Search results for: crop yield estimation

Authors: Bibek Sapkota, Michael Burton, Krishna Prasad Timsina

Abstract:

This paper presents a discrete choice experiment (DCE)-based analysis of farmers' preferences for rice variety attributes involving 540 farmers from the Terai region of Nepal clustered into East, Mid, and Western Terai regions. Findings reveal that farmers prioritize grain yield, finer grain types, drought tolerance, and shorter crop duration when selecting rice varieties, with subtle gender-based differences observed. However, breeding programs have predominantly emphasized grain yield and crop duration, possibly neglecting other vital traits. Furthermore, the research reveals a concerning decline in the yield trends of both released and registered rice varieties. Notably, the limited availability of recommended rainfed varieties, despite strong farmer preferences for drought tolerance, underscores the imperative of bridging this gap to ensure food security. This study provides insights into the multifaceted nature of farmer preferences and calls for a more holistic approach to varietal development that aligns with farmers' needs and the evolving challenges of rice farming in the Terai region of Nepal.

Keywords: breeders’ preferences, discrete choice experiment, farmers’ preferences, rice variety attributes

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Authors: Javed Sidiqi, Stephen Baezinger, Stephen Wegulo

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Wheat (Triticum aestivum L.) production continues to be challenged by foliar fungal diseases although significant improvement has been made to manage the diseases through developing resistant varieties and the fungicide use to ensure sufficient wheat is produced to meet the growing population’s need. Significant crop losses have been recorded in the history of grain production and yield losses due to fungal diseases, and the trend continues to threat food security in the world and particularly in the less developed countries. The impact of individual fungal diseases on grain yield has been studied extensively to determine crop losses. However, there is limited research available to find out the combined effects of fungal diseases on grain yield and the ways to effectively manage the diseases. Therefore, the objectives of this research were to study the effect of fungal pathogens on grain yield of pre-released winter wheat genotypes in fungicide treated and untreated plots, and to determine whether S7b gene was present in ‘Gage’ wheat as previously hypothesized. Sixty winter wheat genotypes in fungicide treated and untreated plots were studied across four environments. There was a significant effect of fungicide on grain yield consistently across four environments in three years. Fungicide treated wheat lines demonstrated (4,496 kg/ ha-1) grain yield compared to (3,147 kg/ ha-1) grain yield in untreated wheat lines indicating 43% increased grain yield due to severity of foliar fungal diseases. Furthermore, fungicide application also caused an increase in protein concentration from 153 (g kg-1) to 164 (g kg-1) in treated plots in along with test weight from 73 to 77 (kg hL-1) respectively. Gage wheat variety and ISr7b-Ra were crossed to determine presence of Sr7b in Gage. The F2 and F2:3 segregating families were screened and evaluated for stem rust resistance. The segregation of families fell within 15:1 ratio for two separate resistance genes suggesting that Sr7b segregates independently from an unknown resistance gene in Gage that needs to be characterized for its use in the future wheat breeding program to develop resistant wheat varieties.

Keywords: funicide, genetics, foliar diseases, grain

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Authors: Ejoh Nonso Francis

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: Irrigation scheduling is a critical aspect of sustainable agriculture as it ensures optimal use of water resources, reduces water waste, and enhances crop yields. This paper presents a case study of a farm in Onitsha, Anambra State, Nigeria, where irrigation scheduling was optimized using a combination of soil moisture sensors and weather data. The study aimed to evaluate the effectiveness of this approach in improving water use efficiency and crop productivity. The results showed that the optimized irrigation scheduling approach led to a 30% reduction in water use while increasing crop yield by 20%. The study demonstrates the potential of technology-based irrigation scheduling to enhance sustainable agriculture in Nigeria and beyond.

Keywords: irrigation scheduling, sustainable agriculture, soil moisture sensors, weather data, water use efficiency, crop productivity, nigeria, onitsha, anambra state, technology-based irrigation scheduling, water resources, environmental degradation, crop water requirements, overwatering, water waste, farming systems, scalability

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Authors: Rafeza Begum, Mohammad Mokhlesur Rahman, Safikul Moula, Rafiqul Islam

