Crop Production In Areas Research Articles

Organic farming practices utilizing spent microbial biomass from an industrial fermentation facility promote transition to copiotrophic soil communities.

Organic farming has become more prevalent in recent years as consumer demand for organic food and fiber has rapidly grown. Until recently, organic fertilizers and soil amendments have largely been based on the practices of returning crop residues, manures and related agricultural wastes back to crop production areas. One rapidly growing segment in commercial organic fertilizer development is the use of spent microbial biomass (SMB) from industrial fermentation processes. While SMB is widely accepted in many organic farming systems (OFS), little is known concerning the effectiveness, environmental impact, and influence on prokaryotic communities in soils receiving this treatment. In this study, a comparative analysis of bacterial communities associated with OFS and conventional farming systems was performed over a growing season for a field containing yellow dent corn (Zea mays). A statistically significant increase in microbial population α-diversity, along with a strong recruitment of Proteobacteria and Actinobacteria populations, was observed in soils treated with SMB when compared to areas in the field that utilized conventional farmer practices. These phyla are members of the copiotrophic subgroup, and considered a signature for the use of traditional organic fertilizers. These results provide valuable new information that SMB functions similarly to traditional organic fertilizers in promoting a high level of functional prokaryotic diversity and plant growth-promoting bacteria, but in contrast do not contribute directly to viable microorganisms in the soil due to the sterilization of SMB prior to land application.

Understanding photothermal interactions will help expand production range and increase genetic diversity of lentil (Lens culinarisMedik.)

Societal Impact StatementLentil is a staple in many diets around the world and growing in popularity as a quick‐cooking, nutritious, plant‐based source of protein in the human diet. Lentil varieties are usually grown close to where they were bred. Future climate change scenarios will result in increased temperatures and shifts in lentil crop production areas, necessitating expanded breeding efforts. We show how we can use a daylength and temperature model to identify varieties most likely to succeed in these new environments, expand genetic diversity, and give plant breeders additional knowledge and tools to help mitigate these changes for lentil producers.SummaryLentil (Lens culinarisMedik.) is cultivated under a wide range of environmental conditions, which has led to diverse phenological adaptations and resulted in a decrease in genetic variability within breeding programs due to reluctance in using genotypes from other environments.We phenotyped 324 genotypes across nine locations over three years to assess their phenological response to the environment of major lentil production regions and to predict days from sowing to flowering (DTF) using a photothermal model.DTF was highly influenced by the environment and is sufficient to explain adaptation. We were able to predict DTF reliably in most environments using a simple photothermal model, however, in certain site‐years, results suggest there may be additional environmental factors at play. Hierarchical clustering of principal components revealed the presence of eight groups based on the responses of DTF to contrasting environments. These groups are associated with the coefficients of the photothermal model and revealed differences in temperature and photoperiod sensitivity.Future climate change scenarios will result in increased temperature and/or shifts in production areas. The ability to use the photothermal model to identify genotypes most likely to succeed in these new environments has important social impacts with respect to traditional cropping systems.

Examining the effects of green revolution led agricultural expansion on net ecosystem service values in India using multiple valuation approaches

