Row Planting Research Articles

Determination of Optimal Plant Density of Adapted Maize Varieties in the Low and Mid-altitude Ecologies of Tanzania

Purpose: The objective of this study is to validate the commonly recommended plant density in the target zone to maximize maize production and productivity. The commonly recommended plant density is 44,444 plants/ha for decades. However, there is no recent study done to validate this practice if it optimizes productivity under current climate and soil fertility variability. A blanket recommendation has been used for decades without validation for optimum productivity that farmer can realize. 
 Methodology: The factorial experiment was used with the total of 18 treatment combinations in a Randomized Complete Block Design (RCBD) with three replications according to Gomez, A and Gomez, K (1983). The open pollinated varieties (OPV) commonly grown by small scale farmers were planted in three different plant densities of 44,444, 53,333 and 66,666 plants per hector with inter and intra row spacings of 0.75mx0.3m, 0.75mx0.25m and 0.75mx0.2m respectively. Field management was done as usual following the recommended agronomic practices.
 Findings: Analysis of variance (ANOVA) was done using GENSTAT (9th edition) statistical programme software and presented in a tabular form. The results indicated no significant difference in all parameters analysed except for 50% anthesis days (AD) and 50% Silking days (SD) both at 0.1% levels. The overall site mean for grain yield was found to be 6.43t/ha, 7.31t/ha and 6.11t/ha for the plant density of 44,444plants/ha, 53,333plants/ha and 66,666plants/ha respectively. Therefore, based on these findings the optimum plant density was found to be 53,333/ha unlike the commonly used plant density of 44,444 plants/ha.
 Unique Contribution to Theory, Practice and Policy: This study contributes to existing experience and practice commonly recommended by extension officers in many parts of the country without performing a site-specific study to determine the optimum spacing for particular environment. This, study also open up an avenue for further research to validate various research technologies. Plant population, in addition to plant height, maturity class, and row spacings, affects the geometry of plant spacing and leaf distribution. All these factors may affect light and CO2 penetration in the canopy, as well as water use rate (Tharp, B and Kells, J, 2001)

Growing Coffea canephora in agroforestry systems with Brazilian firetree, Brazil nut, and teak

Planting coffee in agroforestry systems (AFSs) provides diverse advantages to farmers interested in producing environmental services, such as increased local biodiversity, reduction in soil erosion, improvement in water infiltration into the soil, and regulation of climate extremes. It can also be economically attractive due to the possibility of serving alternative markets that have higher and more stable prices for coffees integrated into alternative systems and the generation of products complementary to coffee. This study aimed to evaluate the effects of different planting densities of three forest species on the composition of AFSs with coffee plants under the conditions of the southwestern Amazon region. The study was conducted from November 2014 to June 2021 in the experimental field of Embrapa in Ouro Preto do Oeste, RO, Brazil. The coffee plants were intercropped with three forest species: i) Brazilian firetree (Schizolobium parahyba var. amazonicum), ii) Brazil nut (Bertholletia excelsa), and iii) teak (Tectona grandis). The treatments used in each experiment were four plant densities of plants: zero (coffee plants only, in full sun), 111 plants ha−1 (10 × 9 m), 222 plants ha−1 (10 × 4.5 m), and 444 plants ha−1 (5 × 4.5 m). The experiments were conducted in a split-plot arrangement, with plots consisting of plant densities and subplots consisting of harvest periods (crop seasons). The experimental design was completely randomized, with nine replications. The part of the plot used for data collection consisted of one planted row with 12 coffee plants. The average and accumulated productivities of coffe plants were evaluated over five harvests (2017-2021). Afforestation of the coffee field with Brazilian firetree plants reduces the mean yield and cumulative yield of C. canephora ‘Conilon’ in the first five commercial crop years. Brazil nut and teak planted at densities of up to 222 trees per hectare did not lead to a reduction in the mean and cumulative yield of coffee plants.

