Standard Contour Research Articles

An algorithm for building contour inference fitting based on multiple contour point classification processes

Extracting buildings from True Digital Ortho Maps often encounters occlusions and misidentifications, making it challenging to obtain complete, regular, and accurate building contours. To address this issue, we developed a building recognition process based on the Segment Anything Model, and proposed a novel regularization algorithm for building contour inference and fitting, which quantifies the confidence levels of contour points to accurately fit building contours from data containing substantial noise, and reformulates the fitting problem as progressive node classification tasks consisting of contour simplification, iterative regularization, and rationality assessment. In experimental evaluations, the proposed contour fitting algorithm achieved 97.99 % Intersection over Union (IoU), 95.39 % consistency with the standard contour edge count, and 88.06 % of cases with Hausdorff distances less than or equal to 15 pixels (30 cm), significantly outperforming comparative methods. Notably, it was the only contour regularization algorithm that improved IoU (1.03 %) compared to the original contours. The experimental results demonstrate that the proposed algorithm effectively suppresses noise and infers incomplete building contours, producing accurate and regular contours comparable to manual delineation. It is particularly suitable for buildings with near-orthogonal structures, exhibiting significant practical applicability and generalization potential.

Evaluating effects of selected water conservation techniques and manure on sorghum yields and rainwater use efficiency in dry region of Zimbabwe

Sorghum production in semi-arid areas of Zimbabwe is constrained by low and erratic rainfall, low fertility and soil moisture stress. Sorghum grain yields ranges from 0.2 to 0.4 t ha−1 in sandy-to-sandy loam soils respectively. The objective of the study was to assess cattle manure and rainwater harvesting techniques in improving sorghum grain yield in a semi-arid region of Zimbabwe. The experiment used a randomised complete block design with rainwater harvesting technique as a main treatment factor at three levels. Sub-plot factor was cattle manure at five levels (0, 2.5, 5, 10 and 15 t ha−1) and two sorghum varieties (Macia and SV1) as sub-sub plot factor. Sorghum grain yields were improved significantly (p < 0.05) for both varieties using tied contours. Increasing application rates of cattle manure, showed significant increase (p < 0.05) in sorghum grain yield over the control (0 t ha−1). Tied contour had higher grain yield (1.15 t ha−1) with the use of Macia variety. Stover yield was highly influenced by rainwater harvesting method of tied contour (p < 0.05) compared with infiltration pit and standard contour. Increase in application levels of cattle manure show significant (p < 0.05) increase in stover yields. Tied contour had the highest (3.11 kg ha−1 mm−1) rainwater use efficiency which show significant differences (p < 0.05) from infiltration pits and standard contour. Interaction of tied contour and different rates of cattle manure showed significant increments in rainwater use efficiency with increases in manure application rates. Tied contours, 15 t ha−1 cattle manure and Macia variety are potential strategy to achieve climate smart agriculture and improve food security in semi-arid areas. Sorghum production in marginalised areas can be productive with adoption of tested techniques.

The effects of contour-based rainwater harvesting and integrated nutrient management on maize yields in semi-arid regions of Zimbabwe

In the smallholder farming areas located in semi-arid regions of Zimbabwe, low and unreliable rainfall distribution and poor soil fertility are the major factors limiting crop production. The negative effects of these biophysical factors have been worsened by climate change. However, the major challenges have been the lack of sustainable, low-cost water and nutrient management technologies for these semi-arid regions. The objectives of this study were to evaluate the effects of contour-based rainwater harvesting (RWH) namely tied contours (TC), infiltration pits (IP) which were compared with the standard contour (STDC), and intergrated nutrient management (INM) where cattle manure was used as basal fertiliser and Ammonium Nitrate (AN) as top dressing, on maize yields. Results showed that fields with RWH had higher yields compared to STDC. Average maize yields were 2210 and 1792 kg ha−1 for TC and IP which were 88% and 52% above STDC (1176 kg ha−1) respectively. Increasing nitrogen (N) levels resulted in a further increase in maize yields. Return on investment was negative during drier years and was significantly higher in RWH systems compared with STDC during wet seasons. Farmers need to reduce mineral fertiliser application during dry seasons since little rainwater is captured. We conclude that contour based RWH and INM can be used as sustainable low cost methods of crop production. Higher fertiliser application rates when rainfall is limiting, do not result in increased return on investiment.