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Potassium (K) is crucial for healthy soil and plant growth. However, K fertilization is either disregarded or poorly underutilized in Bangladesh agriculture, despite the great demand for crops. This could eventually result in a significant depletion of the soil's potassium reserves, irreversible alteration of the minerals that contain potassium, and detrimental effects on crop productivity. Soil K mining in Bangladesh is a worrying problem, and we need to evaluate it thoroughly and find remedies. A pot culture experiment was conducted in the greenhouse of Bangladesh Institute of Nuclear Agriculture (BINA) using eleven soil series of Bangladesh in order to see the depletion behaviour of potassium (K) by continuous cropping using rice (var. Iratom-24) as the test crop. The soil series were Ranishankhail, Kaonia. Sonatala, Silmondi, Gopalpur, Ishurdi, Sara, Kongsha, Nunni, Lauta and Amnura on which four successive rice plants (45 days duration) were raised with (100 ppm K) or without addition of potassium. Nitrogen, phosphorus, sulfur and zinc were applied as basal to all pots. Potassium application resulted in higher dry matter yield, increased K concentration and uptake in all the soils compared with no K treatment; which gradually decreased in the subsequent harvests. Furthermore, plant takes up K not only from exchangeable pool but also from non-exchangeable sites and a minimum replenishment of K from the soil reserve was observed. Continuous cropping has resulted in the depletion of available K of the soil. The result indicated that in order to sustain higher crop yield under intensive cultivation, the addition of potash fertilizer is necessary.

Keywords: potassium, exchangeable pool, depletion behavior., Soil series

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Authors: Alefsi D. Sanchez-Reinoso, Leonardo Lombardini, Hermann Restrepo

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Colombian coffee is recognized worldwide for its mild flavor and aroma. Its cultivation generates a large amount of waste, such as fresh pulp, which leads to environmental, health, and economic problems. Obtaining biochar (BC) by pyrolysis of coffee pulp and its incorporation to the soil can be a complement to the crop mineral nutrition. The objective was to evaluate the effect of the application of BC obtained from coffee pulp on the physiology and agronomic performance of the Castillo variety coffee crop (Coffea arabica L.). The research was developed in field condition experiment, using a three-year-old commercial coffee crop, carried out in Tolima. Four doses of BC (0, 4, 8 and 16 t ha-1) and four levels of chemical fertilization (CF) (0%, 33%, 66% and 100% of the nutritional requirements) were evaluated. Three groups of variables were recorded during the experiment: i) physiological parameters such as Gas exchange, the maximum quantum yield of PSII (Fv/Fm), biomass, and water status were measured; ii) physical and chemical characteristics of the soil in a commercial coffee crop, and iii) physiochemical and sensorial parameters of roasted beans and coffee beverages. The results indicated that a positive effect was found in plants with 8 t ha-1 BC and fertilization levels of 66 and 100%. Also, a positive effect was observed in coffee trees treated with 8 t ha-1 BC and 100%. In addition, the application of 16 t ha-1 BC increased the soil pHand microbial respiration; reduced the apparent density and state of aggregation of the soil compared to 0 t ha-1 BC. Applications of 8 and 16 t ha-1 BC and 66%-100% chemical fertilization registered greater sensitivity to the aromatic compounds of roasted coffee beans in the electronic nose. Amendments of BC between 8 and 16 t ha-1 and CF between 66% and 100% increased the content of total soluble solids (TSS), reduced the pH, and increased the titratable acidity in beverages of roasted coffee beans. In conclusion, 8 t ha-1 BC of the coffee pulp can be an alternative to supplement the nutrition of coffee seedlings and trees. Applications between 8 and 16 t ha-1 BC support coffee soil management strategies and help the use of solid waste. BC as a complement to chemical fertilization showed a positive effect on the aromatic profile obtained for roasted coffee beans and cup quality attributes.

Keywords: crop yield, cup quality, mineral nutrition, pyrolysis, soil amendment

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Authors: Fatemeh Benakashani, Hossein Tavakoli, Elias Soltani