Optimizing Basil (Ocimum basilicum L.) Planting Densities and Row Arrangements in Tomato-Basil Intercropping System

A field experiment was conducted at Wondo Genet Agricultural Research Center under irrigated conditions during 2018, to evaluate the performance of tomato yield and yield components under an intercropping system with different basil planting densities and row arrangements. it was arranged in a 2 × 4 factorial arrangement in randomized complete block design with three replications each consisting of ten treatments: two basil row arrangements (one tomato row alternating with one basil row (1T:1B) or with two basil rows (1T:2B)) and four basil population densities (66666, 50000, 33333 and 16666 plants ha -1). Results of the study indicated that intercropping system significantly (p<0.05) affected the yield and yield components of tomato. Inter-cropped tomato with basil had the highest yield (36657.8 kg ha-1) as compared to sole cropped tomato (31004.3kg ha-1) and inter-cropping with basil increased its yield by 15.42%. Therefore, basil with a density of 33,333 plants ha-1and intercropped with tomato with 1T:1B row arrangement could be recommended for the wondo genet and similar agroecology area. However, the effect of tomato-basil intercropping on the incidence and severity of major tomato insects and diseases needs further study.

Farmers’ adoption of multiple climate-smart agricultural technologies in Ghana: determinants and impacts on maize yields and net farm income

This study investigates the factors affecting maize farmers’ decisions to adopt climate-smart agricultural (CSA) technologies and estimates the impacts of CSA technology adoption on maize yields and net farm income. Unlike most previous studies that analyze a single technology, we consider different combinations of three CSA technologies (zero tillage, row planting, and drought-resistant seed). A multinomial endogenous switching regression model addresses selection bias issues arising from observed and unobserved factors and analyses data collected from 3197 smallholder farmers in three Ghana regions (Brong-Ahafo, Northern, and Ashanti). The findings show that smallholder farmers’ decisions to adopt multiple CSA technologies are influenced by farmer-based organization membership, education, resource constraints such as lack of land, access to markets, and production shocks such as perceived pest and disease stress and drought. We also find that adopting all three CSA technologies together has the largest impact on maize yields, while adopting row planting and zero tillage as a combination has the largest impact on net farm income. Governments should collaborate with farmer-based groups and extension officers to improve farmers’ awareness and understanding of the benefits associated with CSA technologies and help them adopt multiple technologies that generate higher benefits.

Effects of maize plant type and row spacing on the field microclimate and yield of intercropping ginger

ABSTRACT To explore field microclimate changes under maize/ginger intercropping and select a reasonable field configuration, this study used the major ginger variety ‘Zhugen’ from Southwest China as the experimental material. Two maize plant types; tall (Zhenghong 311) and short (Zhenghong 6), with 2, 3, and 4 m row spacings, shading treatment (ST), and a control (pure) without shading (CK) were used for the study. The effects of the maize plant type and row spacing on soil temperature, humidity, canopy temperature, light transmittance, plant growth, and intercropped ginger yield were investigated. Soil moisture, ginger canopy humidity, and shading rate in the maize/ginger intercropping mode were significantly higher than those in the non-shading treatment. Conversely, the soil and ginger canopy temperatures of the maize/ginger intercropping mode were significantly lower than those of the non-shading treatment. As a result, plant height, stem diameter, branch number, and ginger yield were significantly higher under the intercropping mode than the non-shading treatment. Although maize/ginger intercropping improves ginger growth and yield, these parameters are dependent on maize plant type and row spacing. The ginger yield was significantly higher when intercropped with the tall maize ZH 311 than with short maize ZH 6. The yield improved with decreasing row spacing and was the highest at a row spacing of 2 m. At the aforementioned field configurations, the soil and canopy humidity were the highest whereas the soil and canopy temperatures were the lowest, thereby giving best results on parameters like plant height, stem diameter, branch number, and yield.

Reduction in Atmospheric Particulate Matter by Green Hedges in a Wind Tunnel

Urban vegetation plays a crucial role in reducing atmospheric particulate matter (PM), modifying microclimates, and improving air quality. This study investigates the impact of a laurel hedge (Laurus nobilis L.) on airborne PM, specifically total suspended particulate (TSP) and respirable particles (PM4) generated by a Diesel tractor engine. Conducted in a wind tunnel of approximately 20 m, the research provides insights into dust deposition under near-real-world conditions, marking, to our knowledge, the first exploration in a wind tunnel of this scale. Potted laurel plants, standing around 2.5 m tall, were arranged to create barriers of three different densities, and air dust concentrations were detected at 1, 4, 9, and 14 m from the plants. The study aimed both to develop an experimental system and to assess the laurel hedge’s ability to reduce atmospheric PM. Results show an overall reduction in air PM concentrations (up to 39%) due to the presence of the hedge. The highest value of dust reduction on respirable particles was caused by the thickest hedge (three rows of plants). However, the data exhibit varying correlations with hedge density. This study provides empirical findings regarding the interaction between dust and vegetation, offering insights for designing effective hedge combinations in terms of size and porosity to mitigate airborne particulate matter.