Artificial Neural Networks for Long-Bone Fracture Detection Based on X-Ray Image Contour Features

Abstract: Two contour-based fracture detection strategies are presented in the ensuing research. The programs are designed to help medical practitioners identify human long bone fractures from X-ray pictures. The line-based fracture detection systems suggested in [1] served as the foundation for the creation of the contour-based fracture. Convolutional Neural Networks (CNN) are widely used in current Computer Aided Diagnosis (CAD) systems to classify broken X-ray images. Even while the current CAD systems achieve excellent accuracy, doing so comes at a cost: a large volume of training data. By using identified contours in X-ray pictures, the suggested techniques aim to achieve high classification accuracy with little training data. Two methods exist for contour-based fracture detection. The first is the enhanced CHFB scheme, while the second is the Standard Contour Histogram Feature-Based (CHFB). The modified CHFB scheme differs from the other one in that it removes the detected flesh contours surrounding the leg region.

Communicating Uncertainty and Risk in Air Quality Maps.

Environmental sensors provide crucial data for understanding our surroundings. For example, air quality maps based on sensor readings help users make decisions to mitigate the effects of pollution on their health. Standard maps show readings from individual sensors or colored contours indicating estimated pollution levels. However, showing a single estimate may conceal uncertainty and lead to underestimation of risk, while showing sensor data yields varied interpretations. We present several visualizations of uncertainty in air quality maps, including a frequency-framing "dotmap" and small multiples, and we compare them with standard contour and sensor-based maps. In a user study, we find that including uncertainty in maps has a significant effect on how much users would choose to reduce physical activity, and that people make more cautious decisions when using uncertainty-aware maps. Additionally, we analyze think-aloud transcriptions from the experiment to understand more about how the representation of uncertainty influences people's decision-making. Our results suggest ways to design maps of sensor data that can encourage certain types of reasoning, yield more consistent responses, and convey risk better than standard maps.

MO-0714 Statistical comparison between GTV and gold standard contour on AI-based registered histopathology

MO-0714 Statistical comparison between GTV and gold standard contour on AI-based registered histopathology

Enhancing Sorghum bicolor (L.) grain yield with the use of field edge rainwater harvesting and NPK fertiliser in a dry region of Zimbabwe

AbstractBackgroundFarmers in marginalised areas across Africa are mainly resource poor and have limited capacity to procure enough inorganic fertilisers. This contributed immensely towards declining crop productivity causing food insecurity. Soil moisture stress is another key factor which has led to a decline in crop yields across semi‐arid areas. This experiment determines the effects of field edge rainwater harvesting and NPK fertiliser microdosing on sorghum grain yields and agronomic nutrient use efficiency of two sorghum varieties (Macia and SV1). Rainwater harvesting techniques was the main plot factor with three levels (tied contour, infiltration pits and standard contour), sorghum variety was used as subplot factor with two levels (Macia and SV1) and NPK fertiliser as sub‐sub plot factor with five levels (0, 25, 50, 100 and 150 kg ha−1) with all treatments replicated three times. A randomised complete block design arranged in split‐plot was used.ResultsPhosphorous was significantly increased from 3.32 to 3.52 mg kg−1 with no significant (p &gt; 0.05) increase in total nitrogen and soil organic carbon. Sorghum grain yields were statistically (p &lt; 0.05) influenced by main treatment factors. Tied contour had considerably higher grain yield (861 kg ha−1) than infiltration pits and standard contours. Highest grain yield of 909 kg ha−1 was observed from plots applied 150 kg ha−1 NPK fertiliser. Macia variety performed significantly (p &lt; 0.05) higher than SV1. Grain yields show significant (p &lt; 0.05) increase with increasing fertiliser levels. Interaction of tied contour + Macia+ 150 kg ha−1 NPK fertiliser had significant grain yields (1150 kg ha−1) compared to other treatments. Treatments applied NPK fertiliser show significant differences (p &lt; 0.05) than unfertilised plots. Agronomic nutrient use efficiencies were significantly higher (p &lt; 0.05) from all treatments applied 25 kg ha−1 NPK fertiliser. Sorghum variety Macia had better nutrient use efficiency than SV1 in 2017/18 and 2018/19 seasons except during 2019/20 where results show insignificant differences.ConclusionIt can be concluded that farmers adopt the use of tied contour and Macia variety using 150 kg ha−1 to achieved higher yields. Combining rainwater harvesting method of tied contour and mineral fertiliser can increase sorghum grain yields in dry regions.

