Search results for: alley cropping

Authors: Kedar Vishnu, Parmod Kumar

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India is becoming most favored retail destination in the world. The organized retail has presented many opportunities to farmers to increase income by shifting cropping pattern from food grains to commercial crops. Previous research revealed potential benefits for farmers by supplying fruits and vegetables to organized retail channels. However the supply of fruits and vegetables from small and marginal farmers remain low than expected. The main objective of this paper is to identify the factors determining market participation of smallholder farmers in modern organized retail chains. Attempt is also made to find out factors influencing the choice of participation in particular organized retail collection centers as compared to other organized retail. The paper was based on primary survey of 40 Beans and Tomato farmers who supply to organized retail collection centers from Karnataka, India. Multiple regression technique is used to identify the factors determining quantity sold at collection centers. The regression result, show that area under vegetables, yield, and price from modern collection center and having access to technical help were found significantly affecting quantity sold into modern organized retail channels. On the opposite, increased rejection rates and vegetable prices at APMC were found influencing farmers decision into the reverse side. Empirical result of the multinomial logit model show that Reliance fresh has tendency to prefer large farmers who can supply more quality and better quantity compared with TESCO and More collection centers. The negative sign of area, having access to technical help, transportation cost, and number of bore wells led to higher probability of farmers to participate in Reliance Fresh collection centers as compared with More and TESCO.

Keywords: fruits, vegetables, organized retail markets, multinomial logit model

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Authors: Muhammad Sohail Sajid, Hafiz Muhammad Rizwan, Ashfaq Ahmad Chatta, Zafar Iqbal, Muhammad Saqib

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Changes in the climate are posing threats to the livestock community throughout the globe. Agro-grazing animals and natural vegetation as their forages are the most important components of animal production. Climate and local conditions not only determine the nature and kind of plants, their distribution, composition and nutritive value in different cropping belts and grazing sites but also influence number and kinds of grazing animals. Phytomineral supplementation can act as an indirect tool to boost-up immunological profile of animals leading to the development of resilience against parasitic infections. The present study correlates the trace element (Cu, Co, Mn, Zn) profile of grazing sheep, feedstuffs, respective soils and their GI helminths in a selected district of Sialkot, Punjab, Pakistan. Ten species of GI helminths were found during the survey. A significant (P < 0.05) variation in the concentrations (conc.) of Zn, Cu, Mn and Co was recorded in a total of 16 collected forages. During autumn, mean conc. of Cu, Zn and Co in sera were inversely proportional to the GI helminth burden; while, during spring, only Zn was inversely proportional to the GI helminth burden in grazing sheep. During autumn the highest conc. of Zn, Cu, Mn and Co were recorded in Echinochloa colona, Amaranthus viridis, Cannabis sativa, and Brachiaria ramose and during spring in Cichorium intybus, Cynodon dactylon, Parthenium hysterophorus and Coronopus didymus respectively. The trace element-rich forages, preferably Zn, found effective against helminth infection are advisable supplemental remedies to improve the trace element profile in grazing sheep. This mitigation strategy may ultimately improve the resilience against GI helminth infections especially in the resource poor countries like Pakistan.

Keywords: coprological examination, Trace elements, Sheep, Gastro-intestinal parasites, Prevalence, Sialkot, Pakistan

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Authors: S. K. Kakraliya, H. S. Jat, Manish Kakraliya, P. C. Sharma, M. L. Jat

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The biggest challenge in agriculture is to produce more food for the continually increasing world population with in the limited land and water resources. Serious water deficits and reducing natural resources are some of the major threats to the agricultural sustainability in many regions of South Asia. Food and water security may be gained by bringing improvement in the crop water productivity and the amount produced per unit of water consumed. Improvement in the crop water productivity may be achieved by pursuing alternative modern agronomics approaches, which are more friendly and efficient in utilizing natural resources. Therefore, a research trial on conservation agriculture (CA) and precision water management (PWM) was conducted in 2018-19 at Karnal, India to evaluate the effect on crop productivity and irrigation in sodic soils under rice-wheat (RW) systems of Indo-Gangetic Plains (IGP). Eight scenarios were compared varied in the tillage, crop establishment, residue and irrigarion management i.e., {First four scenarios irrigated with flood irrigation method;Sc1-Conventional tillage (CT) without residue, Sc2-CT with residue, Sc3- Zero tillage (ZT) without residue, Sc4-ZT with residue}, and {last four scenarios irrigated with sub-surface drip irrigation method; Sc5-ZT without residue, Sc6- ZT with residue, Sc7-ZT inclusion legume without residue and Sc8- ZT inclusion legume with residue}. Results revealed that CA-flood irrigation (S3, Sc4) and CA-PWM system (Sc5, Sc6, Sc7 and Sc8) recorded about ~5% and ~15% higher wheat yield, respectively compared to Sc1. Similar, CA-PWM saved ~40% irrigation water compared to Sc1. Rice yield was not different under different scenarios in the first year (kharif 2019) but almost half irrigation water saved under CA-PWM system. Therefore, results of our study on modern agronomic practices including CA and precision water management (subsurface drip irrigation) for RW rotation would be addressed the existing and future challenges in the RW system.

Keywords: Sub-surface drip, Crop residue, Crop yield , Zero tillage

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Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

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Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

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Authors: Fitih Ademe, Kibebew Kibret, Sheleme Beyene, Mezgebu Getnet, Gashaw Meteke

