planting density
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2022 ◽  
Vol 177 ◽  
pp. 114542
Author(s):  
Kailei Tang ◽  
Jiayin Wang ◽  
Yang Yang ◽  
Gang Deng ◽  
Jian Yu ◽  
...  

Author(s):  
Negasu Gamachu Dinsa ◽  
Kassahun Desalegn Yalew

Background: The advantage of intercropping is the more efficient utilization of the all available resources and the increased productivity compared with each sole crop of the mixture. If cowpea and Lablab intercropping with Napier grass its nutritional values was improved. Methods: The experimental design was factorial combination arrangement in randomized complete block design with three inter and intra spaces (1 m × 0.5 m, 0.75 m × 0.5 m, 0.5 m × 0.5 m) and intercropping with two tropical legumes. Treatments were T1= Pure Napier grass at 1 m row spacing, T2= Napier grass intercropped with lablab at 0.75 m row spacing, T3= Napier grass intercropped with cowpea at 0.5 m row spacing, T4= Napier grass intercropped with cowpea at 1 m row spacing, T5= Napier grass intercropped with lablab at 0.5 m row spacing, T6= Pure Napier grass at 0.75 m row spacing, T7= Napier grass intercropped with lablab at 1 m row spacing, T8= Napier grass intercropped with cowpea at 0.75 m row spacing, T9= Pure Napier grass at 0.5 m row spacing and totally nine treatments were used. Soil samples were collected before and after forage harvested. Result: Napier grass intercropped with lablab and cowpea at different planting densities had significant effect (P less than 0.05) on the in vitro dry and organic matter digestibility (IVDMD, IVOMD) and increased digestibility. The OM degradation constant was significantly different (P less than 0.05) but ‘ED’ was not and for DM degradation ‘c’ and ‘b’ were non-significant (P greater than 0.05) for Napier grass intercropped with lablab and cowpea at different planting densities. In conclusion, Napier grass intercropped with lablab and cowpea at a planting density of 24 plants m-2 was better choice for high yield and forage quality.


PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0260877
Author(s):  
Bekele Hundie Kotu ◽  
Abdul Rahman Nurudeen ◽  
Francis Muthoni ◽  
Irmgard Hoeschle-Zeledon ◽  
Fred Kizito

This study was conducted to assess the potential impact of applying a new groundnut planting density on welfare of smallholder farmers in northern Ghana. We used data from on-farm experiments, focus group discussions, and a household survey. We followed three steps in our analysis. First, we conducted cost-benefit analysis in which we showed the economic advantage of the new technology over the farmers’ practice. Second, we predicted adoption rates along timeline using the Adoption and Diffusion Outcome Prediction Tool (ADOPT). Third, using the results of the first and the second steps, we estimated the potential impact of the technology on poverty at household level using a combination of methods such as economic surplus model and econometric model. The cost-benefit analysis shows that increasing plant density increases farmers’ financial returns i.e., the benefit-cost-ratio increases from 1.05 under farmers’ practice to 1.87 under the best plant density option, which is 22 plants/sqm. The adoption prediction analysis shows that the maximum adoption rate for the best practice will be 62% which will take about nine years to reach. At the maximum adoption rate the incidence of extreme poverty will be reduced by about 3.6% if farmers have access to the international groundnut market and by about 2% if they do not have. The intervention will also reduce poverty gap and poverty severity. The results suggest that policy actions which can improve farmers’ access to the international market will enhance farmers’ welfare more than the situation in which farmers have access to domestic markets only. Furthermore, promoting a more integrated groundnut value-chain can broaden the demand base of the produce resulting in higher and sustainable impact of the technology on the welfare of groundnut producers and beyond.


2022 ◽  
Author(s):  
Bo Hu ◽  
Peiyong Guo ◽  
Siyu Han ◽  
Yifan Jin ◽  
Yiting Nan ◽  
...  

