Search results for: crop

Authors: A. H. Nanher, N. P. Singh, Shashidhar Yadav, Sachin Tyagi

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Agricultural production system is an outcome of a complex interaction of seed, soil, water and agro-chemicals (including fertilizers). Therefore, judicious management of all the inputs is essential for the sustainability of such a complex system. Precision agriculture gives farmers the ability to use crop inputs more effectively including fertilizers, pesticides, tillage and irrigation water. More effective use of inputs means greater crop yield and/or quality, without polluting the environment the focus on enhancing the productivity during the Green Revolution coupled with total disregard of proper management of inputs and without considering the ecological impacts, has resulted into environmental degradation. To evaluate a new approach for site-specific nutrient management (SSNM). Large variation in initial soil fertility characteristics and indigenous supply of N, P, and K was observed among Field- and season-specific NPK applications were calculated by accounting for the indigenous nutrient supply, yield targets, and nutrient demand as a function of the interactions between N, P, and K. Nitrogen applications were fine-tuned based on season-specific rules and field-specific monitoring of crop N status. The performance of SSNM did not differ significantly between high-yielding and low-yielding climatic seasons, but improved over time with larger benefits observed in the second year Future, strategies for nutrient management in intensive rice systems must become more site-specific and dynamic to manage spatially and temporally variable resources based on a quantitative understanding of the congruence between nutrient supply and crop demand. The SSNM concept has demonstrated promising agronomic and economic potential. It can be used for managing plant nutrients at any scale, i.e., ranging from a general recommendation for homogenous management of a larger domain to true management of between-field variability. Assessment of pest profiles in FFP and SSNM plots suggests that SSNM may also reduce pest incidence, particularly diseases that are often associated with excessive N use or unbalanced plant nutrition.

Keywords: nutrient, pesticide, crop, yield

Procedia PDF Downloads 396

Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

Procedia PDF Downloads 117

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 335

Authors: Mahmood Iqbal, Khalid Nawab, Tachibana Satoshi

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Farmer Field School (FFS) is constantly aims to assist farmers to determine and learn about field ecology and integrated crop management. The study was conducted to examine the change in productivity of tomato crop in the study area; to determine increase in per acre yield of the crop, and find out reduction in per acre input cost. A study of tomato crop was conducted in ten villages namely Jabban, Bijligar Colony, Palonow, Heroshah, Zara Maira, Deghar Ghar, Sidra Jour, Anar Thangi, Miangano Korona and Wartair of district Malakand. From each village 15 respondents were selected randomly on the basis of identical allocation making sample size of 150 respondents. The research was based on primary as well as secondary data. Primary data was collected from farmers while secondary data were taken from Agriculture Extension Department Dargai, District Malakand. Interview schedule was planned and each farmer was interviewed personally. The study was based on comparison of cost, yield and income of tomato before and after FFS. Paired t-test and Statistical Package for Social Sciences (SPSS) was used for analysis; outcome of the study show that integrated pest management project has brought a positive change in the attitude of farmers of the project area through FFS approach. In district Malakand 66.0% of the respondents were between the age group of 31-50 years, 11.3% of respondents had primary level of education, 12.7% of middle level, 28.7% metric level, 3.3% of intermediate level and 2.0% of graduate level of education while 42.0% of respondents were illiterate and have no education. Average land holding size of farmers was 6.47 acres, cost of seed, crop protection from insect pest and crop protection from diseases was reduced by Rs. 210.67, Rs. 2584.43 and Rs. 3044.16 respectively, the cost of fertilizers and cost of farm yard manure was increased by Rs.1548.87 and Rs. 1151.40 respectively while tomato yield was increased by 1585.03 kg/acre from 7663.87 to 9248.90 kg/acre. The role of FFS initiate by integrated pest management project through department of agriculture extension for the development of agriculture was worth mentioning. It has brought enhancement in crop yield of tomato and their income through FFS approach. On the basis of results of the research studies, integrated pest management project should spread their developmental activities for maximum participation of the complete rural masses through participatory FFS approach.