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Changes in precipitation, temperature and atmospheric CO2 concentration are expected to alter agricultural productivity patterns worldwide. The interactive effects of soil moisture and nutrient availability are the two key edaphic factors that determine crop yield and are sensitive to climatic changes. The study assessed the potential impacts of climate change on maize yield and corresponding water productivity and nutrient use efficiency under climate change scenarios for the Central Rift Valley of Ethiopia by mid (2041-2070) and end century (2071-2100). Projected impacts were evaluated using climate scenarios generated from four General Circulation Models (GCMs) dynamically downscaled by the Swedish RCA4 Regional Climate Model (RCM) in combination with two Representative Concentration Pathways (RCP 4.5 and RCP8.5). Decision Support System for Agro-technology Transfer cropping system model (DSSAT-CSM) was used to simulate yield, water and nutrient use for the study periods. Results indicate that rainfed maize yield might decrease on average by 16.5 and 23% by the 2050s and 2080s, respectively, due to climate change. Water productivity is expected to decline on average by 2.2 and 12% in the CRV by mid and end centuries with respect to the baseline. Nutrient uptake and corresponding nutrient use efficiency (NUE) might also be negatively affected by climate change. Phosphorus uptake probably will decrease in the CRV on average by 14.5 to 18% by 2050s, while N uptake may not change significantly at Melkassa. Nitrogen and P use efficiency indicators showed decreases in the range between 8.5 to 10.5% and between 9.3 to 10.5%, respectively, by 2050s relative to the baseline average. The simulation results further indicated that a combination of increased water availability and optimum nutrient application might increase both water productivity and nutrient use efficiency in the changed climate, which can ensure modest production in the future. Potential options that can improve water availability and nutrient uptake should be identified for the study locations using a crop modeling approach.

Keywords: crop model, climate change scenario, nutrient uptake, nutrient use efficiency, water productivity

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Authors: Nwogiji Cletus Olando, Oselebe Happiness Ogba, Enoch Achigan-Dako

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Digitaria iburua, commonly known as black fonio, is a cereal crop native to Africa and extensively cultivated by smallholder farmers in Northern Benin, Togo, and Nigeria. This crop holds immense nutritional and socio-cultural value. Unfortunately, limited knowledge about its genetic diversity exists due to a lack of scientific attention. As a result, its potential for improvement in food and agriculture remains largely untapped. To address this gap, a study was conducted using 41 accessions of D. iburua stored in the genebank of the Laboratory of Genetics, Biotechnology, and Seed Science at Abomey-Calavi University, Benin. The study employed both morphological and simple sequence repeat (SSR) markers to evaluate the genetic variability of the accessions. Agro-morphological assessments were carried out during the 2020 cropping season, utilizing an alpha lattice design with three replications. The collected data encompassed qualitative and quantitative traits. Additionally, molecular variability was assessed using eleven SSR markers. The results revealed significant phenotypic variability among the evaluated accessions, leading to their classification into three main clusters. Furthermore, the eleven SSR markers identified a total of 50 alleles, averaging 4.55 alleles per locus. The primers exhibited an average polymorphic information content value of 0.43, with the DE-ARC019 primer displaying the highest value (0.59). These findings suggest a substantial degree of genetic heterogeneity within the evaluated accessions, and the SSR markers employed in the study proved highly effective in detecting and characterizing this genetic variability. In conclusion, this study highlights the presence of significant genetic diversity in black fonio and provides valuable insights for future efforts aimed at its genetic improvement and conservation.

Keywords: genetic diversity, digitaria iburua, genetic improvement, simple sequence repeat markers, Nigeria, conservation

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Authors: Ngoc-Hieu Vu

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Although dairy production in Vietnam is a relatively new agricultural activity, milk production increased remarkably in recent years. Smallholders are still the main drivers for this development, especially in the southern part of the country. However, information on the farming practices is very limited. Therefore, this study aimed to characterize husbandry practices, educational experiences, decision-making practices, constraints, income and expenses of smallholder dairy farms in Southern Vietnam. A total of 200 farms, located in the regions Ho Chi Minh (HCM, N=80 farms), Lam Dong (N=40 farms), Binh Duong (N=40 farms) and Long An (N=40 farms) were included. Between October 2013 and December 2014 farmers were interviewed twice. On average, farms owned 3.200m2, 2.000m2, and 193m2 of pasture, cropping and housing area, respectively. The number of total, milking and dry cows, heifers, and calves were 20.4, 11.6, 4.7, 3.3, and 2.9 head. The number of lactating dairy cows was higher (p<0.001) in HCM (15.5) and Lam Dong (14.7) than in Binh Duong (6.7) and Long An (10.7). Animals were mainly crossbred Holstein-Friesian (HF) cows with at least 75% HF origin (84%), whereas a higher (P<0.001) percentage of purebred HF was found in HCM and Lam Dong and crossbreds in Binh Duong and Long An. Animals were mainly raised in tie-stalls (94%) and machine-milked (80%). Farmers used their own replacement animals (76%), and both genetic and phenotypic information (67%) for selecting sires. Farmers were predominantly educated at primary school level (53%). Major constraints for dairy farming were the lack of capital (43%), diseases (17%), marketing (22%), lack of knowledge (8%) and feed (7%). Monthly profit per lactating cow was superior in Lam Dong (2,817 thousand VND) and HCM (2,798 thousand VND) compared to other regions in Long An (2,597 thousand VND), and Binh Duong (1,775 thousand VND). Regional differences may be mainly attributed to environmental factors, urbanization, and particularly governmental support and the availability of extension and financial institutions. Results from this study provide important information on farming practices of smallholders in Southern Vietnam that are useful in determining regions that need to be addressed by authorities in order to improve dairy production.

Keywords: dairy farms, milk yield, Southern Vietnam, socio-economics

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Authors: Thapa M., J.P. Dutta, K.R. Pandey, R.R. Kattel

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Nepal is extremely vulnerable to the impact of climate change. To mitigate the climate change effects on agricultural production and productivity a range of adaptive strategies needs to be considered. The study was conducted to assess organic paddy production as a coping strategy to the adverse impact of climate change in Phulbari, VDC of Chitwan district. Altogether, 120 respondents (60 adopters of organic farming and 60 from non adopter) were selected using snowball technique of sampling. Pre- tested interview schedule, direct observation, focus group discussion, key informant interview as well as secondary data were used to collect the required information. Factors determining the adoption of organic farming were found to be age, year of schooling, training, frequency of extension contact, perception about climate change, economically active members and poor. A unit increase in these factors except poor would increase the probability of adoption by 4.1%, 7.5%, 7.8%, 43.1%, 41.8% and 7% respectively. However, for poor, it would decrease the probability of adoption of organic farming by 5.1%. Average organic matter content in the adopters' field was higher (2.7%) than the non-adopters' field (2.5%). The regression result showed that type of farmer, price and area under rice cultivation had positive and significant relationship with income; however dependency ratio had negative relationship. As the year of adoption of organic farming increases, the production of rice decline in the first two years then after goes on increasing but the cost of production goes on decreasing with the year of adoption. The respondents adapted to the changing climate through diversification of crops, use of resistance varieties and following good cropping pattern. Gradually growing consumers' awareness about health, preference towards quality food products are the strong points behind organic farming, whereas lacks of bio-fertilizers, lack of effective extension services, no price differentiation between organic and inorganic products were the weak points. There is need for more training and education to change the attitude of farmers and enhance their confidence about the role of organic farming to cope with climate change impact.