Ecosystem Services (ESs) are bundles of natural processes and functions that are essential for human well-being, subsistence, and livelihoods. The ‘Green Revolution’ (GR) has substantial impact on the agricultural landscape and ESs in India. However, the effects of GR on ESs have not been adequately documented and analyzed. This leads to the main hypothesis of this work – ‘the incremental trend of ESs in India is mainly prompted by GR led agricultural innovations that took place during 1960 - 1970’. The analysis was carried out through five successive steps. First, the spatiotemporal Ecosystem Service Values (ESVs) in Billion US$ for 1985, 1995, and 2005 were estimated using several value transfer approaches. Second, the sensitivity and elasticity of different ESs to land conversion were carried out using coefficient of sensitivity and coefficient of elasticity. Third, the Geographically Weighted Regression model was performed using five explanatory factors, i.e., total crop area, crop production, crop yield, net irrigated area, and cropping intensity, to explore the cumulative and individual effects of these driving factors on ESVs. Fourth, Multi-Layer Perceptron based Artificial Neural Network was employed to estimate the normalized importance of these explanatory factors. Fifth, simple and multiple linear regression modeling was done to assess the linear associations between the driving factors and the ESs. During the observation periods, cropland, forestland and water bodies contributed to 80%–90% of ESVs, followed by grassland, mangrove, wetland and urban built-up. In all three evaluation years, the highest estimated ESVs among the nine ES categories was provided by water regulation, followed by soil formation and soil-water retention, biodiversity maintenance, waste treatment, climate regulation, and greenhouse gas regulation. Among the five explanatory factors, total crop area, crop production, and net irrigated area showed strong positive associations with ESVs, while cropping intensity exhibited a negative association. Therefore, the study reveals a strong association between GR led agricultural expansion and ESVs in India. This study suggests that there should be an urgent need for formulation of rigorous ecosystem management strategies and policies to preserve ecological integrity and flow of uninterrupted ESs and to sustain human well-being.

COMBINING ABILITY OF GRAIN SORGHUM INBRED LINES GROWN DURING OFF-SEASON

ABSTRACT The expansion of sorghum as a succession crop, after soybean, has demanded the development of new inbred lines by the breeding programs. The first step in the selection process consists of evaluating the performance per se of the inbred lines or of their hybrid combination. The purpose of this study was to determine the combining ability of sorghum inbred lines under different environment conditions of the crop production areas. The trials were carried out in the second season of 2017, under no-tillage system, in four environments, Rio Verde, Sete Lagoas, Teresina and Sinop. Thirty hybrids, resulting from the crosses of six fertility restoration lines (R) with five male-sterile lines (A) were evaluated. A randomized complete block design with three replicates was used in all experiments. The characteristics evaluated were flowering, plant height and grain yield. The environment significantly influenced the estimates of general and specific combining ability, which suggests that both effects, additive and dominant, are important in the control of these characters. The restoring lines GI.1 and G1.2 contributed to increasing the grain yield of their hybrids by over 650 kg.ha-1. Among the male-sterile lines, the best for grain yield were GII. 1 and GII.4 with contribution above 450 kg.ha-1 in the hybrids in which they participate. The hybrid combinations GI.5xGII.3 and GI.1xGII.2 stood out with potential to obtain high grain yield, associating positive aspects of the other characteristics.

Effect of source of irrigation water on yield performance of Boro rice

Industrial wastewater is a major problem in Gazipur, Bangladesh which is very cheaply available in the surrounding area for crop production. An experiment was conducted at Farmer’s Field of Gazipur district to study the effect of irrigation water quality on yield of boro rice. The study comprised three varieties viz., BR14, BRRI dhan28 and BRRI dhan29 and three sources of irrigation water viz. fresh water irrigation, mixed water (fresh + industrial wastewater) irrigation, industrial wastewater irrigation. The experiment was laid out in a split-plot design with three replications where irrigation water was assigned in the main plot and rice varieties in the subplot. BRRI dhan29 produced the tallest plant (85.25 cm), the highest number of total tillers hill-1 (19.77), effective tillers hill-1 (17.64), grains panicle-1 (111.0), sterile spikelets panicle-1 (44.29), 1000-grain weight (22.43 g), grain yield (4.56 t ha-1) and straw yield (7.99 t ha-1). On the other hand, plant height (74.50 cm), total tillers hill-1 (19.82), effective tillers hill-1 (17.53), grains panicle-1 (131.7), sterile spikelets panicle-1 (35.50), 1000-grain weight (25.83 g), grain yield (5.05 t ha-1) were found highest when applied fresh water irrigation. The highest numbers of grains panicle-1 (119.14), 1000-grain weight (25.10 g), grain (5.54 t ha-1) and straw (7.93 t ha-1) yield were obtained in BRRI dhan29 with fresh water irrigation. Therefore, BRRI dhan29 with fresh water irrigation would be safe to use. However, if fresh water irrigation is not possible, conjunctive use of fresh and wastewater can be used as irrigation for BRRI dhan29.