Keywords: agriculture, Farmers field schools, extension education, tomato

Procedia PDF Downloads 579

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

Procedia PDF Downloads 39

Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

Procedia PDF Downloads 34

Authors: Sanari Chalin Moriri, Kwabena Kingsley Ayisi, Alina Mofokeng

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Dryland smallholder farmers in South Africa are vulnerable to all kinds of risks, and it negatively affects crop productivity and profit. Pigeonpea is a leguminous and multipurpose crop that provides food, fodder, and wood for smallholder farmers. The majority of these farmers are still growing pigeonpea from traditional unimproved seeds, which comprise a mixture of genotypes. The objectives of the study were to identify the key risk factors that affect pigeonpea productivity and to develop management strategies on how to alleviate the risk factors in pigeonpea production. The study was conducted in two provinces (Limpopo and Mpumalanga) of South Africa in six municipalities during the 2020/2021 growing seasons. The non-probability sampling method using purposive and snowball sampling techniques were used to collect data from the farmers through a structured questionnaire. A total of 114 pigeonpea producers were interviewed individually using a questionnaire. Key stakeholders in each municipality were also identified, invited, and interviewed to verify the information given by farmers. Data collected were subjected to SPSS statistical software 25 version. The findings of the study were that majority of farmers affected by risk factors were women, subsistence, and old farmers resulted in low food production. Drought, unavailability of improved pigeonpea seeds for planting, access to information, and processing equipment were found to be the main risk factors contributing to low crop productivity in farmer’s fields. Above 80% of farmers lack knowledge on the improvement of the crop and also on the processing techniques to secure high prices during the crop off-season. Market availability, pricing, and incidence of pests and diseases were found to be minor risk factors which were triggered by the major risk factors. The minor risk factors can be corrected only if the major risk factors are first given the necessary attention. About 10% of the farmers found to use the crop as a mulch to reduce soil temperatures and to improve soil fertility. The study revealed that most of the farmers were unaware of its utilisation as fodder, much, medicinal, nitrogen fixation, and many more. The risk of frequent drought in dry areas of South Africa where farmers solely depend on rainfall poses a serious threat to crop productivity. The majority of these risk factors are caused by climate change due to unrealistic, low rainfall with extreme temperatures poses a threat to food security, water, and the environment. The use of drought-tolerant, multipurpose legume crops such as pigeonpea, access to new information, provision of processing equipment, and support from all stakeholders will help in addressing food security for smallholder farmers. Policies should be revisited to address the prevailing risk factors faced by farmers and involve them in addressing the risk factors. Awareness should be prioritized in promoting the crop to improve its production and commercialization in the dryland farming system of South Africa.

Keywords: management strategies, pigeonpea, risk factors, smallholder farmers

Procedia PDF Downloads 174

Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

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Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

Procedia PDF Downloads 374

Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

Procedia PDF Downloads 116

Authors: Ezzat Abd El Lateef

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Agroforestry means combining the management of trees with productive agricultural activities, especially in semiarid regions where crop yield increases are limited in agroforestry systems due to the fertility and microclimate improvements and the large competitive effect of trees with crops for water and nutrients, in order to assess the effect of agroforestry of some field crops with citrus trees as an approach to establish biodiversity in fruit tree plantations. Three field crops, i.e., maize, soybean and sunflower, were inter-planted with seedless orange trees (4*4 m) or were planted as solid plantings. The results for the trees indicated a larger fruit yield was obtained when soybean and sunflowers were interplant with citrus. Statistically significant effects (P<0.05) were found for maize grain and biological yields, with increased yields when grown as solid planting. There were no differences in the yields of soya bean and sunflower, where the yields were very similar between the two cropping systems. It is evident from the trials that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Maize, unlike the other crops, was more sensitive to shade conditions under agroforestry practice and not preferred in the biodiversity system. The potential of agroforestry to improve or increase biodiversity is efficient as the understorey crops are usually C4 species, and the overstorey trees are invariably C3 species in agroforestry. Improvement in interplant species is most likely if the understorey crop is a C3 species, which are usually light saturated in the open, and partial shade may have little effect on assimilation or by a concurrent reduction in transpiration. It could be concluded that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Some field crops could be employed successfully, like soybean or sunflowers, while others like maize are sensitive to incorporate in agroforestry system.