Evaluation of different rainwater harvesting techniques for improved maize productivity in semi‐arid regions of Zimbabwe with sandy soils

AbstractBackgroundMaize production in semi‐arid areas has been hindered by moisture stress and poor soil fertility. Long frequent droughts and shortening of growing seasons have been causing yield reduction. Limited knowledge of soil water management by farmers is another key contributor to poor maize yields in the smallholder sector. Therefore, the objective of the study was to investigate the effects of contour‐based and field‐based water harvesting technologies on maize grain yield and rainwater use efficiency under rain‐fed conditions on three farms (Jera, Kudzeeta and Manjengwa) with sandy soils in the Marange smallholder farming area of Zimbabwe. The experiment was laid out as a split plot in a randomised complete block design with three replications at each site. Contour‐based rainwater harvesting structures were the main treatments comprising tied contour (TC), standard contour (STDC) and infiltration pits (IP). Field‐based rainwater harvesting structures were the subplot treatments comprising tied ridges (TR), pot holing (PH) and the flat system (FLAT).ResultsResults showed that the contour‐based water harvesting structures significantly influenced (p &lt; 0.05) maize grain yields. TCs had the highest maize grain yields compared with infiltration pits and STDCs over two cropping seasons. Maize yields on field‐based TR were significantly higher (p &lt; 0.05) than on the FLAT but were not different (p &gt; 0.05) with what was obtained on PH. The combination of TC and TR water harvesting technologies resulted in significantly higher maize yields (p &lt; 0.05) than other combinations. TR and STDC also gave higher maize grain yield at Jera farm which was significantly different from other two farms. Rainwater use efficiency followed the same trend as maize grain yields, with TC having higher values but not significantly different (p &gt; 0.05) from STDC.ConclusionIt can be concluded that farmers in semi‐arid areas adopt a combination of TC with either TR or PH to improve rainwater use efficiency and maize yields.

RELIABILITY ANALYSIS OF PRECISION GEARS WITH MODIFIED INITIAL TOOTH CONTOUR

The article presents the results of a theoretical study that was conducted as part of the search for solutions to the problems of calculating the operational reliability of gears of a new generation that have a significant deviation in the geometry of the profile of the teeth and the entire engagement from the standard initial contour. A method of plotting the wear of the working surfaces of gear teeth has been developed. The essence of the method is that the equation of the worn surface can be obtained by calculating the full variational derivative of the functional of the energy action of wear. Since wear reduces accuracy, the method is used to calculate the probability of failure-free operation of precision gears by the express method. The proposed article is one of the first works on the calculation of the operational reliability of precision gears with teeth profiled by the involute epitrochoid.