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To ensure the sustainability of crop cultivation and rural economies, it is imperative that we focus on cultivating resilient crops capable of withstanding salt stress. However, the effective management of weeds in salt-affected soils remains a significant challenge. This study investigates the impact of living mulches, specifically Berseem clover (Trifolium alexandrinum) and Barley (Hordeum vulgare), on weed control, as well as the quality and yield of Black cumin (Nigella sativa) in salt-affected soil. In our research, we employed a two-fold mowing strategy for the living mulches: once following crop establishment and once before the flowering stage. Notably, the weed-free plots demonstrated Black cumin's seed yield, and oil content (31.1% to 34.3%), consistent with previous studies, highlighting its potential for the reclamation and utilization of salt-affected lands. However, Black cumin exhibited limited competitiveness against prevalent weeds in the field, such as Amaranthus retroflexus, Chenopodium album, and Portulaca oleracea, which significantly diminished both the 1000 grain mass in plots where weeds were present. Interestingly, the introduction of living mulches led to improvements in seed yield and seed oil content when compared to both weed-free and weed-infested plots. Notably, Berseem clover exhibited greater biomass than Barley, indicating its heightened competitiveness against weeds. Nevertheless, it's worth noting that in the long term, Berseem clover also competed with the main crop, thereby limiting overall productivity. Consequently, we recommend relocating the Berseem clover living mulch following the establishment of Black cumin as a strategy for weed management in Black cumin fields situated in salt-affected soils.

Keywords: weed management, competition, clover, barley, medicinal plant

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Shital Bangar, G. B. Khandagale

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The experimentation was carried out to study the influence of sulphur and boron on growth parameters and productivity of soybean in kharif season of 2009-2010 at Experimental Farm, Department of Agricultural Botany, Marathwada Agricultural University, Parbhani (M.S.). The object was to evaluate the impact of sulphur and boron on growth, development, grain yield and physiological aspects of soybean variety MAUS-81. Nine treatments consisted of three levels of sulphur i.e. 20, 30 and 40 Kg/ha as well as three levels boron i.e.10, 15 and 20 kg boron/ha and the combinations of these two mineral elements i.e. Sulphur @30 kg/ha + Borax @15 kg/ha and Sulphur @40 kg/ha + Borax @ 20 kg/ha with one control treatment in Randomized Block Design (RBD) with three replications. The effect of sulphur and boron on various growth parameters of soybean like relative growth rate (RGR) and net assimilation rate (NAR) were remained statistically on par with each other. However, the application of higher dose of Sulphur @40 kg/ha + Borax @ 20 kg/ha enhanced significantly all the growth parameters. Application of the nutrients increased the dry matter accumulation of the crop plant and hence, other growth indices like RGR and NAR also increased significantly. RGR and NAR values were recorded highest at the initial crop growth stages and decline thereafter. The application of sulphur @40 kg/ha + Borax @ 20 kg/ha recorded significantly higher content of chlorophyll ‘a’ than rest of the treatments and chlorophyll ‘b’ observed higher in boron @15 kg/ha as well as boron@20 kg/ha, whereas total chlorophyll content was maximum in sulphur @40 kg/ha. Oil content was not influenced significantly due to above fertilization. The highest seed yield and total biological yield were obtained with combination of Sulphur @40 kg/ha + Borax @ 20 kg/ha, single sulphur and boron application also showed a significant effect on seed and biological yield.

Keywords: boron, growth, productivity, quality, soybean and sulphur

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Authors: E. Tarantino, G. Disciglio, L. Frabboni, A. Libutti, G. Gatta, A. Gagliaridi, A. Tarantino

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Nowadays, the main goal for modern horticultural production is the increase of quality. In the recent years, the use of organic fertilizers or bio stimulants, that can be applied in agriculture in order to improve the quanti-qualitative crop yields, has encountered an increasing interest. The bio stimulants are gaining importance also for their possible use in organic and sustainable agriculture, avoiding excessive fertilizer applications. Consecutive experimental trials were carried out in Apulia region (southern Italy) on three herbaceous crops (cauliflower, pepper and fennel), grown in pots, under conventional and organic fertilization, with and without bio stimulants application, to verify the effects of several bio stimulants (Siapton®10L, Micotech L and Lysodin Alga-Fert) on quanti-qualitative yield characteristics. At the harvest, the quanti-qualitative yield characteristics of each crop were determined. All experimental data were subjected to analysis of variance (ANOVA) and, when significant effects were detected, the mean values were compared using Tukey’s test. Results showed great differences of yield characteristics between conventional and organic crops, particularly highlighting a higher yield in the conventional one. Variable results were generally observed when bio stimulants were applied. In this contest no effect were noted on quantitative yield, whereas a light positive effect of bio stimulants on qualitative characteristic, related to the higher dry matter content of cauliflower and the higher soluble solid content of pepper, was observed. Moreover, an evident positive effect of bio stimulants was noted in the fennel due to the lower nitrate content. The latter results are according with most of published literature obtained on other herbaceous crops.