Extraction of Tobacco Planting Information Based on UAV High-Resolution Remote Sensing Images

Tobacco is a critical cash crop in China, so its growing status has received more and more attention. How to acquire accurate plant area, row spacing, and plant spacing at the same time have been key points for its grow status monitoring and yield prediction. However, accurately detecting small and densely arranged tobacco plants during the rosette stage poses a significant challenge. In Sichuan Province, the contours of scattered tobacco fields with different shapes are not well-extracted. Additionally, there is a lack of simultaneous methods for extracting crucial tobacco planting information, including area, row spacing, and plant spacing. In view of the above scientific problems, we proposed a method to extract the planting information of tobacco at the rosette stage with Unmanned Aerial Vehicle (UAV) remote sensing images. A detection model, YOLOv8s-EFF, was constructed for the small and weak tobacco in the rosette stage. We proposed an extraction algorithm for tobacco field area based on extended contours for different-shaped fields. Meanwhile, a planting distance extraction algorithm based on tobacco coordinates was presented. Further, four experimental areas were selected in Sichuan Province, and image processing and sample label production were carried out. Four isolated tobacco fields with different shapes in four experimental areas were used to preliminarily verify the effectiveness of the model and algorithm proposed. The results show that the precision ranges of tobacco field area, row spacing, and plant spacing were 96.51~99.04%, 90.08~99.74%, and 94.69~99.15%, respectively. And another two experimental areas, Jiange County, Guangyuan, and Dazhai County, Gulin County, and Luzhou, were selected to evaluate the accuracy of the method proposed in the research in practical application. The results indicate that the average accuracy of tobacco field area, row spacing, and plant spacing extracted by this method reached 97.99%, 97.98%, and 98.31%, respectively, which proved the extraction method of plant information is valuable.

The Throughfall, Stemflow, and Canopy Interception Loss in Corn and Soybean Fields in Northeast China

Information about throughfall, stemflow, and canopy interception loss is essential for the water use efficiency of crops and the dynamic processes of water erosion. A two-year field experiment was conducted under natural rainfall conditions to observe the characteristics and factors that affect throughfall, stemflow, and canopy interception loss in corn (Zea mays L.) and soybean (Glycine max L.) fields in northeast China from 2019 to 2020. Nine measurement sites (A, B, C, D, E, F, G, H, and I) were distributed horizontally between two planting rows under the crop canopy. The mean value of the throughfall volume (TF) in measurement locations B, C, and G under the corn canopy and measurement locations B and C could represent the mean level of TF of corn and soybean fields, respectively. The volume of TF, stemflow (SF), and canopy interception loss (CI) of two growing seasons from 2019 to 2020 accounted for approximately 58.5%, 30.1%, and 11.4% of the gross rainfall (GR) of two growing seasons in corn fields, and 78.0%, 7.5%, and 14.5% of the GR in the soybean field, respectively. The TF and TFR of each rainfall event in the corn and soybean fields could be predicted by linear regression models with a normalized root mean square error (NRMSE) lower than 25.0%. These results and prediction models will be used in water management and soil erosion control in northeast China.

Long-Term Effects of Plastic Mulch in a Sandy Loam Soil Used to Cultivate Blueberry in Southern Portugal

Numerous plastic products are used in agriculture, including containers, packaging, tunnels, drip irrigation tubing, and mulches. Large amounts of plastics are used as mulches on the soil surface for vegetable and fruit production (tomato, cucumber, watermelon, strawberry, and vine) to reduce weed competition, increase water and fertilizer use efficiency, and enhance crop yield. Portugal uses around 4500 t/year of polyethylene to cover approximately 23,000 ha of agricultural land, and only a small amount is recovered for recycling or secondary uses because of issues of contamination with the soil, vegetation, pesticides, and fertilizers. Cleaning and decontaminating polyethylene mulch are costly, and commercial technology is often not accessible or economical. Most plastic mulch is composed of polyethylene that degrades slowly and produces a large quantity of residues in the soil, with a negative impact on the environment. In the present study, the effects of long-term cultivation of blueberry using green 100% high-density polyethylene mulch in the south Portugal were evaluated for soil chemical and biological changes. High-density green plastic mulch did not contaminate the topsoil with di(2-ethylhexyl) phthalate, and heavy metals, buttotal nitrogen, organic carbon concentrations, electric conductivity, and microbial activity were significantly reduced in the planting row compared with the bare soil without mulching. Furthermore, the presence of plastic mulch did not negatively affect the presence of nematodes, and the number of Rhabditida (bacterial feeders) increased in the planting and covered row.