Improved accuracy of auto-segmentation of organs at risk in radiotherapy planning for nasopharyngeal carcinoma based on fully convolutional neural network deep learning

ObjectiveWe examined a modified encoder-decoder architecture-based fully convolutional neural network, OrganNet, for simultaneous auto-segmentation of 24 organs at risk (OARs) in the head and neck, followed by validation tests and evaluation of clinical application. Materials and methodsComputed tomography (CT) images from 310 radiotherapy plans were used as the experimental data set, of which 260 and 50 were used as the training and test sets, respectively. An improved U-Net architecture was established by introducing a batch normalization layer, residual squeeze-and-excitation layer, and unique organ-specific loss function for deep learning training. The performance of the trained network model was evaluated by comparing the manual-delineation and the STAPLE contour of 10 physicians from different centers. ResultsOur model achieved good segmentation in all 24 OARs in nasopharyngeal cancer radiotherapy plan CT images, with an average Dice similarity coefficient of 83.75%. Specifically, the mean Dice coefficients in large-volume organs (brainstem, spinal cord, left/right parotid glands, left/right temporal lobes, and left/right mandibles) were 84.97% − 95.00%, and in small-volume organs (pituitary, lens, optic nerve, and optic chiasma) were 55.46% − 91.56%. respectively. Using the STAPLE contours as standard contour, the OrganNet achieved comparable or better DICE in organ segmentation then that of the manual-delineation as well. ConclusionThe established OrganNet enables simultaneous automatic segmentation of multiple targets on CT images of the head and neck radiotherapy plans, effectively improves the accuracy of U-Net based segmentation for OARs, especially for small-volume organs.

Effects of channel contour laser strategies on fatigue properties and residual stresses of laser powder bed printed maraging steel

Laser powder bed fusion is widely used for tooling applications, such as mould insert: conformal cooling channels are designed to decrease cycling time and homogenize the cooling rate. The Achilles’ heel of additive manufacturing mould is the cooling channels close to the surface which generate high stress concentration and are not machined; as a result, they create weaknesses in the part and are likely to reduce the lifespan of the mould. It is necessary to study the impact of such channels on properties (fatigue, residual stresses, microstructure) and determine optimized laser strategies to reduce porosity that may occur near a contour. Residual stresses were first estimated above an internal channel after different heat treatments, and fatigue specimens were printed with a 3-mm diameter channel on an EOS M270 printer using different strategies such as several contours with a concentric offset. The impact of these strategies on fatigue properties was analysed through microstructural observations. Here, it was found that a double contour with an offset improved the fatigue life of the part by more than 10 times compared to the standard single contour strategy.

Determination of the three-dimensional welding residual stress in a thick plate T-welded joint using the stepwise eigenstrain-contour method

The stepwise eigenstrain-contour method (SECM) for determining three-dimensional welding residual stress (WRS) was developed based on conventional eigenstrain-contour method. A thick plate T-welded joint specimen was manufactured and its three-dimensional WRS was measured via the SECM. The SECM was then verified by the superposition method, which obtains the three-dimensional WRS on the cut surface by superposing the measurement results of the hole-drilling method and the standard contour method. Finally, the three-dimensional eigenstrain field and WRS field in the thick plate T-welded joint specimen were comprehensively analyzed. The results show that the SECM greatly improves the reconstruction accuracy of the WRS components in non-principal directions of the welded joint, thus extending the standard contour method to three-dimensional WRS measurement. Overall, the three-dimensional WRS in the specimen presents self-equilibrated tension-compression distribution. The peak longitudinal, transverse and vertical WRSs on the whole mid-length section of the specimen are 382.3 MPa (0.92 σy), 152.7 MPa (0.37 σy) and 105.8 MPa (0.26 σy) respectively, which usually appear near the bottom of weld zone. The transverse and vertical WRSs are usually smaller than the longitudinal WRS, and the WRS in the flange is generally greater than that in the web.