Keywords: biostimulants, cauliflower, pepper, fennel

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Authors: Arslan Shehroz, Muhammad Amjad Ali, Amjad Abbas, Imran Ramzan, Muhammad Zunair Latif

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Potato (Solanum tuberosum L.) is the 4th most important food crop of the world after wheat, rice and maize. It is the staple food in many European countries. Being rich in starch (one of the main three food ingredients) and having the highest productivity per unit area, has great potential to address the challenge of the food security. Processed potato is also used as chips and crisps etc as ‘fast food’. There are many biotic and abiotic factors which check the production of potato and become hurdle in achievement production potential of potato. 20 new varieties along with two checks were evaluated. Plant to plant and row to row distances were maintained as 20 cm and 75 cm, respectively. The trial was conducted according to the randomized complete block design with three replications. Normal agronomic and plant protection measures were carried out in the crop. It is revealed from the experiment that exotic variety 171 gave the highest yield of 35.5 t/ha followed by Masai with 31.0 t/ha tuber yield. The check variety Simply Red 24.2 t/ha yield, while the lowest tuber yield (1.5 t/ha) was produced by the exotic variety KWS-06-125. The maximum emergence was shown by the Variety Red Sun (89.7 %). The lowest emergence was shown by the variety Camel (71.7%). Regarding tuber grades, it was noted that the maximum Ration size tubers were produced by the exotic variety Compass (3.7%), whereas 11 varieties did not produce ration size tubers at all. The variety Red Sun produced lowest percentage of small size tubers (12.7%) whereas maximum small size tubers (93.0%) were produced by the variety Jitka. Regarding disease infestation, it was noted that the maximum scab incidence (4.0%) was recorded on the variety Masai, maximum rhizoctonia attack (60.0%) was recorded on the variety Camel and maximum tuber cracking (0.7%) was noted on the variety Vendulla.

Keywords: check variety, potato, potential and yield, trial

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Authors: Sanjay Kumar Behera, Kanhu Charan Patra

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A GIS-based method has been applied for the determination of soil erosion and sediment yield in a small watershed in Ong River basin, Odisha, India. The method involves spatial disintegration of the catchment into homogenous grid cells to capture the catchment heterogeneity. The gross soil erosion in each cell was calculated using Universal Soil Loss Equation (USLE) by carefully determining its various parameters. The concept of sediment delivery ratio is used to route surface erosion from each of the discretized cells to the catchment outlet. The process of sediment delivery from grid cells to the catchment outlet is represented by the topographical characteristics of the cells. The effect of DEM resolution on sediment yield is analyzed using two different resolutions of DEM. The spatial discretization of the catchment and derivation of the physical parameters related to erosion in the cell are performed through GIS techniques.

Keywords: DEM, GIS, sediment delivery ratio, sediment yield, soil erosion

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Authors: Shahid Iqbal, Haroon Z. Khan, Muhammad Arif

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A sustainable agricultural system involving the improvement in soil properties and crop performance cannot be developed without organic fertilizer use. The effects of poultry manure compost (PMC) and pressmud compost (PrMC) at different levels on improving the soil properties and maize performance has not been yet described by any study comprehensively. Thus, field experiments (2011 and 2012) were conducted at Agronomy Research Area, University of Agriculture Faisalabad (31°26'5" N and 73°4'6" E) in sandy loam soil to determine the improvement in soil properties and maize performance due to application of PMC and PrMC each at five different levels (2, 4, 6, 8 and 10 t ha-1). A control (unamended) treatment was also included for comparison. The results indicated that performance of PMC levels was superior to PrMC levels. Increasing both composts levels improved soil properties, maize growth, and stover yield. Results showed that during both years’ highest rates of PMC i.e. 10 and 8 t ha-1 improved the soil properties: ECe, pH, inorganic N, OM, and WHC higher than other treatments. While, 10 and 8 t PMC ha-1 also significantly increased leaf area index (LAI), crop growth rate (CGR) and net assimilation rate (NAR), and stover yield. Similarly, 10 and 8 t PMC ha-1 also improved the grain protein content, but contrarily, grain oil was lowest for 10 and 8 t ha-1 PMC during both years. Moreover, in both years highest gross and net income, and benefit cost ratio was also achieved by 10 and 8 t ha-1 PMC. It is concluded that PMC at rate of 10 and 8 t ha-1 sustainably improved soil properties and maize performance.