Abstract Microplastics that enter the soil environment are transformed by migration and can affect soil properties, which in turn have an impact on soil function and biodiversity. In this study, we investigated the distribution of soil microplastics at different planting densities and their effects on soil properties in a mangrove restoration wetland. The results showed that the average abundance of soil microplastics in the study area was 2177.5 n/500g, with the largest proportion of 0.038-0.05 mm diameter microplastics accounting for 70.9% and the rest of the diameter microplastics accounting for less than 20%, indicating that the smaller the diameter microplastics are easy to accumulate in the wetland soil. The abundance of microplastics in the restored area by planting density was ranked as 0.5×0.5m > 1.0×0.5m > 1.0×1.0m > control area. Three microplastics, polyethylene terephthalate (PET, accounted for 52%), polyethylene (PE, accounted for 24%), and polypropylene (PP, accounted for 15%), were the most prevalent and dominant microplastics in the soils of the area. SEM images showed that fractures, tears, EDS spectroscopy showed that a large number of metals were detected on the surface of microplastics. PET can influence the distribution of soil particle size due to its adsorptive viscosity, which may affect soil structure. Apart from soil pH, all other physicochemical factors changed significantly in response to PET. Besides, the results of the CV analysis reflect that soils in vegetated areas are more susceptible to the effects of PET than bare ground soils resulting in greater variability in the properties.


2022 ◽  
Vol 12 ◽  
Author(s):  
Yu Zhou ◽  
Juan Huang ◽  
Zebi Li ◽  
Yu Wu ◽  
Jijun Zhang ◽  
...  

Ratooning is the cultivation practice of two harvests in one cropping season by producing a second crop from the original stubble, which could provide higher resource use efficiency and economic benefit compared with direct sown crops. Nitrogen (N) fertilizer and planting density (D) play a vital role in sorghum (Sorghum bicolor L.) production; however, limited information is available on the effects on yield and quality of the sorghum-ratoon system. To address this question, field experiments were conducted with three N treatments (120 kg N ha–1, N1; 180 kg N ha–1, N2; and 255 kg N ha–1, N3) and three D treatments (82,500 plant ha–1, D1; 105,000 plant ha–1, D2; and 127,500 plant ha–1, D3). The yield of the main crop was significantly higher than that of the ratoon crop. Increasing N could increase the yield and yield attributes of both main and ratoon crops, and the effect on the ratoon crop was greater than the main crop. With increasing D, the grain yield of both main and ratoon crops increased, though 1,000-grain weight and grain weight per ear decreased. The sorghum grain of the ratoon crop contained higher starch, protein, and tannin contents but lower fat content, indicating a better quality for liquor production. The quality traits were significantly affected by N and D, but the differences between treatments were smaller than that between the main and ratoon crop. Our results indicated that increasing the yield of ratoon crops could obtain a high yield and quality of the sorghum-ratoon system. It was recommended that 120 kg N ha–1 with 127,500 plant ha–1 for the main crop and a small amount of N be top-dressed in three new buds left on stubble in each hill for the ratoon crop.


Agriculture ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 97
Author(s):  
Feng Wang ◽  
Jun Xue ◽  
Ruizhi Xie ◽  
Bo Ming ◽  
Keru Wang ◽  
...  

Determining the water productivity of maize is of great significance for ensuring food security and coping with climate change. In 2018 and 2019, we conducted field trials in arid areas (Changji), semi-arid areas (Qitai) and semi-humid areas (Xinyuan). The hybrid XY335 was selected for the experiment, the planting density was 12.0 × 104 plants ha−1, and five irrigation amounts were set. The results showed that yield, biomass, and transpiration varied substantially and significantly between experimental sites, irrigation and years. Likewise, water use efficiency (WUE) for both biomass (WUEB) and yield (WUEY) were affected by these factors, including a significant interaction. Normalized water productivity (WP*) of maize increased significantly with an increase in irrigation. The WP* for film mulched drip irrigation maize was 37.81 g m−2 d−1; it was varied significantly between sites and irrigation or their interaction. We conclude that WP* differs from the conventional parameter for water productivity but is a useful parameter for assessing the attainable rate of film-mulched drip irrigation maize growth and yield in arid areas, semi-arid areas and semi-humid areas. The parametric AquaCrop model was not accurate in simulating soil water under film mulching. However, it was suitable for the prediction of canopy coverage (CC) for most irrigation treatments.