Effect of silicon on aphid populations and wheat yield in Minas Gerais, Brazil

The area cultivated with wheat has been increasing in the savannahs of the state of Minas Gerais, Brazil. Aphids are usually one of the main pests of wheat in many regions of the world; however, little is known about the aphid population in this new environment. The southern region of Brazil, the main wheat production area, has had several problems as a result of aphids, but aphid populations and the resulting impact on wheat production have not been investigated in these new crop production areas. Understanding control strategies to manage this insect could be essential for the “Cerrado” wheat that is grown in this area. The application of silicon (Si) has the potential to reduce the population growth of wheat aphids; however no field studies have been reported. Hence, we evaluated the effect of Si fertilization via soil application on the aphid populations and species composition and on yield components of wheat in three locations in Minas Gerais; the experiment was repeated simultaneously in Uberlândia, at the experimental areas of UFU and IFTM, and in Montes Claros, at the experimental area of UFMG, using the cultivars BRS 264 and BRS 394. The aphids first appeared just before wheat earing; they were then sampled six times over the course of the study, seven days apart, starting from 45 days after sowing. The aphid species Sitobion avenae (Fabricius), Schizaphis graminum (Rondani), and Rhopalosiphum padi (Linnaeus) were observed in all three locations; S. avenae was the dominant species in all locations. The experimental area of UFU had the highest number of S. avenae aphids per tiller for both cultivars, while UFMG had the lowest populations. Aphid populations and wheat yield components were not affected by soil Si fertilization. There was no difference in yield as a result of location or cultivar, but the location UFU and the cultivar BRS 394 had the greatest average hectoliter weight.

ҚАЗАҚСТАННЫҢ ОҢТҮСТІК ӨҢІРІНІҢ АГРОҚҰРЫЛЫМДАРЫН ДАМЫТУ

The article defines the priority areas of crop and livestock production for the intensive development of industries in the southern region of the republic, considers the problems of the development of agro-industrial sector. The characteristic of production of main types of crop and livestock products is presented. The natural potential of this territory has the potential for cultivating such crops as corn, soybeans, sugar beets, cotton, and large areas of pastures. The population number of livestock of cattle, sheep, poultry, pigs, the area of pasture land, the yield of vegetables and potatoes, the volume of production of cattle meat, lamb, the concentration of meat and dairy animals in the context of regions are shown. The assessment of the competitiveness of the manufactured products is presented. Potential, targets and prospects for increasing agricultural production have been identified. Proposals have been developed for deepening specialization in beef cattle breeding, developing the industry on an industrial basis through intensification, favorable natural and climatic conditions that allow organizing outdoor feeding farms, creating zones for growing young animals, irrigation systems that ensure the expansion of crops for fodder grain. The authors concluded that it is necessary to develop fine-wool sheep breeding on the basis of intensive technologies, with the production of lamb and fine wool, using new breeds of meat merino, as well as meat sheep breeding to saturate the domestic market with mutton and dairy cattle in order to fully provide the population with whole milk products.

Impacts of Climatic and Agricultural Input Factors on the Water Footprint of Crop Production in Jilin Province, China

Water consumption ensures crop production and grain security, and is influenced by many factors. Analyzing the impact factors of water consumption during crop production will be beneficial to the full use of water resources and crop growth. Jilin Province is one of the major crop production areas in China and is facing water shortages. Using the water footprint as an indicator, this study evaluated the water consumption of crop production in Jilin Province during 2000–2016, explored the impacts of climatic and agricultural input factors on the water consumption of crop production, and identified the most influential factors in years under different levels of rainfall. The results indicate that the crop water footprint exhibited a decreasing trend during 2000–2016, and the most influential factors of the crop water footprint changed over the years with different levels of rainfall. Precipitation and the effective irrigation area were the most influential factors in the drought year, and accumulated temperature, machinery power, and chemical fertilizer consumption were the most influential factors in normal and humid years. The most influential factors of the crop water footprint differed in different regions with the differences in natural and human interfered conditions. Identifying the impacts of the most influential factors on the water consumption of crop production would be conducive to optimizing farmland management and achieving sustainable agricultural production.

Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008\u20132015

While food insecurity is a persistent public health challenge, its long-term association with depression at a national level is unknown. We investigated the spatial heterogeneity of food insecurity and its association with depression in South Africa (SA), using nationally-representative panel data from the South African National Income Dynamics Study (years 2008–2015). Geographical clusters (“hotpots”) of food insecurity were identified using Kulldorff spatial scan statistic in SaTScan. Regression models were fitted to assess association between residing in food insecure hotspot communities and depression. Surprisingly, we found food insecurity hotspots (p < 0.001) in high-suitability agricultural crop and livestock production areas with reliable rainfall and fertile soils. At baseline (N = 15,630), we found greater likelihood of depression in individuals residing in food insecure hotspot communities [adjusted relative risk (aRR) = 1.13, 95% CI:1.01–1.27] using a generalized linear regression model. When the panel analysis was limited to 8,801 participants who were depression free at baseline, residing in a food insecure hotspot community was significantly associated with higher subsequent incidence of depression (aRR = 1.11, 95% CI:1.01–1.22) using a generalized estimating equation regression model. The association persisted even after controlling for multiple socioeconomic factors and household food insecurity. We identified spatial heterogeneity of food insecurity at a national scale in SA, with a demonstrated greater risk of incident depression in hotspots. More importantly, our finding points to the “Food Security Paradox”, food insecurity in areas with high food-producing potential. There is a need for place-based policy interventions that target communities vulnerable to food insecurity, to reduce the burden of depression.

Crop production in the USA is frequently limited by a lack of pollinators.

Most of the world's crops depend on pollinators, so declines in both managed and wild bees raise concerns about food security. However, the degree to which insect pollination is actually limiting current crop production is poorly understood, as is the role of wild species (as opposed to managed honeybees) in pollinating crops, particularly in intensive production areas. We established a nationwide study to assess the extent of pollinator limitation in seven crops at 131 locations situated across major crop-producing areas of the USA. We found that five out of seven crops showed evidence of pollinator limitation. Wild bees and honeybees provided comparable amounts of pollination for most crops, even in agriculturally intensive regions. We estimated the nationwide annual production value of wild pollinators to the seven crops we studied at over $1.5 billion; the value of wild bee pollination of all pollinator-dependent crops would be much greater. Our findings show that pollinator declines could translate directly into decreased yields or production for most of the crops studied, and that wild species contribute substantially to pollination of most study crops in major crop-producing regions.

Selection of Wireless Technologies for Use in Agriculture

Since the advent of early agriculture, agriculture has sought to increase yields. The continuous development of tools and fertilizers, the cultivation of plants and animals, the accumulation of knowledge about the processes of product growth began more than 10,000 years ago and continues to this day. The modern development of transport has made it possible to achieve the indices of humanity unprecedented before.In recent years, the introduction of Internet technologies, satellite communication and geopositioning, robotics, sensors and automation systems has begun in agriculture. In 2016, GPS and GLONASS have already been implemented and are being actively used in agriculture, which made it possible to improve the accuracy of machinery movement across the field. The transition to robotic transport enabled precise parallel movement. The use of sensitive sensors allows you to monitor the condition of the soil, accurately take into account its composition in small areas and make fertilizers where necessary.Thanks to these technologies, the field of "precision farming" is spreading. UAVs are being used to monitor crops, spray fertilizers and insect repellents. And the implementation of technology is ongoing. It is anticipated that the application of Big Data in agriculture will significantly improve the quality of knowledge about the processes that occur when growing products. Now 2016-2018 is called "experimental" and predicts the rapid development of smart agriculture in 2019-2020 and subsequent years.In the areas of high-precision agriculture, land management and crop production, there are ample opportunities for the use of IoT technologies. In particular, the ability to monitor soil parameters - its temperature, humidity and moisture capacity, which is necessary for optimal irrigation and fertilization, as well as environmental parameters of land. Remote monitoring and control of these parameters requires the use of wireless technologies. Different ways of data transmission, their advantages and disadvantages in the energy plan, dependence on external factors, range and method of information transfer were considered in the article. On this basis, the conclusions about the most appropriate to use the system of data transmission from greenhouses to the server, which in turn have less energy consumption and the most optimal for data transmission, also considered the feasibility of using certain methods of charging, depending on their advantages.