Keywords: agroforestry, field crops, C3 and C4 plants, yield

Procedia PDF Downloads 160

Authors: S. Boonlertnirun, R. Suvannasara, K. Boonlertnirun

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Hypoxia has negative effects on growth and crop yield, its severity is so varied depending on crop growth stages, duration of hypoxia and crop species. The objective was to evaluate the sensitive growth stage and the duration of hypoxia negatively affecting growth and yield of waxy corn. Pot experiment was conducted using a split plot in randomized complete block with 3 growth stages: V3 (3-4 true leaves), V7 (7-8 true leaves), and R1 (silking stage), and three hypoxic durations: 6, 9, and 12 days, in an open–ended outdoor greenhouse during January to March 2013. The results revealed that different growth stages had significantly (p < 0.5) different responses to hypoxia, seeing that the sensitive growth stage affecting plant height, yield and yield components was mostly detected in V7 growth stage whereas leaf greenness and days to silking were sensitive to hypoxia at R1 growth stage. Different hypoxic durations significantly affected the yield and yield components, hypoxic duration of twelve days showed the most negative effect greater than the others. In this present study, it can be concluded that waxy corn plants were waterlogged at V7 growth stage for twelve days had the most negative effect on yield and yield components.

Keywords: hypoxia duration, waxy corn, growth stage, Zea mays L.

Procedia PDF Downloads 358

Authors: Shirin Ghatrehsamani

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Higher efficiency and lower environmental impact are the consequence of using advanced technology in farming. They also help to decrease yield variability by diminishing weather variability impact, optimizing nutrient and pest management as well as reducing competition from weeds. A better understanding of the pros and cons of applying technology and finding the main reason for preventing the utilization of the technology has a significant impact on developing technology adoption among farmers and producers in the digital agriculture era. The results from two surveys carried out in 2019 and 2021 were used to investigate whether the crop types had an impact on the willingness to utilize technology on the farms. The main focus of the questionnaire was on utilizing precision agriculture (PA) technologies among farmers in some parts of the united states. Collected data was analyzed to determine the practical application of various technologies. The survey results showed more similarities in the main reason not to use PA between the two crop types, but the present application of using technology in specialty crops is generally five times larger than in row crops. GPS receiver applications were reported similar for both types of crops. Lack of knowledge and high cost of data handling were cited as the main problems. The most significant difference was among using variable rate technology, which was 43% for specialty crops while was reported 0% for row crops. Pest scouting and mapping were commonly used for specialty crops, while they were rarely applied for row crops. Survey respondents found yield mapping, soil sampling map, and irrigation scheduling were more valuable for specialty crops than row crops in management decisions. About 50% of the respondents would like to share the PA data in both types of crops. Almost 50 % of respondents got their PA information from retailers in both categories, and as the second source, using extension agents were more common in specialty crops than row crops.

Keywords: precision agriculture, smart farming, digital agriculture, technology adoption

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Authors: Anis Eloud, Ben Salah Nahla, Sayed Chehaibi

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In order to improve and develop the Tunisian agriculture, the government has encouraged the introduction of modern technologies and has also promoted the adoption of innovative practices cultures. Indeed, the extensive use of mechanization can increase crop productivity but its inadequate application also has a negative impact on the ground caused by the phenomenon of compaction. Which will cause the loss of soil fertility and increased production costs. This problem is accentuated with increase the stress on contact wheel / ground. For this reason, the objective of this study is to simulate the footprint of the ground contact / tire two types of tractor after their passage. The method of this work is based on a simulation including passages from two different tractors on soil with similar characteristics. Simulation parameters were based on the choice of two tractors masses of 6500 kg and 4400 kg of soil and sandy loam in nature. The analysis was performed using specific software. The main results showed that the heaviest tractor caused a constraint wheel / rear floor exceeding 100 kPa. For cons, the second tractor has caused stress wheel / rear floor of 50 kPa. The comparison of the two results showed that 6500 kg tractor made a serious and excessive compaction which generated a negative impact on soil quality and crop yields.