Keywords: Organic farming, climate change, sustainable development

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Neelam Patel

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Farmers in peri-urban areas of developing countries depend on wastewater for Irrigation but with great environmental and health hazards. Since, irrigation with wastewater is growing in the developing countries but its suitability to environment and other health factors should be checked. Metal pollution is a very serious issue these days, various neuro, physical and mental disorders are prevailing due to the metal pollution. Waste water contaminated with heavy metals got accumulated in the soil and then bioaccumulated in the vegetables irrigated with waste water. A 3-year field experiment on cauliflower has been done by using wastewater with two different methods of irrigation i.e. Drip and Flood irrigation and checked the impact on the cauliflower and soil quality. Heavy metals (Cr, Cu, Ni, Zn and Pb) have been studied in wastewater used for the irrigation and their accumulation in the soil and vegetable was studied. The study reveals that the concentration of heavy metals increases by 100 times from initial in soil. After 3 years, the concentration of Copper(41 ppm) Chromium(39.4 ppm) Lead(62.2ppm) Zinc(100.5 ppm) and Nickel(75.7 ppm) in Flood irrigated soil while in Drip irrigated soil , Copper (36.4 ppm) Chromium(36.8 ppm) Lead(53.7 ppm) Zinc(70.3 ppm) and Nickel (53.9 ppm). In vegetable, the wastewater irrigated shows an increase in the concentration of metals with the time and the accumulation of Nickel (6.98ppm), Lead (30.18 ppm) and Zinc (55.83 ppm) in drip irrigated while in flood irrigated, Nickel (30.58 ppm), Lead (73.95ppm) Zinc (93.50 ppm) and Copper (54.58 ppm) in edible part of cauliflower which is above the permissible limits suggested by different international agencies. On other hand, the nutrients content i.e. Nitrogen, Phosphorus and Potassium in soil was increased in concentration with time. The study pointed out that the metal contaminated waste water consisting the nutrients in it but also heavy metals which causes health issues in human. While the increase in concentration of nutrients in the soil indirectly helpful to the farmers economically by restricting the use of fertilizers. But the metal pollution directly affects the health of human being. The different method of irrigation suggested that the drip irrigated vegetable acquired less metal then the flood one and is a better combo with the waste water for the irrigation.

Keywords: drip irrigation, heavy metals, metal contamination, waste water

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Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

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large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

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Authors: V. S. Manivasagam, R. Nagarajan

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Modeling the soil, water and crop growth interactions are attaining major importance, considering the future climate change and water availability for agriculture to meet the growing food demand. Progress in understanding the crop growth response during water stress period through crop modeling approach provides an opportunity for improving and sustaining the future agriculture water use efficiency. An attempt has been made to evaluate the potential use of crop modeling approach for assessing the minimal supplementary irrigation requirement for crop growth during water limited condition and its practical significance in sustainable improvement of crop yield and water productivity. Among the numerous crop models, water driven-AquaCrop model has been chosen for the present study considering the modeling approach and water stress impact on yield simulation. The study has been evaluated in rainfed maize grown area of semi-arid Shanmuganadi watershed (a tributary of the Cauvery river system) located in southern India during the rabi cropping season (October-February). In addition to actual rainfed maize growth simulation, irrigated maize scenarios were simulated for assessing the supplementary irrigation requirement during water shortage condition for the period 2012-2015. The simulation results for rainfed maize have shown that the average maize yield of 0.5-2 t ha-1 was observed during deficit monsoon season (<350 mm) whereas 5.3 t ha-1 was noticed during sufficient monsoonal period (>350 mm). Scenario results for irrigated maize simulation during deficit monsoonal period has revealed that 150-200 mm of supplementary irrigation has ensured the 5.8 t ha-1 of irrigated maize yield. Thus, study results clearly portrayed that minimal application of supplementary irrigation during the critical growth period along with the deficit rainfall has increased the crop water productivity from 1.07 to 2.59 kg m-3 for major soil types. Overall, AquaCrop is found to be very effective for the sustainable irrigation assessment considering the model simplicity and minimal inputs requirement.

Keywords: AquaCrop, crop modeling, rainfed maize, water stress

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Authors: K. O. Ogbedeh, T. T. Epidi, E. U. Onweremadu, E. E. Ihem

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Apart from the devastating nature of termites as pest of cassava, nearly all termite species have been implicated in soil fertility modifications. Elasticity of soil fertility indicators and pH in termite infested cassava field as influenced by tillage and organic manure sources in Owerri, Southeast, Nigeria was investigated in this study. Three years of of field trials were conducted in 2007, 2008 and 2009 cropping seasons respectively at the Teaching and Research Farm of the Federal University of Technology, Owerri. The experiments were laid out in a 3x6 split-plot factorial arrangement fitted into a randomized complete block design (RCBD) with three replications. The TMS 4 (2)1425 was the cassava cultivar used. Treatments consists three tillage methods (zero, flat and mound), two rates of municipal waste (1.5 and 3.0tonnes/ha), two rates of Azadirachta indica (neem) leaves (20 and 30tonnes/ha), control (0.0 tonnes/ha) and a unit dose of carbofuran (chemical check). Data were collected on pre-planting soil physical and chemical properties, post-harvest soil pH (both in water and KCl) and residual total exchangeable bases (Ca, K, Mg and Na). These were analyzed using a Mixed-model procedure of Statistical Analysis Software (SAS). Means were separated using Least Significant Difference (LSD.) at 5% level of probability. Result shows that the native soil fertility status of the experimental site was poor. However soil pH increased substantially in plots where mounds, A.indica leaves at 30t/ha and municipal waste (1.5 and 3.0t/ha) were treated especially in 2008 and 2009. In 2007 trial, highest soil pH was maintained with flat (5.41 in water and 4.97 in KCl). Control on the other hand, recorded least soil pH especially in 2009 with values of 5.18 and 4.63 in water and KCl respectively. Equally, mound, A. indica leaves at 30t/ha and municipal waste at 3.0t/ha consistently increased organic matter content of the soil than other treatments. Finally, mound and A. indica leaves at 30t/ha linearly and consistently increased residual total exchangeable bases of the soil.