RSM and ANN Modeling of Camelina (Camelina sativa L. Crantz) Seed Yield as Affected by Nitrogen, Sulfur, Cow Manure, and Row Spacing

Camelina [Camelina sativa (L.) Crantz] is an annual versatile oilseed crop of the Brassicaceae family, with an increasingly cultivated area. Predicting camelina seed yield response to fertilization and planting density is of great importance in understanding production potential and management planning. Therefore, the current study aimed to estimate the seed yield of camelina by response surface methodology (RSM) and artificial neural network (ANN) as affected by different levels of planting row spacing and nitrogen (N), sulfur (S), and cow manure (CM) fertilization. The experiment was conducted in two growing years of 2019–2020 and 2020–2021, based on a central composite design with four factors including row spacing (15–35 cm), N (0–200 kg ha−1), S (0–100 kg ha−1), and CM (0–40 t ha−1). The RSM models for seed yield versus fertilization and row spacing factors in both years were statistically significant and had an acceptable predictive ability. Camelina seed yield decreased with increasing row spacing but showed a positive response to increasing the amount of N, S, and CM fertilizers. Comparing the performance of the models showed that, although the RSM models were significant and had the necessary efficiency in predicting camelina seed yield, the ANN models were more accurate. The performance criteria of coefficient of determination (R2), root mean square error (RMSE), standard error of prediction (SEP), mean absolute error (MAE), and Akaike information criterion (AICc) averaged over the two years for the RSM model were 0.924, 51.60, 5.51, 41.14, and 394.05, respectively, and for the ANN model were 0.968, 32.62, 3.54, 19.55, and 351.33, respectively. Based on the results, the ANN modeling can be used in predicting camelina seed yield in field conditions with more confidence than the RSM technique.

АЛГОРИТМ РАБОТЫ АВТОНОМНОГО РОБОТИЗИРОВАННОГО КОМПЛЕКСА МОНИТОРИНГА СОРНОЙ РАСТИТЕЛЬНОСТИ

An autonomous robotic complex designed for monitoring weed vegetation requires an efficient algorithm for proper movement in the work area. (Research purpose) The research purpose is creating and testing an algorithm using a virtual robot model in Gazebo simulator and field tests using a prototype. (Materials and methods) It was noted that the developed algorithm includes a method of classification and decision-making. Indicated that at the first stage the robot is being prepared, including checking the systems and sensors. Then parallel programs are launched, including receiving and processing the video stream from the camera, detecting weeds and correcting the path traveled. (Results and discussion) It was determined that the camera continuously sends images of plants under the robot for processing. The second program detects weeds, and according to the data obtained, the robot’s path is corrected and the working part is positioned. It was established that in case of detection of weed vegetation, its coordinates are determined, which is necessary for localization in the work area and correction of the path. Then the path of the robot’s movement between the rows of plants is determined, and the error of deviation from the set course is transferred to the next step of the algorithm. (Conclusions) As a result of the experiments conducted in simulation and field tests, the algorithm showed the effectiveness and correct operation of the robot in real time. The created algorithm does not require significant computational resources, and its successful testing in various conditions has confirmed its applicability for monitoring weeds.