Keywords: compaction, soil, resistance to penetration, crop yields

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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

Procedia PDF Downloads 74

Authors: Ákos Tótin

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In crop production the most modern hybrids are available for us, therefore the yield and yield stability is determined by the agro-technology. The purpose of the experiment is to adapt the modern agrotechnology to the new type of hybrids. The long-term experiment was set up in 2015-2016 on chernozem soil in the Hajdúság (eastern Hungary). The plots were set up in 75 thousand ha-1 plant density. We examined some mainly use hybrids of Hungary. The conducted studies are: germination dynamic, growing dynamic and the effect of annual weather for the yield. We use three different sowing date as early, average and late, and measure how many plant germinated during the germination process. In the experiment, we observed the germination dynamics in 6 hybrid in 4 replication. In each replication, we counted the germinated plants in 2m long 2 row wide area. Data will be shown in the average of the 6 hybrid and 4 replication. Growing dynamics were measured from the 10cm (4-6 leaf) plant highness. We measured 10 plants’ height in two weeks replication. The yield was measured buy a special plot harvester - the Sampo Rosenlew 2010 – what measured the weight of the harvested plot and also took a sample from it. We determined the water content of the samples for the water release dynamics. After it, we calculated the yield (t/ha) of each plot at 14% of moisture content to compare them. We evaluated the data using Microsoft Excel 2015. The annual weather in each crop year define the maize germination dynamics because the amount of heat is determinative for the plants. In cooler crop year the weather is prolonged the germination. At the 2015 crop year the weather was cold in the beginning what prolonged the first sowing germination. But the second and third sowing germinated faster. In the 2016 crop year the weather was much favorable for plants so the first sowing germinated faster than in the previous year. After it the weather cooled down, therefore the second and third sowing germinated slower than the last year. The statistical data analysis program determined that there is a significant difference between the early and late sowing date growing dynamics. In 2015 the first sowing date had the highest amount of yield. The second biggest yield was in the average sowing time. The late sowing date has lowest amount of yield.

Keywords: germination, maize, sowing date, yield

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

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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: Sunita Singh, Rajani Srivastava

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For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.

Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices

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Authors: Babatunde Oluwamayokun Soyoye

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This technology, whose development revolves round culture, tradition, and prevailing needs of the people, is seen as a solution in promoting development in poor rural communities in many parts of Nigeria. The research was based on one of the food security agenda of the Federal Government of Nigeria by developing a motorized multi-grain crop planter suitable for planting operations in tropical soils. The ergonomic design is tailored towards the ease of planting operations for would-be users, improve crop yields and profitability by minimizing the cost of production. Some properties of the grain crops were determined and were used to develop and assemble the locally-made motorized planter. These properties were used in establishing the design criteria of various components of the planter. The geometric mean diameter of the maize, cowpea, groundnut, and soybean were 8.26 mm, 8.72 mm, 9.51 mm and 6.52 mm respectively, with respective groove depths of 8 mm, 7 mm, 9 mm and 6 mm. The results obtained from the evaluation of the planter confirmed that the planter has a uniform discharge and application rates. The field capacity of the planter was determined to be 0.187 ha/h. Also, the average performance efficiency of the planter was 95.5%, with the average discharge and application rates of 7.86 kg/h and 42.1 kg/ha, respectively. The motorized multi-grain planter can be used in increasing food production, reduce time, cost of production, and can become a major tool to fast-track the food security agenda of the government of Nigeria.

Keywords: design and fabrication, food security, grain crop, motorized planter

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Authors: Charles Iledun Oyewole