Keywords: elasticity, fertility, indicators, termites, tillage, cassava and manure sources

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Authors: Fitih Ademe, Kibebew Kibret, Sheleme Beyene, Mezgebu Getnet, Gashaw Meteke

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Soil moisture and nutrient availability are the two key edaphic factors that affect crop yields and are directly or indirectly affected by climate variability and change. The study examined climate-induced yield level, yield variability and gap of maize during 1981-2010 main growing season in the Central Rift Valley (CRV) of Ethiopia. Pearson correlation test was employed to see the relationship between climate variables and yield. The coefficient of variation (CV) was used to analyze annual yield variability. Decision Support System for Agro-technology Transfer cropping system model (DSSAT-CSM) was used to simulate the growth and yield of maize for the study period. The result indicated that maize grain yield was strongly (P<0.01) and positively correlated with seasonal rainfall (r=0.67 at Melkassa and r = 0.69 at Ziway) in the CRV while day temperature affected grain yield negatively (r= -0.44) at Ziway (P<0.05) during the simulation period. Variations in total seasonal rainfall at Melkassa and Ziway explained 44.9 and 48.5% of the variation in yield, respectively, under optimum nutrition. Following variation in rainfall, high yield variability (CV=23.5%, Melkassa and CV=25.3%, Ziway) was observed for optimum nutrient simulation than the corresponding nutrient limited simulation (CV=16%, Melkassa and 24.1%, Ziway) in the study period. The observed farmers’ yield was 72, 52 and 43% of the researcher-managed, water-limited and potential yield of the crop, respectively, indicating a wide maize yield gap in the region. The study revealed rainfed crop production in the CRV is prone to yield variabilities due to its high dependence on seasonal rainfall and nutrient level. Moreover, the high coefficient of variation in the yield gap for the 30-year period also foretells the need for dependable water supply at both locations. Given the wide yield gap especially during lower rainfall years across the simulation periods, it signifies the requirement for a more dependable application of irrigation water and a potential shift to irrigated agriculture; hence, adopting options that can improve water availability and nutrient use efficiency would be crucial for crop production in the area.

Keywords: climate variability, crop model, water availability, yield gap, yield variability

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Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu, Tigray

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Sesame is an important oilseed crop in Ethiopia; which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool; which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validated the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates; 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99; and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99, and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, sesame, normalized water productivity, nitrogen fertilizer

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Authors: Hussien Ali, Mesfin Menza, Fitsum Hagos, Amare Haileslassie

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Climate change has perverse effects on agricultural productivity and natural resource base, negatively affecting the well-being of the households and communities. The government and NGOs promote climate smart agricultural (CSA) practices to help farmers adapt to and mitigate the negative effects of climate change. This study aims to identify widely available CSA practices and examine their impacts on food security and multi-dimensional poverty of rural farm households in the Central Rift Valley, Ethiopia. Using three-stage proportional to size sampling procedure, the study randomly selected 278 households from two kebeles from four districts each. A cross-sectional data of 2020/21 cropping season was collected using structured and pretested survey questionnaire. Food consumption score, dietary diversity score, food insecurity experience scale, and multidimensional poverty index were calculated to measure households’ welfare indicators. Multinomial endogenous switching regression model was used to assess average treatment effects of CSA on these outcome indicators on adopter and non-adopter households. The results indicate that the widely adopted CSA practices in the area are conservation agriculture, soil fertility management, crop diversification, and small-scale irrigation. Adopter households have, on average, statistically higher food consumption score, dietary diversity score and lower food insecurity access scale than non-adopters. Moreover, adopter households, on average, have lower deprivation score in multidimensional poverty compared to non-adopter households. Up scaling the adoption of CSA practices through the improvement of households’ implementation capacity and better information, technical advice, and innovative financing mechanisms is advised. Up scaling CSA practices can further promote achieving global goals such as SDG 1, SDG 2, and SDG 13 targets, aimed to end poverty and hunger and mitigate the adverse impacts of climate change, respectively.

Keywords: climate-smart agriculture, food security, multidimensional poverty, upscaling CSA, Ethiopia

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Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu

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Sesame is an important oilseed crop in Ethiopia, which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool, which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validate the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates, 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99, and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99 and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, normalized water productivity, nitrogen fertilizer, canopy cover, sesame

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Authors: Ufuk Tosun, Reza Aghazadeh, Mehmet Bülent Özer

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This study puts forward a method to analyze the sloshing characteristics of liquid in a tuned sloshing absorber system by using image processing tools. Tuned sloshing vibration absorbers have recently attracted researchers’ attention as a seismic load damper in constructions due to its practical and logistical convenience. The absorber is liquid which sloshes and applies a force in opposite phase to the motion of structure. Experimentally characterization of the sloshing behavior can be utilized as means of verifying the results of numerical analysis. It can also be used to identify the accuracy of assumptions related to the motion of the liquid. There are extensive theoretical and experimental studies in the literature related to the dynamical and structural behavior of tuned sloshing dampers. In most of these works there are efforts to estimate the sloshing behavior of the liquid such as free surface motion and total force applied by liquid to the wall of container. For these purposes the use of sensors such as load cells and ultrasonic sensors are prevalent in experimental works. Load cells are only capable of measuring the force and requires conducting tests both with and without liquid to obtain pure sloshing force. Ultrasonic level sensors give point-wise measurements and hence they are not applicable to measure the whole free surface motion. Furthermore, in the case of liquid splashing it may give incorrect data. In this work a method for evaluating the sloshing wave height by using camera records and image processing techniques is presented. In this method the motion of the liquid and its container, made of a transparent material, is recorded by a high speed camera which is aligned to the free surface of the liquid. The video captured by the camera is processed frame by frame by using MATLAB Image Processing toolbox. The process starts with cropping the desired region. By recognizing the regions containing liquid and eliminating noise and liquid splashing, the final picture depicting the free surface of liquid is achieved. This picture then is used to obtain the height of the liquid through the length of container. This process is verified by ultrasonic sensors that measured fluid height on the surface of liquid.