Keywords: compost, soil, maize, growth, yield

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Authors: Athar Mahmood, Asad Ali

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Management considerations including harvesting time and nitrogen application considerably influence the biomass yield, quality and biogas production. Therefore, a field study was conducted to determine the effect of various harvesting times and nitrogen rates on the biomass yield, quality and biogas yield of maize crop. This experiment was consisted of various harvesting times i.e., harvesting after 45, 55 and 65 days of sowing (DAS) and nitrogen rates i.e., 0, 100, 150 and 200 kg ha-1 respectively. The data indicated that maximum plant height, leaf area, dry matter (DM) yield, protein, acid detergent fiber, neutral detergent fiber, crude fiber contents and biogas yield were recorded 65 days after sowing while lowest was recorded 45 days after sowing. In contrary to that significantly higher chlorophyll contents were observed at 45 DAS. In case of nitrogen rates maximum plant height, leaf area, and DM yield, protein contents, ash contents, acid detergent fiber, neutral detergent fiber, crude fiber contents and chlorophyll contents were determined with nitrogen at the rate of 200 kg ha-1, while minimum was observed when no N was applied. Therefore, harvesting 65 DAS and N application @ 200 kg ha-1 can be suitable for getting the higher biomass and biogas production.

Keywords: chemical composition, fiber contents, biogas, nitrogen, harvesting time

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Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

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In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

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Authors: G. Disciglio, G. Gatta, A. Libutti, A. Tarantino, L. Frabboni, E. Tarantino

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Results of a field study carried out at Trinitapoli (Puglia region, southern Italy) on the irrigation of an artichoke crop with three types of water (secondary-treated wastewater, SW; tertiary-treated wastewater, TW; and freshwater, FW) are reported. Physical, chemical and microbiological analyses were performed on the irrigation water, and on soil and yield samples. The levels of most of the chemical parameters, such as electrical conductivity, total suspended solids, Na+, Ca2+, Mg+2, K+, sodium adsorption ratio, chemical oxygen demand, biological oxygen demand over 5 days, NO3 –N, total N, CO32, HCO3, phenols and chlorides of the applied irrigation water were significantly higher in SW compared to GW and TW. No differences were found for Mg2+, PO4-P, K+ only between SW and TW. Although the chemical parameters of the three irrigation water sources were different, few effects on the soil were observed. Even though monitoring of Escherichia coli showed high SW levels, which were above the limits allowed under Italian law (DM 152/2006), contamination of the soil and the marketable yield were never observed. Moreover, no Salmonella spp. were detected in these irrigation waters; consequently, they were absent in the plants. Finally, the data on the quantitative-qualitative parameters of the artichoke yield with the various treatments show no significant differences between the three irrigation water sources. Therefore, if adequately treated, municipal wastewater can be used for irrigation and represents a sound alternative to conventional water resources.

Keywords: artichoke, soil chemical characteristics, fecal indicators, treated municipal wastewater, water recycling

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Authors: Fahad Suleiman

Abstract:

Agriculture has been the mainstay of the nation’s economy in Nigeria. It provides food for the ever rapidly increasing population and raw materials for the industries. People especially the rural dwellers are gainfully employed on their crop farms and small-scale livestock farms for income earning. In farming, availability of funds and time management are one of the major factors that influence the system of farming in Nigeria in which mathematical science knowledge was highly required in order for farms to be managed effectively. Farmers often applied mathematics, almost every day for a variety of tasks, ranging from measuring and weighing, to land marking. This paper, therefore, explores some of the ways math is used in farming. For instance, farmers use arithmetic variety of farm activities such as seed planting, harvesting crop, cultivation and mulching. It is also important in helping farmers to know how much their livestock weighs, how much milk their cows produce and crop yield per acres, among others.

Keywords: agriculture, application, economic, farming, mathematics

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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: Fhatuwani Herman Nndwambi, P. W. Mashela

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Salinity is a major constraint limiting crop productivity. It has been predicted that by the year 2050, more than 50% of the arable land will be affected by salinity. Two similar salinity experiments were conducted in two seasons under greenhouse condition. Six levels of salinity plus control (viz; control, 2, 4, 8, 16, 32 and 64 % NaCl and CaCl2 at 3:1 ratio) were applied in a form of irrigation water in a single factor experiment arranged in a complete block design with 20 replications. Plant growth and yield were negatively affected by salinity treatments especially at the high levels of salinity. For example, our results suggest that the 32 and 64% of NaCl and CaCl2 treatment were too much for the plant to withstand as determined by reduced dry shoot mass, stem diameter and plant height in both seasons. On the other hand, stomatal conductance and chlorophyll content increased with an increased level of salinity.