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The daunting challenge that the ‘man with the hoe’ is going to face in the coming decades will be complex and interwoven. With global population already above 7 billion people, it has been estimated that food (crop) production must more than double by 2050 to meet up with the world’s food requirements. Nigeria population is also expected to reach over 240 million people by 2050, at the current annual population growth of 2.61 per cent. The country’s farming population is estimated at over 65 per cent, but the country still depends on food importation to complement production. The small scale farmer, who depends on simple hand tools: hoes and cutlasses, remains the centre of agricultural production, accounting for 90 per cent of the total agricultural output and 80 per cent of the market flow. While the hoe may have been a tool for sustainable development at a time in human history, this role has been smothered by population growth, which has brought too many mouths to be fed (over 170 million), as well as many industries to fuel with raw materials. It may then be argued that the hoe is unfortunately not a tool for the coming challenges and that agricultural mechanization should be the focus. However, agriculture as an enterprise is a ‘complete wheel’ which does not work when broken, particularly, in respect to mechanization. Generally, mechanization will prompt increase production, where land is readily available; increase production, will require post-harvest handling mechanisms, crop processing and subsequent storage. An important aspect of this is readily available and favourable markets for such produce; fuel by good agricultural policies. A break in this wheel will lead to the process of mechanization crashing back to subsistence production, and probably reversal to the hoe. The focus of any agricultural policy should be to chart a course for sustainable mechanization that is environmentally friendly, that may ameliorate Nigeria’s food and raw material gaps. This is the focal point of this article.

Keywords: Crop production, Farmer, Hoes, Mechanization, Policy framework, Population, Growth, Rural areas

Procedia PDF Downloads 182

Authors: Marilyn S. Painagan

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This general objective of the study was to apply the AquaCrop model to the conditions in the municipality of Carmen, North Cotabato in terms of predicting corn yields in this area and determine the influence of rainfall and soil depth on simulated yield. The study revealed wide disparity in monthly yields as a consequence of similarly varying monthly rainfall magnitudes. It also found out that simulated yield varies with the depth of soil, which in this case was clay loam, the predominant soil in the study area. The model was found to be easy to use even with limited data and shows a vast potential for various farming and policy applications, such as formulation of a cropping calendar.

Keywords: aquacrop, evapotranspiration, crop modelling, crop simulation

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Authors: Yan Wang, Guowei Chen, Gang Wang

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Soil microbial diversity is one of the important parameters to assess the soil fertility and soil health, even stability of the ecosystem. In this paper, we aim to reveal the soil microbial difference in rhizosphere and root zone, even to pick the special biomarkers influenced by the long term tillage practices, which included four treatments of no-tillage, ridge tillage, continuous cropping with corn and crop rotation with corn and soybean. Here, high-throughput sequencing was performed to investigate the difference of bacteria in rhizosphere and root zone. The results showed a very significant difference of species richness between rhizosphere and root zone soil at the same crop rotation system (p < 0.01), and also significant difference of species richness was found between continuous cropping with corn and corn-soybean rotation treatment in the rhizosphere statement, no-tillage and ridge tillage in root zone soils. Implied by further beta diversity analysis, both tillage methods and crop rotation systems influence the soil microbial diversity and community structure in varying degree. The composition and community structure of microbes in rhizosphere and root zone soils were clustered distinctly by the beta diversity (p < 0.05). Linear discriminant analysis coupled with effect size (LEfSe) analysis of total taxa in rhizosphere picked more than 100 bacterial taxa, which were significantly more abundant than that in root zone soils, whereas the number of biomarkers was lower between the continuous cropping with corn and crop rotation treatment, the same pattern was found at no-tillage and ridge tillage treatment. Bacterial communities were greatly influenced by main environmental factors in large scale, which is the result of biological adaptation and acclimation, hence it is beneficial for optimizing agricultural practices.

Keywords: tillage methods, biomarker, biodiversity, rhizosphere

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Authors: A. B. Alarape, O. D. Aba

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The use of legume tree pruning as mulch in agroforestry system is a common practice to maintain soil organic matter and improve soil fertility in the tropics. The study was conducted to determine the influence of agroforestry trees leafy biomass and nitrogen fertilizer on crop growth rate and relative growth rate of maize. The experiments were laid out as 3 x 4 x 2 factorial in a split-split plot design with three replicates. Control, biomass species (Parkia biglobosa and Albizia lebbeck) as main plots were considered, rates of nitrogen considered include (0, 40, 80, 120 kg N ha⁻¹) as sub-plots, and maize varieties (DMR-ESR-7 and 2009 EVAT) were used as sub-sub plots. Data were analyzed using descriptive and inferential statistics (ANOVA) at α = 0.05. Incorporation of leafy biomass was significant in 2015 on Relative Growth Rate (RGR), while nitrogen application was significant on Crop Growth Rate (CGR). 2009 EVAT had higher CGR in 2015 at 4-6 and 6-8 WAP. Incorporation of Albizia leaves enhanced the growth of maize than Parkia leaves. Farmers are, therefore, encouraged to use Albizia leaves as mulch to enrich their soil for maize production and most especially, in case of availability of inorganic fertilizers. Though, production of maize with biomass and application of 120 kg N ha⁻¹ will bring better growth of maize.