Keywords: fluid structure interaction, image processing, sloshing, tuned liquid damper

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Authors: Zeenat Rupawalla, Nicole Robinson, Susanne Schmidt, Sijie Li, Selina Carruthers, Elodie Buisset, John Roles, Ben Hankamer, Juliane Wolf

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Agriculture has radically changed the global biogeochemical cycle of nitrogen (N). Fossil fuel-enabled synthetic N-fertiliser is a foundation of modern agriculture but applied to soil crops only use about half of it. To address N-pollution from cropping and the large carbon and energy footprint of N-fertiliser synthesis, new technologies delivering enhanced energy efficiency, decarbonisation, and a circular nutrient economy are needed. We characterised algae fertiliser (AF) as an alternative to synthetic N-fertiliser (SF) using empirical and modelling approaches. We cultivated microalgae in nutrient solution and modelled up-scaled production in nutrient-rich wastewater. Over four weeks, AF released 63.5% of N as ammonium and nitrate, and 25% of phosphorous (P) as phosphate to the growth substrate, while SF released 100% N and 20% P. To maximise crop N-use and minimise N-leaching, we explored AF and SF dose-response-curves with spinach in glasshouse conditions. AF-grown spinach produced 36% less biomass than SF-grown plants due to AF’s slower and linear N-release, while SF resulted in 5-times higher N-leaching loss than AF. Optimised blends of AF and SF boosted crop yield and minimised N-loss due to greater synchrony of N-release and crop uptake. Additional benefits of AF included greener leaves, lower leaf nitrate concentration, and higher microbial diversity and water holding capacity in the growth substrate. Life-cycle-analysis showed that replacing the most effective SF dosage with AF lowered the carbon footprint of fertiliser production from 2.02 g CO₂ (C-producing) to -4.62 g CO₂ (C-sequestering), with a further 12% reduction when AF is produced on wastewater. Embodied energy was lowest for AF-SF blends and could be reduced by 32% when cultivating algae on wastewater. We conclude that (i) microalgae offer a sustainable alternative to synthetic N-fertiliser in spinach production and potentially other crop systems, and (ii) microalgae biofertilisers support the circular nutrient economy and several sustainable development goals.

Keywords: bioeconomy, decarbonisation, energy footprint, microalgae

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Authors: Garima Sharma, R. N. Sharma

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Integrated watershed management programme based on 'Four Water Concept' was implemented in Sali village, in Jaipur District, Rajasthan State of India . The latitude 26.7234486 North and longitude 75.023876 East are the geocoordinate of the Sali. 'Four Waters Concept' is evolved by integrating the 'Four Waters', viz. rain water, soil moisture, ground water and surface water This methodology involves various water harvesting techniques to prevent the runoff of water by treatment of catchment, proper utilization of available water harvesting structures, renovation of the non-functional water harvesting structures and creation of new water harvesting structures. The case study included questionnaire survey from farmers and continuous study of village for two years. The total project area is 6153 Hac, and the project cost is Rs. 92.25 million. The sanctioned area of Sali Micro watershed is 2228 Hac with an outlay of Rs. 10.52 million. Watershed treatment activities such as water absorption trench, continuous contour trench, field bunding, check dams, were undertaken on agricultural lands for soil and water conservation. These measures have contributed in preventing runoff and increased the perennial availability of water in wells. According to the survey, water level in open wells in the area has risen by approximately 5 metres after the introduction of water harvesting structures. The continuous availability of water in wells has increased the area under irrigation and helped in crop diversification. Watershed management activities have brought the changes in cropping patterns and crop productivity. It helped in transforming 567 Hac culturable waste land into culturable arable land in the village. The farmers of village have created an additional income from the increased crop production. The programme also assured the availability of water during peak summers for the day to day activities of villagers. The outcomes indicate that there is positive impact of watershed management practices on the water resource potential as well the crop production of the area. This suggests that persistent efforts in this direction may lead to sustainability of the watershed.

Keywords: four water concept, groundwater potential, irrigation potential, watershed management

Procedia PDF Downloads 319

Authors: M. Saleem, M. Shahnawaz, A. W. Gandahi, S. M. Bhatti

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The micronutrients boron and zinc deficiencies are extensive in the areas of rice-wheat cropping system. Optimum levels of these nutrients in soil are necessary for healthy crop growth. Since rice and wheat are major staple food of worlds’ populace, the higher yields and nutrition status of these crops has direct effect on the health of human being and economy of the country. A field study was conducted to observe the direct and residual effect of two selected micronutrients boron (B) and zinc (Zn)) on rice and wheat crop growth and its grain nutrient status. Each plot received either B or Zn at the rates of 0, 1, 2, 3 and 4 kg B ha⁻¹, and 5, 10, 15 and 20 kg Zn ha⁻¹, combined B and Zn application at 1 kg B and 5 kg Zn ha⁻¹, 2 kg B and 10 kg Zn ha⁻¹. Colemanite ore were used as source of B and zinc sulfate for Zn. The second season wheat crop was planted in the same plots after the interval period of 30 days and during this time gap soil was fallow. Boron and Zn application significantly enhanced the plant height, number of tillers, Grains panicle⁻¹ seed index fewer empty grains panicle⁻¹ and yield of rice crop at all defined levels as compared to control. The highest yield (10.00 tons/ha) was recorded at 2 Kg B, 10 Kg Zn ha⁻¹ rates. Boron and Zn concentration in grain and straw significantly increased. The application of B also improved the nutrition status of rice as B, protein and total carbohydrates content of grain augmented. The analysis of soil samples collected after harvest of rice crop showed that the B and Zn content in post-harvest soil samples was high in colemanite and zinc sulfate applied plots. The residual B and Zn were also effectual for the second season wheat crop, as the growth parameters plant height, number of tillers, earhead length, weight 1000 grains, B and Zn content of grain significantly improved. The highest wheat grain yield (4.23 tons/ha) was recorded at the residual rates of 2 kg B and 10 kg Zn ha⁻¹ than the other treatments. This study showed that one application of B and Zn can increase crop yields for at least two consecutive seasons and the mineral colemanite can confidently be used as source of B for rice crop because very small quantities of these nutrients are consumed by first season crop and remaining amount was present in soil which were used by second season wheat crop for healthy growth. Consequently, there is no need to apply these micronutrients to the following crop when it is applied on the previous one.