Keywords: growth, salinity, season, yield

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Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

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Precision Agriculture has long being benefited from crop fields’ aerial imagery. This important tool has allowed identifying patterns in crop fields, generating useful information to the production management. Reflectance intensity data in different ranges from the electromagnetic spectrum may indicate presence or absence of nutrients in the soil of an area. Different relations between the different light bands may generate even more detailed information. The knowledge of the nutrients content in the soil or in the crop during its growth is a valuable asset to the farmer that seeks to optimize its yield. However, small farmers in Brazil often lack the resources to access this kind information, and, even when they do, it is not presented in a comprehensive and/or objective way. So, the challenges of implementing this technology ranges from the sampling of the imagery, using aerial platforms, building of a mosaic with the images to cover the entire crop field, extracting the reflectance information from it and analyzing its relationship with the parameters of interest, to the display of the results in a manner that the farmer may take the necessary decisions more objectively. In this work, it’s proposed an analysis of soil nutrient contents based on image processing of satellite imagery and comparing its outtakes with commercial laboratory’s chemical analysis. Also, sources of satellite imagery are compared, to assess the feasibility of using Google Earth data in this application, and the impacts of doing so, versus the application of imagery from satellites like Landsat-8 and Pleiades. Furthermore, an algorithm for building mosaics is implemented using Google Earth imagery and finally, the possibility of using unmanned aerial vehicles is analyzed. From the data obtained, some soil parameters are estimated, namely, the content of Potassium, Phosphorus, Boron, Manganese, among others. The suitability of Google Earth Imagery for this application is verified within a reasonable margin, when compared to Pleiades Satellite imagery and to the current commercial model. It is also verified that the mosaic construction method has little or no influence on the estimation results. Variability maps are created over the covered area and the impacts of the image resolution and sample time frame are discussed, allowing easy assessments of the results. The final results show that easy and cheaper remote sensing and analysis methods are possible and feasible alternatives for the small farmer, with little access to technological and/or financial resources, to make more accurate decisions about soil nutrient management.

Keywords: remote sensing, precision agriculture, mosaic, soil, nutrient content, satellite imagery, aerial imagery

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

Abstract:

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: Rajeshwari Madli, Santhosh Hebbar, Vishwanath Heddoori, G. V. Prasad

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Agriculture is the major occupation in India and forms the backbone of Indian economy in which irrigation plays a crucial role for increasing the quality and quantity of crop yield. In spite of many revolutionary advancements in agriculture, there has not been a dramatic increase in agricultural performance. Lack of irrigation infrastructure and agricultural knowledge are the critical factors influencing agricultural performance. However, by using advanced agricultural equipment, the effect of these factors can be curtailed.  The presented system aims at increasing the yield of crops by using an intelligent irrigation controller that makes use of wireless sensors. Sensors are used to monitor primary parameters such as soil moisture, soil pH, temperature and humidity. Irrigation decisions are taken based on the sensed data and the type of crop being grown. The system provides a mobile application in which farmers can remotely monitor and control the irrigation system. Also, the water pump is protected against damages due to voltage variations and dry running.

Keywords: android application, Bluetooth, wireless sensors, irrigation, temperature, soil pH

Procedia PDF Downloads 362

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

Procedia PDF Downloads 57

Authors: Mojtaba Esmaeilzad Limoudehi

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To evaluate the model ORYZA2000, under the management of irrigation and nitrogen fertilization experiment, a split plot with a randomized complete block design with three replications on hybrid cultivars (spring) in the 1388-1387 crop year was conducted at the Rice Research Institute. Permanent flood irrigation as the main plot in the fourth level, around 5 days, from 11 days to 8 days away, and the four levels of nitrogen fertilizer as the subplots 0, 90, 120, and 150 kg N Ha were considered. Simulated and measured values of leaf area index, grain yield, and biological parameters using the regression coefficient, t-test, the root mean square error (RMSE), and normalized root mean square error (RMSEn) were performed. Results, the normalized root mean square error of 10% in grain yield, the biological yield of 9%, and 23% of maximum LAI was determined. The simulation results show that grain yield and biological ORYZA2000 model accuracy are good but do not simulate maximum LAI well. The results show that the model can support ORYZA2000 test results and can be used under conditions of nitrogen fertilizer and irrigation management.