Augmenting Leucaena leucocephala biomass with mineral fertiliser on rainwater use efficiency, agronomic efficiency and yields on sorghum (Sorghum bicolor [(L.) Moench]) under rainwater harvesting techniques in semi-arid region of Zimbabwe

Food security in semi-arid regions is threatened by declining soil fertility, soil moisture stress and long frequent droughts as a result of erratic rainfall. Therefore we assessed the effects of augmenting Leucaena leucocephala biomass (organic manure) with mineral fertiliser on rainwater use efficiency, agronomic efficiency, grain and stover yields for two sorghum varieties (Macia and SV1) under rainwater harvesting techniques. The experiment was laid in split-split plot arrangement with rainwater harvesting method as main plot factor, with Leucaena biomass + NPK fertiliser as subplot factor and sorghum variety as sub-sub plot factor over three cropping seasons. Data collected include rainwater use efficiency, agronomic efficiency, grain and stover yields. Results show that tied contours have significantly (p ≤ 0.05) higher grain and stover yields from all varieties and seasons. Irregardless of sorghum variety, tied contours had significant (p ≤ 0.05) sorghum grain and stover yield followed by infiltration pits and lastly standard contours. Grain and stover yields improved with increasing levels of Leucaena biomass + NPK fertiliser combination. Highest grain yields observed were 1.146 t ha−1 (Macia) and 1.1 t ha−1 (SV1) from tied contour +15 t ha−1 biomass +150 kg ha−1 NPK fertiliser treatments. Rainwater use efficiency was significantly (p ≤ 0.05) higher from tied contours compared to infiltration pits and standard contour. Rainwater use efficiency was statistically (p ≤ 0.05) influenced by increasing application levels of Leucaena biomass + NPK fertiliser in all seasons. Agronomic efficiencies were considerably (p ≤ 0.05) affected by rainwater harvesting, Leucaena biomass + NPK fertiliser and interaction of all factors. It can therefore be concluded that Leucaena biomass + NPK fertiliser, tied contours and infiltration pits improve sorghum yields. Augmenting 2.5 t ha−1 biomass with 25 kg ha−1 NPK fertiliser under tied contours and Macia have better agronomic efficiency.

Compatibility of Leucaena leucocephala biomass and cattle manure combination under rainwater harvesting on sorghum (Sorghum bicolor (L.) Moench) productivity in semi-arid region of Zimbabwe

Soil infertility is one of the constraints contributing to poor sorghum production in semi-arid areas across Africa. To increase sorghum production, there is need to address soil fertility issues. Therefore, the objective was to assess the effects of Leucaena/cattle manure combination on grain and stover yields, harvest index and net return of two sorghum varieties (Macia and SV1) under rainwater harvesting techniques. The field experiment was conducted as a randomized complete block design over three cropping seasons in a split-split plot arrangement. Results show significant (P < 0.05) increase in sorghum grain yield with increased applications of Leucaena/cattle manure combination. Macia variety had statistically greater (P < 0.05) grain yield than SV1 variety. Tied contour show considerably higher yield for both varieties across all seasons. Stover yield show significant differences (P < 0.05) as affected by Leucaena/cattle manure and rainwater harvesting techniques. Rainwater harvesting techniques significantly influence (P < 0.05) harvest index, with tied contour and infiltration pits having comparably higher harvest index than standard contour. Application of Leucaena/cattle manure combination show significant increases in harvest index with increased application rates. However, no significant effect was observed at 20 and 30 t ha−1 from SV1 variety across all seasons. Leucaena/cattle manure combination significantly influenced (P < 0.05) sorghum net return across all seasons except at 5 t ha−1 where no significant effect was observed. Macia variety had higher net return than SV1. To increase grain yield and net return, farmers can adopt Macia variety, tied contour and 10 t ha−1 Leucaena/cattle manure combination due to higher incremental yield per tonne.

Rainwater harvesting and Leucaena leucocephala biomass rates effects on soil moisture, water use efficiency and Sorghum bicolor [(L.) Moench] productivity in a semi-arid area in Zimbabwe.