Keywords: residual boron, zinc, rice, wheat

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Authors: Misheck Musokwa, Paramu Mafongoya, Simon Lorentz

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Seasonal shortages of fodder during the dry season is a major constraint to smallholder livestock farmers in South Africa. To mitigate the shortage of fodder, legume trees can be intercropped with pastures which can diversify the sources of feed and increase the amount of protein for grazing animals. The objective was to evaluate dry matter yield of Panicum maximum and land productivity under different fodder production systems during 2016/17-2017/18 seasons at Empangeni (28.6391° S and 31.9400° E). A randomized complete block design, replicated three times was used, the treatments were sole Panicum maximum, Panicum maximum + Sesbania sesban, Panicum maximum + pigeonpea, sole Sesbania sesban, Sole pigeonpea. Three months S.sesbania seedlings were transplanted whilst pigeonpea was direct seeded at spacing of 1m x 1m. P. maximum seeds were drilled at a respective rate of 7.5 kg/ha having an inter-row spacing of 0.25 m apart. In between rows of trees P. maximum seeds were drilled. The dry matter yield harvesting times were separated by six months’ timeframe. A 0.25 m² quadrant randomly placed on 3 points on the plot was used as sampling area during harvesting P. maximum. There was significant difference P < 0.05 across 3 harvests and total dry matter. P. maximum had higher dry matter yield as compared to both intercrops at first harvest and total. The second and third harvest had no significant difference with pigeonpea intercrop. The results was in this order for all 3 harvest: P. maximum (541.2c, 1209.3b and 1557b) kg ha¹ ≥ P. maximum + pigeonpea (157.2b, 926.7b and 1129b) kg ha¹ > P. maximum + S. sesban (36.3a, 282a and 555a) kg ha¹. Total accumulation of dry matter yield of P. maximum (3307c kg ha¹) > P. maximum + pigeonpea (2212 kg ha¹) ≥ P. maximum + S. sesban (874 kg ha¹). There was a significant difference (P< 0.05) on seed yield for trees. Pigeonpea (1240.3 kg ha¹) ≥ Pigeonpea + P. maximum (862.7 kg ha¹) > S.sesbania (391.9 kg ha¹) ≥ S.sesbania + P. maximum. The Land Equivalent Ratio (LER) was in the following order P. maximum + pigeonpea (1.37) > P. maximum + S. sesban (0.84) > Pigeonpea (0.59) ≥ S. Sesbania (0.57) > P. maximum (0.26). Results indicates that it is beneficial to have P. maximum intercropped with pigeonpea because of higher land productivity. Planting grass with pigeonpea was more beneficial than S. sesban with grass or sole cropping in terms of saving the shortage of arable land. P. maximum + pigeonpea saves a substantial (37%) land which can be subsequently be used for other crop production. Pigeonpea is recommended as an intercrop with P. maximum due to its higher LER and combined production of livestock feed, human food, and firewood. Panicum grass is low in crude protein though high in carbohydrates, there is a need for intercropping it with legume trees. A farmer who buys concentrates can reduce costs by combining P. maximum with pigeonpea this will provide a balanced diet at low cost.

Keywords: fodder, livestock, productivity, smallholder farmers

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Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

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Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

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Authors: Anu Krishna

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Cardamom Hills geographically falls into the Western Ghat region in the state of Kerala (India). The fame of these hills dates back to antiquity as the abode of various indigenous communities and treasure house of spices like cardamom. With the colonial conquest over the region, the evergreen forests got converted into zones of mono-cropping with commercial crops such as coffee, tea, cardamom etc. on plantation basis; a process which has been further accentuated with the migration of settlers during the post-independent times. Curiously, when Cardamom Hills are better known today as the plantation belt of the country or as one of the most fostering grounds of agrarian capitalism producing the lion share of Indian cardamom, the indigenous communities of the place such as the Mannans got alienated of their ancestral lands, became inter-generational proletariats and got reduced into ‘segmented spaces’ called the settlements. While dispossession of land for plantations has dislocated the economic life of the Mannans, the migration of the settlers has resulted into a complete social, cultural, political and demographic dominion over them. This has not only relegated their existential relations, history, culture and association with the place but also condensed them as the ‘Other’ in their own territories. Therefore inquisitively, violation of rights of the communities like Mannans, encroachment of their lands, negation towards their very existence and distortion of their history gets defined as the ‘Manifest Destiny’ of the people and place whereby its inevitability gets manufactured. This paper is an attempt to elicit the ways in which the formation of Mannan settlements are interconnected to the historical reality and contemporary opulence of the plantation industry in the place. The arguments put forth by this study is based on extensive ethnographic fieldwork conducted in various Mannan settlements in the cardamom hills. The study basically dwells on to the methodological premises of multi-sited ethnography wherein information was gathered from different sites such as settlements, plantations and other interactive spaces wherein the Mannans from the settlements engages in socio-economic, cultural and political relations. Such an attempt was made to understand in depth the associations and interactions that people in the settlements have among themselves and others. The study equally uses the method of oral history to understand the alternative history, the socio-cultural and economic life of the people before the importation of plantations to the place. The paper gauges into the ways in which settlements imprisons generations of Mannans into plantation work and acts as moulds for subservient, hardworking plantation labourers.