ҚОРАҚАЛПОҒИСТОН ВА ТОШКЕНТ ВИЛОЯТИ ЎСИМЛИКЛАРНИ ЭКОТИЗИМ ХИЗМАТЛАРИНИ ИҚТИСОДИЙ БАҲОЛАШ

The given research work aims to analyze Ecosystem Services of crop production area of Uzbekistan, mainly in two regions: Republic of Karakalpakstan and Tashkent Province. After analysis, I will try to give proper assessment of ecosystem service using socio-economic quantification of Ecosystem Services. Mainly the market price valuation method is applied in this research.

「農業構造調整政策」下における伝統的商品作物産地の変容と課題 : 中国重慶直轄市F区Z鎮、N鎮の農村を事例に

「農業構造調整政策」下における伝統的商品作物産地の変容と課題 : 中国重慶直轄市F区Z鎮、N鎮の農村を事例に

Spray nozzle performance on wheat

Fungal diseases in wheat crops (Triticum aestivum) cause significant yield and quality grain losses worldwide. The increase in the crop production area under no-tillage and environmental changes has favored residue-borne fungal survival and, therefore, disease development. Field trials were carried out at the beginning of anthesis on wheat crops (state z61), in order to evaluate different spray nozzle performance. The test was arranged in a 4x2 factorial design with ten repetitions. Factors consisted in four nozzles: flat-fan (XR11002), air induction asymmetrical dual flat-fan (AI3070-02), air induction symmetrical dual flat-fan (GAT11002), hollow cone (TXA8002), and two artificial targets, one vertical and another horizontal related to head and flag leaf location, respectively. Water-sensitive cards and CIR 1.5® software were used to determine droplet density (DD), coverage, and deposition. The latter was contrasted using Brilliant Blue tracer. Data were subjected to anova and means were compared by Tukey test (p≤0,05). The use of fine droplets and multiple directions such as TXA8002 increases coverage and deposition in the vertical and horizontal target, under optimum environmental conditions. The methodologies used to evaluate spraying performance are complementary to completely characterize the application parameters.

Preface

The 2nd International Conference on Food Security and Sustainable Agriculture in the Tropic (IC-FSSAT 2019) was held in Makassar, Indonesia on September 2 2019. As in previous conference, IC-FSSAT 2019 is dedicated to address issues related to food security and sustainable agriculture in the Tropics. This event was hosted by Faculty of Agriculture and Publication Management Centre (PMC), Universitas Hasanuddin.The major goal and feature of the conference was to promote knowledge, science, and technology as well as to address issues in food security and sustainable agriculture in the tropics, by bringing together researchers, scientists, practitioners and scholars in the respected fields. While food security and sustainable agriculture issues had been discussed broadly in several conferences, our conference emphasizes on the tropical agriculture. A total of 7 Keynote/Invited Speakers from Australia, Germany, Taiwan, Czechoslovakia, Japan and Indonesia delivered an insight into the state of art of the challenges in food security and sustainable agriculture in the tropics and any possibilities that could arise in developing integrated problem solving and collaboration to create better world.This proceedings present selected papers submitted to the conference by academics and researches from universities and research institutes. All papers were subjected to rigorous peer-reviews by conference committee members and international reviewers to ensure their compliance to meet the required standard for qualified scientific publication. This volume presents recent researches in the field of Food Security and Sustainable Agriculture in the Tropic covering various related areas of Crop Production and Environment, Plant Breeding and Biotechnology, Biodiversity and Climate Change, Integrated Pest and Disease Management, Genetically Modified Foods, Food Safety, and Product Development, Geospatial Agriculture, Agricultural Engineering and Sustainable Agriculture and Rural Development.

