fishery in Chesapeake Bay and provides a range of ecosystem services such as removing seston, enhancing water clarity, and creating benthic habitat. We use an optimization approach to identify the locations where oyster restoration efforts are most likely to maximize one or more benefits such as reduction in seston, increase in light penetration, spawning stock enhancement, and harvest, subject to funding constraints and other limitations. This proof-of-concept Oyster Restoration Optimization model (ORO) incorporates predictions from three-dimensional water quality (nutrients-phytoplankton zooplankton-detritus [NPZD] with oyster filtration) and larval transport models; calculates size- and salinity-dependent growth, mortality, and fecundity of oysters; and includes economic costs of restoration efforts. Model results indicate that restoration of oysters in different regions of the Chesapeake Bay would maximize different suites of benefits due to interactions between the physical characteristics of a system and nonlinear biological processes. For example, restoration locations that maximize harvest are not the same as those that would maximize spawning stock enhancement. Although preliminary, the ORO model demonstrates that our understanding of circulation patterns, single-species population dynamics and their interactions with the ecosystem can be integrated into one quantitative framework that optimizes spending allocations and provides explicit advice along with testable predictions. The ORO model has strengths and constraints as a tool to support restoration efforts and ecosystem approaches to fisheries management.

Relationship of driver blood alcohol to injury severity

The research described in this paper analyzed injury severities at a disaggregate level for single-vehicle (SV) and multi-vehicle (MV) large truck at-fault accidents for rural and urban locations in Alabama. Given the occurrence of a crash, four separate random parameter logit models of injury severity (with possible outcomes of major, minor, and possible or no injury) were estimated. The models identified different sets of factors that can lead to effective policy decisions aimed at reducing large truck-at-fault accidents for respective locations. The results of the study clearly indicated that there are differences between the influences of a variety of variables on the injury severities resulting from urban vs. rural SV and MV large truck at-fault accidents. The results showed that some variables were significant only in one type of accident model (SV or MV) but not in the other accident model. Again, some variables were found to be significant in one location (rural or urban) but not in other locations. The study also identified important factors that significantly impact the injury severity resulting from SV and MV large truck at-fault accidents in urban and rural locations based on the estimated values of average direct pseudo-elasticity. A careful study of the results of this study will help policy makers and transportation agencies identify location specific recommendations to increase safety awareness related to large truck involved accidents and to improve overall highway safety.