Keywords: Cardamom Hills, plantations, labourers, Mannans, segmented spaces, settlements

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Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

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Authors: Mohsen Rabbani, Trista McLaughlin, Ehsan Vahidi

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the remediation of polluted sites with heavy metals, such as rare earth elements (REEs), has been a primary concern of researchers to decontaminate the soil. Among all developed methods to address this concern, phytoremediation has been established as efficient, cost-effective, easy-to-use, and environmentally friendly way, providing a long-term solution for addressing this global concern. Furthermore, this technology has another great potential application in the metals production sector through returning metals buried in soil via metals cropping. Considering the significant metal concentration in hyper-accumulators, the utilization of bioaccumulated metals to extract metals from plant matter has been proposed as a sub-economic area called phytomining. As a recent, more advanced technology to eliminate such pollutants from the soil and produce critical metals, bioharvesting (phytomining/agromining) has been considered another compromising way to produce metals and meet the global demand for critical/target metals. The bio-ore obtained from phytomining can be safely disposed of or introduced to metal production pathways to obtain the most demanded metals, such as REEs. It is well-known that some hyperaccumulators, e.g., fern Dicranopteris linearis, can be used to absorb REE metals from the polluted soils and accumulate them in plant organs, such as leaves and stems. After soil remediation, the plant species can be harvested and introduced to the downstream steps, namely crushing/grinding, leaching, and purification processes, to extract REEs from plant matter. This novel interdisciplinary field can fill the gap between agriculture, mining, metallurgy, and the environment. Despite the advantages of agromining for the REEs production industry, key issues related to the environmental sustainability of the entire life cycle of this new concept have not been assessed yet. Hence, a comparative life cycle assessment (LCA) study was conducted to quantify the environmental footprints of REEs phytomining. The current LCA study aims to estimate and calculate environmental effects associated with phytomining by considering critical factors, such as climate change, land use, and ozone depletion. The results revealed that phytomining is an easy-to-use and environmentally sustainable approach to either eliminate REEs from polluted sites or produce REEs, offering a new source of such metals production. This LCA research provides guidelines for researchers active in developing a reliable relationship between agriculture, mining, metallurgy, and the environment to encounter soil pollution and keep the earth green and clean.

Keywords: phytoremediation, phytomining, life cycle assessment, environmental impacts, rare earth elements, hyperaccumulator

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Authors: Saddam Hussain, Ghadeer Mohsen Albadrani

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Pakistan is one of the most vulnerable countries to climate change. Being a country where 23% of the country’s GDP relies on agriculture, this is a serious cause of concern. Introducing industrial hemp in Pakistan can help build climate resilience in the agricultural sector of the country, as hemp has recently emerged as a sustainable, eco-friendly, resource-efficient, and climate-resilient crop globally. Hemp has the potential to absorb huge amounts of CO₂, nourish the soil, and be used to create various biodegradable and eco-friendly products. Hemp is twice as effective as trees at absorbing and locking up carbon, with 1 hectare (2.5 acres) of hemp reckoned to absorb 8 to 22 tonnes of CO₂ a year, more than any woodland. Along with its high carbon-sequestration ability, it produces higher biomass and can be successfully grown as a cover crop. Hemp can grow in almost all soil conditions and does not require pesticides. It has fast-growing qualities and needs only 120 days to be ready for harvest. Compared with cotton, hemp requires 50% less water to grow and can produce three times higher fiber yield with a lower ecological footprint. Recently, the Government of Pakistan has allowed the cultivation of industrial hemp for industrial and medicinal purposes, making it possible for hemp to be reinserted into the country’s economy. Pakistan’s agro-climatic and edaphic conditions are well-suitable to produce industrial hemp, and its cultivation can bring economic benefits to the country. Pakistan can enter global markets as a new exporter of hemp products. The production of hemp in Pakistan can be most exciting to the workforce, especially for farmers participating in hemp markets. The minimum production cost of hemp makes it affordable to small holding farmers, especially those who need their cropping system to be as highly sustainable as possible. Dr. Saddam Hussain is leading the first pilot project of Industrial Hemp in Pakistan. In the past three years, he has been able to recruit high-impact research grants on industrial hemp as Principal Investigator. He has already screened the non-toxic hemp genotypes, tested the adaptability of exotic material in various agroecological conditions, formulated the production agronomy, and successfully developed the complete value chain. He has developed prototypes (fabric, denim, knitwear) using hemp fibre in collaboration with industrial partners and has optimized the indigenous fibre processing techniques. In this lecture, Dr. Hussain will talk on hemp agronomy and its complete fibre value chain. He will discuss the current progress, and will highlight the major challenges and future research direction on hemp research.

Keywords: industrial hemp, agricultural sustainability, agronomic evaluation, hemp value chain

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Authors: Jihede Haj Messaoud, Hamdi Omar, Hela Fakhfakh Ben Jemia, Chokri Yaich

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The Upper Lutetian alternating marl–limestone succession of Reineche Member was deposited over a warm shallow carbonate platform that permits Nummulites proliferation. High-resolution studies of 30 meters thick Nummulites-bearing Reineche Member, cropping out in Central Tunisia (Jebel Siouf), have been undertaken, regarding pronounced cyclical sedimentary sequences, in order to investigate the periodicity of cycles and their related orbital-scale oceanic and climatic changes. The palaeoenvironmental and palaeoclimatic data are preserved in several proxies obtainable through high-resolution sampling and laboratories measurement and analysis as magnetic susceptibility (MS) and carbonates contents in conjunction with a wireline logging tools. The time series analysis of proxies permits to establish cyclicity orders present in the studied intervals which could be linked to the orbital cycles. MS records provide high-resolution proxies for relative sea level change in Late Lutetian strata. The spectral analysis of MS fluctuations confirmed the orbital forcing by the presence of the complete suite of orbital frequencies in the precession of 23 ka, the obliquity of 41 ka, and notably the two modes of eccentricity of 100 and 405 ka. Regarding the two periodic sedimentary cycles detected by wavelet analysis of proxy fluctuations which coincide with the long-term 405 ka eccentricity cycle, the Reineche Member spanned 0,8 Myr. Wireline logging tools as gamma ray and sonic were used as a proxies to decipher cyclicity and trends in sedimentation and contribute to identifying and correlate units. There are used to constraint the highest frequency cyclicity modulated by a long term wavelength cycling apparently controlled by clay content. Interpreted as a result of variations in carbonate productivity, it has been suggested that the marl-limestone couplets, represent the sedimentary response to the orbital forcing. The calculation of cycle durations through Reineche Member, is used as a geochronometer and permit the astronomical calibration of the geologic time scale. Furthermore, MS coupled with carbonate contents, and fossil occurrences provide strong evidence for combined detrital inputs and marine surface carbonate productivity cycles. These two synchronous processes were driven by the precession index and ‘fingerprinted’ in the basic marl–limestone couplets, modulated by orbital eccentricity.