A multi-model analysis of teleconnected crop yield variability in a range of cropping systems

Abstract. Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño–Southern Oscillation (ENSO), which has been found to impact crop yields on all continents that produce crops, while two other climate oscillations – the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) – have been shown to especially impact crop production in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD, and NAO on the growing conditions of maize, rice, soybean, and wheat at the global scale by utilising crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that, while accounting for their potential co-variation, climate oscillations are correlated with simulated crop yield variability to a wide extent (half of all maize and wheat harvested areas for ENSO) and in several important crop-producing areas, e.g. in North America (ENSO, wheat), Australia (IOD and ENSO, wheat), and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed and fully fertilised scenarios, while the sensitivity tends to be lower if crops were to be fully irrigated. Since the development of ENSO, IOD, and NAO can potentially be forecasted well in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate-related shocks.

Richness and diversity of odonates of the agricultural college and research institute, Vazhavachanur, Tamilnadu, India

Investigations on the diversity of Odonata in and around the Agricultural College and Research Institute, Vazhavachanur, Tamil Nadu, India were studied. Eight locations were selected, of which sixteen Odonata species were recorded. In total, eleven dragonfly and five damselfly species were identified from Thiruvannamalai district, Tamil Nadu, India. Pantala flavescens, Diplacodes trivialis, Brachythemis contaminata and Ischnura aurora were recorded from all eight locations. Trithemis pallidinervis and Agriocnemis pygmaea were recorded from seven locations except from the farm pond and the open stretch area. Rhyothemis variegata was recorded only at the open stretch area. The results clearly show that, Odonates have specific habitat preferences for their growth and development. Four families Libellulidae, Gomphidae, Aeshnidae and Coenagrionidae were observed and collected during the study. Libellulidae were the most abundant family (56.25%) and comprised of 9 species, followed by Coenagrionidae (31.25%) with 5 species. Low species abundance was recorded within the Gomphidae and Aeshnidae families with 6.25% each. Simpson and Shannon Index showed maximum diversity in the open stretch area (0.8743 and 2.186, respectively) and minimum in location 8 (crop production area) and location 4 (Sathakuppam), respectively. Open stretch area showed maximum Richness Index (Margalef) (2.275) followed by farm pond (2.196) where recorded minimum in sathakuppam (1.276) location. Equitability J index, maximum species evenness (0.788) was recorded Location 6 i.e. farm pond (0.6727) followed by open stretch area 0.686.

Rapid Design System for Agricultural Machinery Employing Knowledge-Based Engineering: Case Study of A Wheeled Combine Chassis

Abstract. Highlights A knowledge-based rapid design system for combine chassis is proposed. The object-oriented knowledge representation uniformly describes the multi-source heterogeneous design knowledge. The multivariate linear regression analysis ratiocinates further unknown design principles behind existing products. Abstract. In the design of agricultural machinery, the lack of systematic and structured knowledge utilization systems results in low development efficiency and poor reusability of design knowledge. This paper considers the design of a combine chassis, and focuses on the application of knowledge-based rapid design to agricultural machinery. As a typical sophisticated agricultural machine, combines have a complicated design that requires the integration of multiple disciplines according to the crop types, production areas, and ability of the designers. Hence, a knowledge-based design system for a wheeled combine chassis is proposed. By integrating object-oriented technology with a mixed reasoning strategy, multi-source heterogeneous design knowledge can be applied in completing the chassis design task. To date, there are more than 2000 design ideas and 350 parameter models in the knowledge database. In addition, tacit design knowledge acquired by a knowledge discovery method can be employed to perfect the design and improve the reliability of the product. The design of a combine chassis demonstrates that the knowledge-based rapid design of agricultural machinery is completely feasible, and the design system significantly reduces the design workload, shortens the development cycle, and improves design efficiency and knowledge utilization.