Keywords: evaluation, rice, nitrogen fertilizer, model ORYZA2000

Procedia PDF Downloads 49

Authors: Senthilkumar S, Vijayakumar R M , Soorianathasundaram K, Durga Devi D

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A study was conducted to assess the influence of brassinosteroid and other bioregulators as pre-harvest sprays on yield and quality of newly introduced Californian grape cv. Italia. The vines were exposed to standardized pruning level of pruning 50% of the canes to 5-6 bud level for fruiting and 50% of the canes to two bud level for vegetative growth. The influence of brassinosteroid was assessed using BR (1 ppm) alone and in combination with GA3 and CPPU, sprayed at three different stages over the control (water spray) were given as treatments. The results revealed that the bunches treated with Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage i.e., 7-8 mm berry size, recorded the maximum values on yield characters like bunch weight (719.94 g), yield per vine (12.70 kg/vine) and yield per hectare (15.88 t). The berry characters and quality traits were also significantly influenced by the application of bioregulators. The maximum value for all those characters was registered under bunch sprays of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage. The economic feasibility indicated that the treatment combination Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) had registered the maximum benefit cost ratio of 3.13, as compared to 1.89 in control (water spray). Overall, it was observed that a combined bunch spray of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) was adjudged as the best treatment for promoting the crop for better the bunch quality and yield.

Keywords: bioregulators, brassinosteroid, CPPU, GA3, Italia grape cultivar

Procedia PDF Downloads 221

Authors: Alhaji M. H. Conteh, Xiangbin Yan, Issa Fofana, Brima Gegbe, Tamba I. Isaac

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Rice grain is Sierra Leone’s staple food and the nation imports over 120,000 metric tons annually due to a shortfall in its cultivation. Thus, the insufficient level of the crop's cultivation in Sierra Leone is caused by many problems and this led to the endlessly widening supply and demand for the crop within the country. Consequently, this has instigated the government to spend huge money on the importation of this grain that would have been otherwise cultivated domestically at a cheaper cost. Hence, this research attempts to explore the response of rice supply with respect to its demand in Sierra Leone within the period 1980-2010. The Nerlovian adjustment model to the Sierra Leone rice data set within the period 1980-2010 was used. The estimated trend equations revealed that time had significant effect on output, productivity (yield) and area (acreage) of rice grain within the period 1980-2010 and this occurred generally at the 1% level of significance. The results showed that, almost the entire growth in output had the tendency to increase in the area cultivated to the crop. The time trend variable that was included for government policy intervention showed an insignificant effect on all the variables considered in this research. Therefore, both the short-run and long-run price response was inelastic since all their values were less than one. From the findings above, immediate actions that will lead to productivity growth in rice cultivation are required. To achieve the above, the responsible agencies should provide extension service schemes to farmers as well as motivating them on the adoption of modern rice varieties and technology in their rice cultivation ventures.

Keywords: Nerlovian adjustment model, price elasticities, Sierra Leone, trend equations

Procedia PDF Downloads 210

Authors: Nour Elhouda Abed, Bedj Mimi, Wahid Slimani, Mourad Atif, Abdelhakim Ouzzane, Hocine Irekti, Abdelkader Bekki

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The most frequent system of cereal production in Algeria is fallow-wheat. This is an extensive system that meets only the half needs some cereals and fodder demand. Resorption of fallow has become a strategic necessity to ensure food security in response to the instability of supply and the persistence of higher food prices on the world market. Despite several attempts to replace the fallow by crop cultures, choosing the best crop remains. Today, the agronomic and economic interests of legumes are demonstrated. However, their crop culture remains marginalized because of the weakness and instability of their performance. In the context of improving legumes and cereals crops as well as fallow resorption, we undertook to test, in the field, the effect of rhizobial inoculation of Phaseolus vulgaris in association with Zea Mays. We firstly studied the genetic diversity of rhizobial strains that nodulate P.vulgaris isolated from fifteen (15) different regions. ARDRA had shown 18 different genetic profiles. Symbiotic characterization highlighted a strain that highly significantly improved the fresh and dry weight of the host plant, in comparison to the negative control (un-inoculated) and the positive control (inoculated with the reference strain CIAT 899). In the field, the selected strain increased significantly the growth and yield of P.vulgaris and Zea Mays comparing to the non-inoculated control. However, the mix inoculation (selected strain+ Ciat 899) had not given the best parameters showing, thus, no synergy between the strains. These results indicate the replacing fallow by a crop legume in intercropping with cereals crops.