Keywords: agroforestry trees, fertilizer, growth, incorporation, leafy biomass

Procedia PDF Downloads 154

Authors: Indu Bala Sethi, Meena Sewhag, Rakesh Kumar, Parveen Kumar

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Field experiment was conducted at Pulse Research Area of CCS Haryana Agricultural University, Hisar during rabi 2012-13 to study the economics of chickpea cultivars as influenced by sowing time and seed rate on sandy loam soils under irrigated conditions. The factorial experiment consisting of 24 treatment combinations with two sowing time (1st fortnight of November and 1st fortnight of December.) and four cultivars (H09-23, H08-18, C-235 and HC-1) kept in main plots while three seed rates viz. 40 kg ha-1, 50 kg ha-1 and 60 kg ha-1 was laid out in split plot design with three replications. The crop was sown with common row spacing of 30 cm as per the dates of sowing. The fertilizer was applied in the form of di- ammonium phosphate. The soil of the experimental site was deep sandy loam having pH of 7.9, EC of 0.13 dS/m and low in organic carbon (0.34%), low in available N status (193.36 kg ha-1), medium in available P2O5 (32.18 kg ha-1) and high in available K2O (249.67 kg ha-1). The crop was irrigated as and when required so as to maintain adequate soil moisture in the root zone The crop was sprayed with monocrotophos (1.25 l/ha) at initiation of flowering and at pod filling stage to protect the crop from pod borer attack. The yield was measured at the time of harvest. The cost of field preparation, sowing of seeds, thinning, weeding, plant protection, harvesting and cleaning contributed to fixed cost. The experiment was laid out in a split plot design with two sowing time (1st fortnight of November and 1st fortnight of December.) and four cultivars (H09-23, H08-18, C-235 and HC-1) kept in main plots while three seed rates viz. 40 kg ha-1, 50 kg ha-1 and 60 kg ha-1 were kept in subplots and replicated thrice. Results revealed that 1st fortnight of November sowing recorded significantly higher gross (Rs.1, 01,254 ha-1), net returns (Rs. 68,504 ha-1) and BC (3.09) ratio as compared to delayed crop of chickpea. Highest gross (Rs.91826 ha-1), net returns (Rs. 59076ha-1) and BC ratio (2.81) was recorded with H08-18. Higher value of cost of cultivation of chickpea was observed in higher seed rate than the lower ones. However no significant variation in net and gross returns was observed due to seed rates. Highest BC (2.72) ratio was recorded with 50 kg ha-1 which differs significantly from 60 kg ha-1 but was at par with 40 kg ha-1. This is because of higher grain yield obtained with 50 kg ha-1 seed rate. Net profit for farmers growing chickpea with seed rate of 50 kg ha-1 was higher than the farmers growing chickpea with seed rate of 40 and 60 kg ha.

Keywords: chickpea, cultivars, seed rate, sowing time

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Authors: Nicolae Bold, Daniel Nijloveanu

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The idea of cropping-system is a method used by farmers. It is an environmentally-friendly method, protecting the natural resources (soil, water, air, nutritive substances) and increase the production at the same time, taking into account some crop particularities. The combination of this powerful method with the concepts of genetic algorithms results into a possibility of generating sequences of crops in order to form a rotation. The usage of this type of algorithms has been efficient in solving problems related to optimization and their polynomial complexity allows them to be used at solving more difficult and various problems. In our case, the optimization consists in finding the most profitable rotation of cultures. One of the expected results is to optimize the usage of the resources, in order to minimize the costs and maximize the profit. In order to achieve these goals, a genetic algorithm was designed. This algorithm ensures the finding of several optimized solutions of cropping-systems possibilities which have the highest profit and, thus, which minimize the costs. The algorithm uses genetic-based methods (mutation, crossover) and structures (genes, chromosomes). A cropping-system possibility will be considered a chromosome and a crop within the rotation is a gene within a chromosome. Results about the efficiency of this method will be presented in a special section. The implementation of this method would bring benefits into the activity of the farmers by giving them hints and helping them to use the resources efficiently.