Connecting the Fragmented Forests by Opportunity of Vertical Dual Land Use-II (Plantation of Dwarf Species, Preferably Medicinal Plants in RoW of Transmission Lines as Compliance of the Existing Mandatory Condition under FC Act, 1980)

Connecting the Fragmented Forests by Opportunity of Vertical Dual Land Use-II (Plantation of Dwarf Species, Preferably Medicinal Plants in RoW of Transmission Lines as Compliance of the Existing Mandatory Condition under FC Act, 1980)

Evaluation of forty‑five rice (Oryza species) accessions for resistance to rice blast (Magnaporthe oryzae) disease under natural conditions

Abstract The experiments were conducted to investigate the resistance levels among forty‑five lowland rice accessions at the Teaching and Research Farm, Federal College of Agriculture, Ishiagu (Latitude 5°56″N and Longitude 7°41″E) Ebonyi State, Nigeria. Forty‑five rice accessions were screened for their resistance to the blast disease in row planting during the 2017 and 2019 cropping seasons using Randomised Complete Block Design (RCBD) and were replicated thrice. The data on disease intensity and agronomic performance were subjected to Analysis of Variance and the significant means were separated with the Tukey HSD test at p < 0.05. Assessment of blast disease showed that the incidence, severity, and resistance levels varied significantly among rice tested. Accession NG / SA / JAN / 023 had the highest disease incidence (59.06 %) while accessions NG / SA / DEC / 07 / 0300, TOG 5453, TOG 6804, FARO‑22 and FARO‑57 had no blast symptoms for the two cropping seasons. The disease severity ranged from 0.00 to 3.43 for the two cropping seasons. Five accessions (NG / SA / DEC / 07 / 0300, TOG‑5453, TOG‑6804, FARO‑22, and FARO‑57) were highly resistant, 10 were resistant, 14 moderately resistant, and 16 were moderately susceptible to the disease. In the 2017 cropping season, the result of the grain yield showed that accession Local Foreign and FARO 26 had the value of 46.77 g apiece while NG / SA / DEC / 07 / 0278 had the least (11.00 g). However, in the 2019 cropping season, the results of the grain yield showed that accession Local Foreign produced the highest yield (56.00 g), FARO 26 had 40.31 g grain yield while NG / SA / DEC / 07 / 0285 (22.0 g) had the lowest grain yield. The study concluded that using the blast‑resistant cultivars is the best option in managing blast disease, and the five highly resistant accessions could be planted out in other agroecological zones for further studies on managing rice blast disease in the field.

Effect of in-row spacing on weed suppression and yield of ‘Covington’ and ‘Monaco’ sweetpotato

Abstract Organic sweetpotato growers have limited effective weed management options, and most rely on in-season between-row cultivation and hand weeding, which are time consuming, are costly, and deteriorate soil quality. Studies were conducted at the Samuel G. Meigs Horticulture Research Farm, Lafayette, IN, and at the Southwest Purdue Agricultural Center, Vincennes, IN, in 2022 and 2023 to determine the effects of in-row plant spacing and cultivar selection on weed suppression and organic sweetpotato yield. The experiment was a split-split plot design, with in-row spacings of 20, 30, and 40 cm as the main plot factor, weeding frequency (critical weed-free period and weed-free) as the subplot factor, and sweetpotato cultivar (‘Covington’ and ‘Monaco’) as the sub-subplot factor. However, in 2022, we evaluated only in-row spacing and weeding frequency because of the poor establishment of ‘Monaco’. In 2023, sweetpotato canopy at 5 wk after transplanting (WAP) decreased as in-row spacing increased from 20 to 40 cm, and sweetpotato canopy cover of ‘Monaco’ (62%) was greater than that of ‘Covington’ (44%). In-row spacing did not affect weed density at 4, 5, and 6 WAP. As in-row spacing increased from 20 to 40 cm, total sweetpotato yield pooled across both locations in 2023 decreased from 30,223 to 21,209 kg ha−1 for ‘Covington’ and from 24,370 to 20,848 kg ha−1 for ‘Monaco’; however, jumbo yield increased for both cultivars. Findings from this study suggest that an in-row spacing of 20 cm may provide greater yield than the standard spacing of 30 cm for both ‘Monaco’ and ‘Covington’.

Estimation of efficiency of ultrasonic extraction using deep eutectic solvents for extraction of biologically active compounds from plant raw materials

Deep eutectic solvents are novel media for the extraction of biologically active substances from plant row material. They are often used for ultrasonic extraction. However, due to the high viscosity of the deep eutectic solvents, the question of the sufficiency of ultrasonic exposure for effective diffusion of the target components into the solution remains open. The purpose of this study was to compare the effectiveness of ultrasonic extraction with and without additional mixing. The antioxidant activity of Chamaenerion angustifolium (L.) Scop. extracts obtained by these two methods in the medium of two deep eutectic solvents were compared. It has been shown that additional mixing increases the extraction efficiency concerning antioxidant activity by 20-80%. The obtained data can be used for the development of modern technologies for the isolation of biologically active compounds from plant material using deep eutectic solvents.