Sorghum is one of the major staple crops in Sub Saharan Africa but its production is mainly limited by moisture stress, frequent droughts and soil infertility, especially in the smallholder farming systems. This raises the need to develop climate smart options to improve sorghum production. The objective was to assess the effects of rainwater harvesting and use of different Leucaena leucocephala biomass rates on soil moisture content, rainwater use efficiency, and stover and grain yields in two sorghum varieties (Macia and SV1). The experiment was laid as a randomized complete block design in split-split plot arrangement from 2017/2018 to 2019/2020 season. The results show that tied contour (TC) and infiltration pits (IPs) significantly (P < 0.05) increased soil moisture content than standard contour (SC). Soil moisture content increased gradually with the increase in soil depth (20-40 cm > 0-20 cm), with 2018/2019 season having the maximum soil moisture content. Soil moisture content also increased with the increase in application rates of Leucaena biomass. Grain and stover yields were significantly (P < 0.05) increased by all Leucaena biomass application rates with higher yield observed in 2018/2019 season. SC had significantly lower grain and stover yields at all Leucaena biomass application rates. TC and IPs had comparable rainwater use efficiency compared to SC. Rainwater use efficiency increased with application rates of Leucaena biomass across all seasons and varieties. TC and IPs are better adaptive mechanisms against drought spells in semi-arid areas and can be combined with 10 t ha-1 of Leucaena biomass due to better yield increments realized. © 2022 Society of Chemical Industry.

A knowledge augmented deep learning method for vision-based yarn contour detection

Contour detection extracts accurate object boundaries from natural images, which plays a critical role in the vision-based inspection. However, contour detection is still challenging in yarn quality inspection tasks, since the current methods pursue global high-precision contours while ignoring detecting the boundaries of interest from intertwined objects in complex local regions. This paper proposes a knowledge augmented contour detection method with deep learning to extract pure backbone boundaries from intertwined objects for more accurate yarn quality inspection. Firstly, according to the directional gradient distribution of yarn images in the visual system, a radial pixel difference convolution is improved to extract interested edge features. Secondly, considering the graphical characteristics of the yarn to be inspected, a mask layer of texture erosion is designed to further filter irrelevant details from extracted edge features. The comparative experiments during actual spinning processes demonstrate that the proposed method achieves a better ODS (optimal dataset scale, a standard contour detection evaluation measure) of 0.815, and reduces the quality inspection error from about 1.5% to tolerated 0.534%.

New optical soliton solutions for the variable coefficients nonlinear Schrödinger equation

This paper is devoted to seek new optical soliton solutions of nonlinear Schrödinger equation (NLSE) with time-dependent coefficients which describes the dispersion decreasing fiber. To achieve optical soliton solutions of NLSE, the basic idea of homogenous balance approach has been used to propose Bernoulli $$(G'/G)$$ -expansion method, where $$G =G(\zeta )$$ satisfies Bernoulli equation, which is easier to solve than previous studies. By applying some transformations and using this method, some periodic wave, bright and dark soliton solutions are successfully obtained. Moreover, 3D surfaces, standard deviation line plots and contour maps graphs of the obtained results under effect of different values of coefficients are illustrated to have acceptable image of dynamic structures and to find the relation between the parameters and wave behaviors.

Systematic Modeling and Analysis of On-Board Vehicle Integrated Novel Hybrid Renewable Energy System with Storage for Electric Vehicles