Keywords: fallow, intercropping, inoculation, legumes-cereals

Procedia PDF Downloads 342

Authors: R. A. Eman Elsheikh, Bart Schultz, Abraham Mehari Haile, Hussein S. Adam

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A field experiment was conducted at Gezira research station farm during the winter season in the third week of November 2012, in WadMedani, Sudan (Lat 14.23 W, Long 33.39 E and altitude 405 m above sea level, in deep cracking alkaline heavy clay Vertisols). The objective of this study was to determine the effect of three different irrigation for 10 days (W1), 15 days (W2) and 20 days (W3) and for two rows of 30 cm (S1) and 40 cm (S2), respectively. The experimental design was split plot with three replicates. The sunflower test variety was Hysun 33 cultivar. The seasonal water applied during the study was 6898, 6647, 5256, 5435, 5214, 5416 m3/ha for W1S1, W1S2, W2S1, W2S2, W3S1 and W3S2 respectively. The seed yield obtained for the above treatment in that sequence was 4208, 5542, 5167, 4579, 2931, 2936 kg/ha. The corresponding computed water productivity was 0.61, 0.82, 0.87, 0.95, 0.54, 0.56 kg/m3. The study clearly indicated that the highest seed yield was obtained when the crop was sown at 40 cm row spacing and was irrigated every 10 days (W1S2), followed by W2S1.

Keywords: water productivity, water deficit, sunflower, plant spacing

Procedia PDF Downloads 324

Authors: Rully D. Purwati, Tantri D.A. Anggraeni, Bambang Heliyanto, M. Machfud, Joko Hartono

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The availability of fuel in the world will be reduced in next few years, it is necessary to find alternative energy sources. Jatropha curcas L. is one of oil crops producing non-edible oil which is potential for bio-diesel. Jatropha cultivation and development program in Indonesia is facing several problems especially low seed yield resulting in inefficient crop cultivation cost. To cope with the problem, development of high yielding varieties is necessary. Development of new varieties to improve seed yield was conducted by hybridization and selection and resulted in fourteen potential genotypes. The yield potential of the fourteen genotypes were evaluated and compared with two check varieties. The objective of the evaluation was to find Jatropha hybrids with some characters i.e. their productivity was higher than check varieties, oil content > 40% and harvesting age ≤ 110 days. Hybridization and individual plant selection were carried out from 2010 to 2014. Evaluation of high yield was conducted in Asembagus experimental station, Situbondo, East Java in three years (2015-2017). The experimental designed was Randomized Complete Block Design with three replication, and plot size 10 m x 8 m. The characters observed were number of capsules per plant, dry seed yield (kg/ha) and seed oil content (%). The results of this experiment indicated that all the hybrids evaluated have higher productivity than check variety IP-3A. There were two superior hybrids i.e. HS-49xSP-65/32 and HS-49xSP-19/28 with highest seed yield per hectare and number of capsules per plant for three years.

Keywords: Jatropha, bio energy, hybrid, high seed yield

Procedia PDF Downloads 124

Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

Procedia PDF Downloads 61

Authors: Reshu Chaudhary, R. S. Sengar

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To increase the agricultural production Indian farmer needs to aware of the latest technology i.e. precision farming to maximize the crop yield and minimize the input (fertilizer, pesticide etc.) through monitoring the environmental factors. Biotechnology and information technology have provided lots of opportunities for the development of agriculture. But, still we have to do much more for increasing our agricultural production in order to achieve the target growth of agriculture to secure food, to eliminate poverty and improve living style, to enhance agricultural exports and national income and to improve quality of agricultural products. Nanotechnology can be a great element to satisfy these requirements and to boost the multi-dimensional development of agriculture in order to fulfill the dream of Indian farmers. Nanotechnology is the most rapidly growing area of science and technology with its application in physical science, chemical science, life science, material science and earth science. Nanotechnology is a part of any nation’s future. Research in nanotechnology has extremely high potential to benefit society through application in agricultural sciences. Nanotechnology has greater potential to bring revolution in the agricultural sector.

Keywords: agriculture, biotechnology, crop yield, nanotechnology

Procedia PDF Downloads 338