Growth, Yield and Economic Advantage of Onion (Allium cepa L.) Varieties in Response to NPSB Fertilizer and Planting Pattern

Haphazard and low soil fertility, low yielding verities and poor agronomic practices are among the major factors constraining onion production in the central rift valley of Ethiopia. Therefore, a field experiment was conducted in East Showa Zone of Adami Tulu Jido Combolcha district in central rift valley areas at ziway from October 2021 to April 2022 to identify appropriate rate of NPSB fertilizer and planting pattern of onion varieties. The experiment was laid out in split plot design of factorial arrangement in three replications. The main effect of NPSB blended fertilizer rates and varieties (red coach and red king) significantly (p<0.01) influenced plant height, leaf length, leaf diameter, leaf number and fresh leaf weight, shoot dry matter per plant, and harvest index. Total dry biomass, bulb diameter, neck diameter, average fresh bulb weight, bulb dry matter, marketable bulb yield, and total bulb yield were significantly (p<0.01) influenced only by the main effect of NPSB blended fertilizer rates. In addition, unmarketable bulb yield was statistically significantly affected (p≥0.05) by the blended fertilizer rates and planting pattern. Moreover, days to 90% maturity of onion was affected by the main factor of NPSB fertilizer rate, variety and planting pattern. The non-fertilized plants in the control treatment were inferior in all parameters except unmarketable bulb yield and harvest index. Significantly higher marketable bulb yield (41 t ha-1) and total bulb yield (41.33 t ha-1) was recorded from 300 kg ha-1 NPSB blended fertilizer rate applied. Double row planting method and hybrid red coach onion variety had also gave higher growth and yields. The study revealed that the highest net benefit of Birr, 878,894 with lest cost of Birr 148,006 by the combinations of 150 kg blended NPSB ha-1 with double row planting method (40cm*20cm*7cm) and red coach variety which can be recommendable for higher marketable bulb yield and economic return of hybrid onion for small scale farmers in the study area. Also, for resource full producers (investors), highest net benefit of Birr 1,205,372 with higher cost (159,628 Birr) by application of 300 kg NPSB ha-1 is recommended as a second option. However, the research should be replicated both in season and areas to more verify the recommendations.

Economic Evaluation of Twin Row Maize Planter: A Cost-Benefit Analysis

The adoption of innovative agricultural technologies plays a crucial role improving farm productivity and overall economic outcomes. This research article aims to evaluate the economic viability of twin row maize planters compared to conventional single-row planters. The study assesses the economic benefits, costs and profitability associated with the adoption of twin row planting in maize cultivation. The analysis incorporates factors such as yields improvement, input savings, labor requirements, and machinery costs, providing valuable insights for farmers. Annual utility of mini tractor and the machine was considered as 1000 and 200 hrs respectively. Field efficiency of developed twin-row planter at 1.5 to 2.5 kmh-1 speed of operation was 76.9 to 87% respectively. The payback period calculated on year basis for planter was 1.78 years. Cost of operation by twin row maize planter can save up to 20% as compared to the traditional methods.

Developing Biocontrol Strategies for the Management of Set rot Disease of Sugarcane under Wider Row Planting