Rapid Design System for Agricultural Machinery Using Knowledge-Based Engineering: Case Study of a Wheeled Combine Chassis

HighlightsA knowledge-based rapid design system for combine chassis is proposed.Object-oriented knowledge representation uniformly describes the multi-source heterogeneous design knowledge.Multivariate linear regression analysis ratiocinates further unknown design principles behind existing products.Abstract. In the design of agricultural machinery, the lack of systematic and structured knowledge utilization systems results in low development efficiency and poor reusability of design knowledge. This study considers the design of a combine chassis and focuses on the application of knowledge-based rapid design to agricultural machinery. As a typical sophisticated agricultural machine, combines have a complicated design that requires the integration of multiple disciplines according to the crop types, production areas, and ability of the designers. Hence, a knowledge-based design system for a wheeled combine chassis is proposed. By integrating object-oriented technology with a mixed reasoning strategy, multi-source heterogeneous design knowledge can be applied in completing the chassis design task. To date, there are more than 2000 design ideas and 350 parameter models in the knowledge database. In addition, tacit design knowledge acquired by a knowledge discovery method can be employed to perfect the design and improve the reliability of the product. The design of a combine chassis demonstrates that the knowledge-based rapid design of agricultural machinery is completely feasible, and the design system significantly reduces the design workload, shortens the development cycle, and improves design efficiency and knowledge utilization. Keywords: Combine chassis, Knowledge-based design system, Knowledge-based engineering, Rapid design.

Domates (Solanum lycopersicum L.) Bitkisinin Büyüme Derece-Gün Değerlerinin Modellenmesi: Çukurova Yöresi Örneği

Çalışmada ülkemizde en çok yetiştirilen sebzeler arasında yer alan domates bitkisi araştırmanın konusu olarak seçilmiştir. Domates üretiminde Çukurova yöresi son yıllarda giderek artan bir üretim potansiyeline sahiptir. Dolayısıyla çalışma alanı olarak Çukurova yöresi seçilmiştir. Çalışmada araştırma alanındaki illere ait uzun yıllık sıcaklık ve yağış değerleri çalışmanın materyalini oluşturmuştur. Çalışmada Büyüme Derece-Gün (BDG) yöntemi kullanılmıştır. Domates bitkisinin gelişim evreleri için denge sıcaklıkları seçilmiş, gelişim dönemlerindeki denge sıcaklık değerlerine göre BDG değerleri hesaplanmıştır. Hesaplanan bu değerler irdelenerek araştırma alanındaki illerin yetiştiricilik açısından uygunluğu belirlenmeye çalışılmıştır. Çalışmadan elde edilen veriler doğrultusunda Mersin ilinin ön plana çıktığı kanısına varılmıştır. Bitkisel üretim alanlarının önceden belirlenmesi ve bu alanlara göre üretim yapılması verimi olumlu yönde etkileyecektir. Dolayısıyla üreticinin gelirinin artması ülke ekonomisine de olumlu yönde katkı sağlayacaktır. Ayrıca, domates bitkisinin gelişim evreleri için seçilen temel sıcaklık değerlerine göre çoklu doğrusal olmayan regresyon denklemleri geliştirilmiştir. Sonuç olarak, geliştirilen bu denklemler kullanılarak domates bitkisinin BDG değerlerini etkileyen değişkenler sayesinde domatesin gelişimi hakkında önceden bilgi sahibi olunacağı kanısına varılmıştır.