Keywords: chromosomes, cropping, genetic algorithm, genes

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Authors: K. C. Sony

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This paper investigates the coping strategies of households confronting disease in large cardamom (Amomum Subulatum Roxb.) in eastern Nepal. Cardamom farmers draw on various coping strategies to reduce the impact of crop disease in their livelihoods. Yet farmers face tremendous decline in production with a constant effort for revival. Past evidences provides dearth of information about coping strategies employed by farmers and institutional intervention to combat disease. Using factual data from Ilam district, and conducting a political economic analysis, this research addresses the gap by 1) understanding the impact of crop disease in farmers’ livelihoods, 2) identifying the coping strategies adopted by farmers and, 3) examining the existing institutional arrangements to address the disease. Coping strategies vary by household’s status defined by size of land, alternative income, and access to supporting institutions. Measures adopted are burning the cardamom field, changing land use pattern, diversifying crops, and visiting institutions for support. The local government’s support is limited to providing trainings and producing new varieties of cardamom. During crisis, farmers expect institutions to help revive the cardamom production, despite customary practice to combat disease. To retain and improve the livelihoods of farmers, there needs to be institutional innovation at the community level and policies that endorse immediate and sustainable support during hazards.

Keywords: cardamom, coping strategy, disease, institutions, Nepal

Procedia PDF Downloads 265

Authors: Abraham Castro-Alvarez, Luisaldo Sandate-Flores, Roberto Parra-Saldivar

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The losing of crops during the whole production process is a problem that is affecting farmers in the whole world, as climate change affects the weather behavior. Stenocereus spp. is a tropical, exotic and endemic columnar cacti, it produces a colored and expensive fruit known how “pitaya”. The quality and value of the fruit, these species represent an attractive option for economical development in arid and semi-arid regions. This fruits are produced in Mexico, mainly in 4 regions, Mixteca Oaxaca-Puebla, Michoacan, Sinaloa-Sonora, Jalisco-Zacatecas. Pitaya can be an option to try mixed crop in this states due to the resistance to hard weather conditions. And also because of the marginalization problems that exist in these townships. As defined by the Population National Council it consists in the absence of development opportunities and the lack of capacity to get them. According to an analysis done in EsriPress ArcGis 10.1 the potential area in the country is almost the half of the territory being the total area of Mexico 1,965,249 km2 and the area with potential to produce pitaya 960,527 km2. This area covers part of the most affected townships that also have a few options of maize varieties making even harder the production of maize and exposing farmers to crop losing if conditions are good enough. Making pitaya a good option for these farmers to have an economic backup in their productions.

Keywords: maize, pitaya, rain fed, Stenocereus

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Authors: Getinet Gezahegn Gebre

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The study examined the impact of gender differences on Crop productivity in Decha woreda of southwest Kafa zone, located 140 Km from Jimma Town and 460 km southwest of Addis Ababa, between Bonga town and Omo River. The specific objectives were to assess the extent to which the agricultural production system is gender oriented, to examine access and control over productive resources, and to estimate men’s and women’s productivity in agriculture. Cross-sectional data collected from a total of 140 respondents were used in this study, whereby 65 were female-headed and 75 were male-headed households. The data were analyzed by using Statistical Package for Social Science (SPSS). Descriptive statistics such as frequency, mean, percentage, t-test and chi-square were used to summarize and compare the information between the two groups. Moreover, Cobb-Douglas(CD) production function was used to estimate the productivity difference in agriculture between male and female-headed households. Results of the study showed that male-headed households (MHH) own more productive resources such as land, livestock, labor and other agricultural inputs as compared to female-headed households (FHH). Moreover, the estimate of CD production function shows that livestock, herbicide use, land size and male labor were statistically significant for MHH, while livestock, land size, herbicides use and female labor were significant variables for FHH. The crop productivity difference between MHH and FHH was about 68.83% in the study area. However, if FHH had equal access to the inputs as MHH, the gross value of the output would be higher by 23.58% for FHH. This might suggest that FHH would be more productive than MHH if they had equal access to inputs as MHH. Based on the results obtained, the following policy implication can be drawn: accessing FHH to inputs that increase the productivity of agriculture, such as herbicides, livestock and male labor; increasing the productivity of land; and introducing technologies that reduce the time and energy of women, especially for enset processing.