Sugarcane (Saccharum officinarum L.) is one of the economically valuable agricultural crops grown worldwide in tropical and subtropical areas mainly for their sugar source. Among the 110 sugarcane cultivated countries, India and Brazil contribute half of global production [1]. During the period of last five decades the production, productivity and sugarcane recovery has also shown remarkable resilience in productivity growth rate. One of the reasons for the low productivity and recovery is increasing incidence of insect pests and diseases. An ecologically friendly alternative to these problems is biological control using rhizobacteria and their metabolic products [2]. In order to develop a technology capsule Surveys and surveillance were conducted in sugarcane fields both in plant and ratoon crops distributed in Orthanadu and Vallam block in New Cauvery delta area of Thanjavur dictrict during three consecutive years 2019- 22 with an objective to assess the incidence of sett rot, red rot and smut in New Cauvery delta area of Thanjavur dictrict. Fortnightly fixed plot observation was taken. The Maximium and minimum temperature, RH and quantity of rain and rainy days also recorded daily and consolidated on monthly basis and weather parameters were correlated with the incidence of disease. The results revealed that the maximum incidence sett rot negatively correlated with temperature. Similarly the number of rainy days and rainfall is positively correlated (r = 0.7523) with incidence of sett rot. For managing sett rot disease of sugarcane through biological approach, studies were conducted on biocontrol agents viz., Trichoderma asperellum (TNAU), Bacillus subtilis (TNAU), Chaetomium globosum (Cg6) with fungicide check propiconozole 0.1%. Among the treatment, highest millable cane (91,080/ha) and yield (91.39 tonnes / ha) and sugar yield ( 10.63 tonnes/ha) were recorded in M1- (Single bud treated with Trichoderma asperellum (TNAU)@ 4 g l-1 + soil application @ 2.5 kg ha-1) followed by M2- (Single bud treated with Bacillus subtilis (TNAU)@ 10 g l-1 + soil application @ 2.5 kg ha-1) in which, the cane yield of 88.54 tonnes/ha and sugar yield of 10.68 tonnes/ha were recorded. This study provides a technology capsule for the management of important disease of sugarcane.

Determination of Effects the Different Holes Position in the Vacuum Discs of Pneumatic Precision Vegetable Planters on Emergence and Uniform Plant Distribution in Black Carrot Production

The objective of this study was to determine the seed releasing characteristics of seed metering discs used in the precision seeding of black carrot seeds. High precision vegetable seeder was tested in the field conditions using black carrot seeds in Kuzukuyu village of Ereğli-Konya in 2018. Three different seed metering discs that have holes in three different circle positions were used in the experiments. These applications referred to seeding techniques, ST1, ST2 and ST3. The seed metering discs with three trajectories, each diameter was 210, 185, and 155 mm respectively. Each trajectory on vacuum plate using in ST1 had equal number of holes (96 holes), while P1 and P2 hole positions had same number of holes in ST2 ve ST3, however, 25% and 50% decrease in the number of holes in the P3 (bottom hole position), respectively. The downforce on the press wheel was kept constant throughout all trials. In these three different seeding techniques, the planting performance of the machine under field conditions was evaluated and the coefficient of variation values expressing the seed distribution uniformity, mean of the emergence rates were determined. According to the results, the mean of emergence rates and coefficient variation values were determined as %59.86 ve %76.84, %68.91 ve %75.31, %66.26 ve %72.48for ST1, ST2 ve ST3, respectively. Given hole positions (planting rows), emergence rates and CV values were obtained %59.71 ve %81.94 for P1, %62.69 ve %74.49 for P2 and %72.60 ve %68.20 for P3.

Efektifitas Tanaman Refugia Kacang-Kacangan Menangkal Intensitas Serangan Hama Ulat Grayak (spodoptera exigua Hubner.) Pada Bawang Merah

This experimental research aims to obtain the type of legume refugia plant that is most effective in preventing invasion, colonization and intensity of attack by the Spodoptera exigua Hubner pest on shallot. The experiment was designed with a randomized block design consisting of six treatments of various refugia plants, namely shallot plants without refugia treatment (Ro), shallot plants with refugia treatment peanuts (R1), soybeans (R2), green beans (R3), red beans (R4) and cowpeas (R5), which are planted in two rows on the side of the bund at a distance of 10 cm from the outermost row of shallot plants. Observation parameters were egg population, larvae, intensity of S. exigua pest attack and weight of fresh shallot bulbs. The variety of refugia plants from the legume group influences invasion, colonization and the intensity of Spodoptera exigua Hubner pest attacks. on red onions. Peanut and cowpea refugia plants planted in two rows on the sides of the shallot mounds, are very effective in preventing invasion, colonization and the intensity of Spodoptera exigua Hubner pest attacks, so that the shallot plants experience very light disturbance with an attack intensity of 2,522% – 4,432 %, which is in the very low category. As a result, the yield of fresh shallot tubers obtained was significantly higher compared to shallot plants without refugia plants and with refugia plants of soybeans, green beans and red beans. Soybean, green bean and red bean refugia plants are not effective in preventing Spodoptera exigua Hubner pest attacks on shallots because the plants experience attack intensity from the age of 49 HST – 63 HST of 21.86% - 23.34% with the attack intensity being in the medium category.