Keywords: magnetic susceptibility, cyclostratigraphy, orbital forcing, spectral analysis, Lutetian

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Authors: Mmatladi D. Mnguni, Mustapha Mohammed, George Y. Mahama, Alhassan L. Abdulai, Felix D. Dakora

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Industrial-based nitrogen (N) fertilizers are justifiably credited for the current state of food production across the globe, but their continued use is not sustainable and has an adverse effect on the environment. The search for greener and sustainable technologies has led to an increase in exploiting biological systems such as legumes and organic amendments for plant growth promotion in cropping systems. Although the benefits of legume rotation with cereal crops have been documented, the full benefits of soybean-sorghum rotation systems have not been properly evaluated in Africa. This study explored the benefits of soybean-sorghum rotation through assessing N₂ fixation and water-use efficiency of soybean in rotation with sorghum with and without organic and inorganic amendments. The field trials were conducted from 2017 to 2020. Sorghum was grown on plots previously cultivated to soybean and vice versa. The succeeding sorghum crop received fertilizer amendments [organic fertilizer (5 tons/ha as poultry litter, OF); inorganic fertilizer (80N-60P-60K) IF; organic + inorganic fertilizer (OF+IF); half organic + inorganic fertilizer (HIF+OF); organic + half inorganic fertilizer (OF+HIF); half organic + half inorganic (HOF+HIF) and control] and was arranged in a randomized complete block design. The soybean crop succeeding fertilized sorghum received a blanket application of triple superphosphate at 26 kg P ha⁻¹. Nitrogen fixation and water-use efficiency were respectively assessed at the flowering stage using the ¹⁵N and ¹³C natural abundance techniques. The results showed that the shoot dry matter of soybean plants supplied with HOF+HIF was much higher (43.20 g plant-1), followed by OF+HIF (36.45 g plant⁻¹), and HOF+IF (33.50 g plant⁻¹). Shoot N concentration ranged from 1.60 to 1.66%, and total N content from 339 to 691 mg N plant⁻¹. The δ¹⁵N values of soybean shoots ranged from -1.17‰ to -0.64‰, with plants growing on plots previously treated to HOF+HIF exhibiting much higher δ¹⁵N values, and hence lower percent N derived from N₂ fixation (%Ndfa). Shoot %Ndfa values varied from 70 to 82%. The high %Ndfa values obtained in this study suggest that the previous year’s organic and inorganic fertilizer amendments to sorghum did not inhibit N₂ fixation in the following soybean crop. The amount of N-fixed by soybean ranged from 106 to 197 kg N ha⁻¹. The treatments showed marked variations in carbon (C) content, with HOF+HIF treatment recording the highest C content. Although water-use efficiency varied from -29.32‰ to -27.85‰, shoot water-use efficiency, C concentration, and C:N ratio were not altered by previous fertilizer application to sorghum. This study provides strong evidence that previous HOF+HIF sorghum residues can enhance N nutrition and water-use efficiency in nodulated soybean.

Keywords: ¹³C and ¹⁵N natural abundance, N-fixed, organic and inorganic fertilizer amendments, shoot %Ndfa

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Authors: Catariny C. Aleman, Flavio B. Campos, Matheus A. Caliman, Everardo C. Mantovani

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The seedling production stage is a critical point in the vegetable production system. Obtaining high-quality seedlings is a prerequisite for subsequent cropping to occur well and productivity optimization is required. The water management is an important step in agriculture production. The adequate water requirement in horticulture seedlings can provide higher quality and increase field production. The practice of irrigation is indispensable and requires a duly adjusted quality irrigation system, together with a specific water management plan to meet the water demand of the crop. Irrigation management in seedling management requires a great deal of specific information, especially when it involves the use of inputs such as hydrorentering polymers and automation technologies of the data acquisition and irrigation system. The experiment was conducted in a greenhouse at the Federal University of Viçosa, Viçosa - MG. Tomato seedlings (Lycopersicon esculentum Mill) were produced in plastic trays of 128 cells, suspended at 1.25 m from the ground. The seedlings were irrigated by 4 micro sprinklers of fixed jet 360º per tray, duly isolated by sideboards, following the methodology developed for this work. During Phase 1, in January / February 2017 (duration of 24 days), the cultivation coefficient (Kc) of seedlings cultured in the presence and absence of hydrogel was evaluated by weighing lysimeter. In Phase 2, September 2017 (duration of 25 days), the seedlings were submitted to 4 irrigation managements (Kc, timer, 0.50 ETo, and 1.00 ETo), in the presence and absence of hydrogel and then evaluated in relation to quality parameters. The microclimate inside the greenhouse was monitored with the use of air temperature, relative humidity and global radiation sensors connected to a microcontroller that performed hourly calculations of reference evapotranspiration by Penman-Monteith standard method FAO56 modified for the balance of long waves according to Walker, Aldrich, Short (1983), and conducted water balance and irrigation decision making for each experimental treatment. Kc of seedlings cultured on a substrate with hydrogel (1.55) was higher than Kc on a pure substrate (1.39). The use of the hydrogel was a differential for the production of earlier tomato seedlings, with higher final height, the larger diameter of the colon, greater accumulation of a dry mass of shoot, a larger area of crown projection and greater the rate of relative growth. The handling 1.00 ETo promoted higher relative growth rate.

Keywords: automatic system; efficiency of water use; precision irrigation, micro sprinkler.

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