Keywords: gender difference, crop productivity, GDP, efficiency

Procedia PDF Downloads 41

Authors: Okwara O. S., Osunsina I. O. O., Pitan O. R., Afolabi C. G.

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Rice (Oryza sativa L.) belongs to the family poaceae and has become the most popular food. Globally, this crop is been faced with the menace of vertebrate pests, of which birds and rodents are the most implicated. The study avian and rodents’ infestations and the evaluation of attributable losses was carried out in 2020 and 2021 with the objectives of identifying the types of bird and rodent species associated with lowland rice and to determine the infestation levels, damage intensity, and the crop loss induced by these pests. The experiment was laid out in a split plot arrangement fitted into a Randomized Complete Block Design (RCBD), with the main plots being protected and unprotected groups and the sub-plots being four rice varieties, Ofada, WITA-4, NERICA L-34, and Arica-3. Data collection was done over a 16-week period, and the data obtained were transformed using square root transformation model before Analysis of Variance (ANOVA) was done at 5% probability level. The results showed the infestation levels of both birds and rodents across all the treatment means of thevarieties as not significantly different (p > 0.05) in both seasons. The damage intensity by these pests in both years were also not significantly different (p > 0.05) among the means of the varieties, which explains the diverse feeding nature of birds and rodents when it comes to infestations. The infestation level under the protected group was significantly lower (p < 0.05) than the infestation level recorded under the unprotected group.Consequently, an estimated crop loss of 91.94 % and 90.75 % were recorded in 2020 and 2021, respectively, andthe identified pest birds were Ploceus melanocephalus, Ploceus cuculatus, and Spermestes cucullatus. Conclusively, vertebrates pest cause damage to lowland rice which could result to a high percentage crop loss if left uncontrolled.

Keywords: pests, infestations, evaluation, losses, rodents, avian

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Authors: Ashkan Asgari, Korous Khoshbakht, Saeid Soufizadeh

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Various factors including land lots can affect biodiversity indices in Agricultural systems. Field study conducted to evaluate factors affecting crop diversity in Sarpolzahab in 2012. Required data were collected through direct observation of farms and filling questionnaires. Total numbers of 140 questionnaires were filled, SAS Software was used to analyse data and Ecological Methodology Program was applied to calculate Shannon-Winner index, subsequently. Results of study indicated that average number of land lots for each farmer was 2.78 and various from 2.2 in Rikhak Olia Village to 4.31 in Golam Kaboud Olia Village which shows small size of land lots due to separating larger lots by children of deceased farmers. The correlation between number of land lots and species biodiversity (0.308**) was significant and Shannon-Winner index was (0.262**). Therefore, according to the mentioned results one can assume that increase in number of land lots results in improving of the target index. Multiple land lots allow farmers to cultivate various crops which results in increasing biodiversity of crops in agro ecosystem. Subsequently, this increase will facilitate economic sustainability of the farmers and distribution of work force in the region throughout the year. The correlation of seasonal workers with biodiversity of crop species (0.256**) and Shannon-Winner (0.286**) was statistically significant and increasing number of seasonal work forces had resulted in improving crop biodiversity and decreasing dominant species or single crop farming systems. Vegetable farms which have a significant diversity, require a significant number of work forces which describes correlation between number of workers and diversity of species.

Keywords: agricultural systems, biodiversity indices, Shannon-Winner index, sustainability, rural

Procedia PDF Downloads 501