Agriculture ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 92
Author(s):  
Mohammadreza Ramezani ◽  
Arash Dourandish ◽  
Tinoush Jamali Jaghdani ◽  
Milad Aminizadeh

The cultivation of saffron, which is one of the most expensive agricultural products in the world, is the main source of livelihood and economic wellbeing for the rural communities of Gonabad county in the eastern part of Iran. Nevertheless, farm monitoring in the region has shown that many saffron growers apply a high-density planting system for more profit. This practice results in the loss of land productivity after a six-year production cycle. As a consequence, farmers abandon the cultivated lands and move to plant saffron in available virgin lands. The purpose of this study is to analyse the technical efficiency of saffron farms and its determinants with an emphasis on the role of planting density. A survey was conducted in 2019, and a cross-sectional random sampling technique was used to select 110 saffron growers. We first assessed the technical efficiency of farms using a data envelopment analysis (DEA) model with input orientation. In the next step, efficiency scores were regressed on explanatory variables using OLS and bootstrapped truncated regression to identify efficiency related factors. We find that planting density negatively influenced technical efficiency, suggesting that it is necessary for saffron growers to be educated on the negative impacts of the dense planting system.


2022 ◽  
Vol 14 (2) ◽  
pp. 274
Author(s):  
Mohamed Marzhar Anuar ◽  
Alfian Abdul Halin ◽  
Thinagaran Perumal ◽  
Bahareh Kalantar

In recent years complex food security issues caused by climatic changes, limitations in human labour, and increasing production costs require a strategic approach in addressing problems. The emergence of artificial intelligence due to the capability of recent advances in computing architectures could become a new alternative to existing solutions. Deep learning algorithms in computer vision for image classification and object detection can facilitate the agriculture industry, especially in paddy cultivation, to alleviate human efforts in laborious, burdensome, and repetitive tasks. Optimal planting density is a crucial factor for paddy cultivation as it will influence the quality and quantity of production. There have been several studies involving planting density using computer vision and remote sensing approaches. While most of the studies have shown promising results, they have disadvantages and show room for improvement. One of the disadvantages is that the studies aim to detect and count all the paddy seedlings to determine planting density. The defective paddy seedlings’ locations are not pointed out to help farmers during the sowing process. In this work we aimed to explore several deep convolutional neural networks (DCNN) models to determine which one performs the best for defective paddy seedling detection using aerial imagery. Thus, we evaluated the accuracy, robustness, and inference latency of one- and two-stage pretrained object detectors combined with state-of-the-art feature extractors such as EfficientNet, ResNet50, and MobilenetV2 as a backbone. We also investigated the effect of transfer learning with fine-tuning on the performance of the aforementioned pretrained models. Experimental results showed that our proposed methods were capable of detecting the defective paddy rice seedlings with the highest precision and an F1-Score of 0.83 and 0.77, respectively, using a one-stage pretrained object detector called EfficientDet-D1 EficientNet.


2022 ◽  
Vol 6 (1) ◽  
pp. 1-10
Author(s):  
Mily Yolanda Ramírez Quiñones ◽  
Alberto Martin Medina Villacorta ◽  
Ritza Consuelo Collas Alva ◽  
Jaime Braulio Cahuana Flores ◽  
Andrea Rosario Pari Soto ◽  
...  

The research deals with nitrogen doses and sowing densities in peas. The objective was to determine which nitrogen dose and planting density obtained the highest yield. The methodology is based on applied research; Therefore, the statistical model of the Completely Random Block Design was used, which consisted of 3 blocks and 6 treatments. The doses were applied at 17 days 1/2 N, 100% P2O5 and 100% K2O and 62 days after sowing 1/2 N, it was evaluated from sowing to harvest and the data were processed by analysis of variance of two factors and Duncan, took leaf samples for foliar analysis and determined the total amount of nitrogen used. It was determined that T5 stood out in stem length with 128.42 cm, commercial yield with 12.53 tn/ha, T4 in weight of pods with 620 g, number of pods per plant with 48, T6 in nitrogen concentration with 6.60 g/ 100 g of dry matter and T5 in the amount of nitrogen used with 154.3 kg/ha that obtained the highest yield. It is concluded that the higher dose of nitrogen and less distance that is T5 obtained higher performance exceeding by 24.52% in relation to T1.


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