The automobile industry and technology are putting a great significance in improving vehicles to become more fuel economical, but with incremental costs relative to conventional vehicle technologies; these new vehicles are electric vehicles (EV), plug-in hybrid electric vehicles (PHEV), and hybrid electric vehicles (HEV). However, their significant capabilities to reduce petroleum consumption and achieve efficiency over their life cycles offer economic benefits for customers, industry, carmakers, and policymakers. In this paper, an HEV concept based on renewable energy resources (RERs) is proposed. The proposed HEV design utilizes solar PV energy, wind energy, fuel cell, and a supercapacitor (PV + WE + FC + SC) which generates electrical energy via a proton exchange membrane (PEM) and an SC to cater for strong torque requirements. The vehicle incorporates a battery pack in conjunction with an SC for the power demands and an FC as the backup energy supply. An alternator connected to turbine blades runs by wind energy while the car is moving forward, which produces electricity through the alternator to charge the battery. The design aims to ensure zero carbon emission and improved energy efficiency, is lightweight, and incorporates in-wheel motors to eliminate the mechanical transmissions. Modeling and simulation were carried out for each subsystem using MATLAB® and Simulink® packages. ANSYS Fluent simulation was used to analyze wind energy. The standard analysis, e.g., pressure, velocity, and vector contour, were also considered while designing the final model. To regulate the power supply and demand, the selection of energy sources was controlled by a rule-based supervisory controller following a logical sequence that prioritizes energy sources with the SC as a source in-vehicle stop-and-go situations while the battery acts as the primary source, FC as a backup supply, and wind and solar power to recharge the battery. Solar charging is switched on automatically once the vehicle is parked, and the controller controls the energy flow from the alternator during that period.

Field edge rainwater harvesting and inorganic fertilizers for improved sorghum (Sorghum bicolor L.) yields in semi-arid farming regions of Marange, Zimbabwe

Sorghum (Sorghum bicolor L.) is mainly cultivated in marginal areas of Zimbabwe, where soil fertility is poor and rainfall is low, erratic, and poorly distributed, leading to low yields. The study aimed to determine the effect of tied contour (TC) and in-contour infiltration pits (IP) rainwater harvesting (RWH) methods and varying nitrogen fertilizer application rates on the yield of two sorghum varieties, Macia and Sc Sila. A split-split plot experiment was laid out, with the main plot factor being the RWH method, the subplot factor being sorghum variety, the sub-sub plot factor being nitrogen application, and the sub-sub-sub plot factor being the plant distance from the RWH method. The experiment was done at Mt Zonwe's small-scale farming community in the Mutare region from 2016/17 to 2018/19. The results revealed that TC and IP increased the gravimetric water content (gwc) of the soil. The gwc decreased gradually as the distance from the rainwater RWH method increased (0–5 m > 5–10 m > 10–15 m), with the 2016/17 season having the maximum gwc. In all seasons, TC and IP yielded much more sorghum grain than standard contour (SC). Sorghum grain production was significantly greater at all nitrogen application rates and consistently higher at all plant distances from the RWH method in the 2016/17 season with more rainfall. In comparison to TC and IP, the SC had significantly lower grain yield at all nitrogen application rates. At all plant distances from the RWH method, TC and IP had significantly higher grain production than SC in each variety of sorghum.

Effect of contour rainwater-harvesting and integrated nutrient management on sorghum grain yield in semi-arid farming environments of Zimbabwe

ABSTRACT The application of insufficient amounts of mineral fertiliser, coupled with unreliable precipitation, has caused a drastic reduction in the yield of sorghum in the smallholder-farming areas of Zimbabwe. This calls for innovative interventions to improve production under changing climatic conditions. This study evaluated the effect of contour-based rainwater-harvesting methods and the use of cattle manure + N nutrient amendment on sorghum yield. A split-split plot experiment was conducted where rainwater-harvesting practice, sorghum variety, cattle manure + N and distance from rainwater-harvesting structure were treatment factors. The results showed that the yield of sorghum was significantly higher under the tied contour and infiltration pits than standard contour at all distances from rainwater-harvesting practices and seasons. In all seasons sorghum varieties Macia and Sc Sila showed higher yield under the tied contour and infiltration pits than standard contour. However, regardless of the distance from rainwater-harvesting practice and season the sorghum variety, Macia showed a higher grain yield than Sc Sila. At each incremental level of N application to cattle manure, Macia had a higher grain yield than Sc Sila, and no significant grain yield benefits were shown in each variety at N application to cattle manure above 50 kg N ha−1.