Effect of planting density on yield and yield components of lettuce (Lactuca sativa L.) at two agro-ecologies of Ethiopia

Mengistu, Fekadu Gebretensay; Tabor, Getachew; Dagne, Zebenay; Atinafu, Gizachew; Tewolde, Fasil Tadesse

doi:10.5897/ajar2020.15384

Cited by 4 publications

(1 citation statement)

References 4 publications

(8 reference statements)

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“…Among salad crops, lettuce is one of the most widely grown and takes up the greatest amount of production space worldwide [ 3 , 4 ]. It is consumed primarily fresh and is rich in minerals, vitamins, phenolic compounds and fibers [ 4 , 5 ]. It grows in diverse climatic conditions and soil types.…”

Section: Introductionmentioning

confidence: 99%

Growth and marketable yield of lettuce (Lactuca sativa L.) as affected by bio-slurry and chemical fertilizer application

Meskelu,

Senbeta,

Keneni

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Growth and marketable yield of lettuce (Lactuca sativa L.) as affected by bio-slurry and chemical fertilizer application

Meskelu,

Senbeta,

Keneni

et al. 2024

Heliyon

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Heavy metal accumulation and food safety of lettuce (Lactuca sativa L.) amended by bioslurry and chemical fertilizer application

Meskelu,

Senbeta,

Keneni

et al. 2024

Food Science & Nutrition

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The accumulation of heavy metals in soil and plant tissue is a serious concern since it impacts both soil quality and food safety. This study evaluated the accumulation of heavy metals and the food quality of lettuce as a result of the application of chemical fertilizer (CF) and bioslurry (BS). The treatments were CF (158 kg ha−1 NPS and 200 kg ha−1 urea), BS (5 ton ha−1), and control with no fertilizer, laid out in a randomized complete block design with three replications. Soil samples were analyzed for their physico‐chemical characteristics. The concentrations of 10 heavy metals (As, Pb, Zn, Cd, Cu, Ni, Co, Fe, Mn, and Cr) in the agricultural soil, bioslurry, and lettuce tissue were determined. Both the BS and CF reduced the concentrations of most heavy metals in the agricultural soil, particularly As, Pb, and Cd. Only the mean concentration of Cd in the agricultural soils exceeded the threshold level set by WHO/FAO (2011) for agricultural soils. Similarly, the concentration of As, Pb, and Cd in lettuce tissue grown in BS‐treated soils and the concentration of As in agricultural soils surpassed the limit set for vegetables. Given the toxicities of As, Cd, and Pb, as well as the effect on food safety, human health, and the environment, it is unsafe to cultivate lettuce using either the agricultural soil or BS in the study area.

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Lettuce Production in Intelligent Greenhouses—3D Imaging and Computer Vision for Plant Spacing Decisions

Πετροπούλου

Marrewijk

Zwart

et al. 2023

Sensors

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Recent studies indicate that food demand will increase by 35–56% over the period 2010–2050 due to population increase, economic development, and urbanization. Greenhouse systems allow for the sustainable intensification of food production with demonstrated high crop production per cultivation area. Breakthroughs in resource-efficient fresh food production merging horticultural and AI expertise take place with the international competition “Autonomous Greenhouse Challenge”. This paper describes and analyzes the results of the third edition of this competition. The competition’s goal is the realization of the highest net profit in fully autonomous lettuce production. Two cultivation cycles were conducted in six high-tech greenhouse compartments with operational greenhouse decision-making realized at a distance and individually by algorithms of international participating teams. Algorithms were developed based on time series sensor data of the greenhouse climate and crop images. High crop yield and quality, short growing cycles, and low use of resources such as energy for heating, electricity for artificial light, and CO2 were decisive in realizing the competition’s goal. The results highlight the importance of plant spacing and the moment of harvest decisions in promoting high crop growth rates while optimizing greenhouse occupation and resource use. In this paper, images taken with depth cameras (RealSense) for each greenhouse were used by computer vision algorithms (Deepabv3+ implemented in detectron2 v0.6) in deciding optimum plant spacing and the moment of harvest. The resulting plant height and coverage could be accurately estimated with an R2 of 0.976, and a mIoU of 98.2, respectively. These two traits were used to develop a light loss and harvest indicator to support remote decision-making. The light loss indicator could be used as a decision tool for timely spacing. Several traits were combined for the harvest indicator, ultimately resulting in a fresh weight estimation with a mean absolute error of 22 g. The proposed non-invasively estimated indicators presented in this article are promising traits to be used towards full autonomation of a dynamic commercial lettuce growing environment. Computer vision algorithms act as a catalyst in remote and non-invasive sensing of crop parameters, decisive for automated, objective, standardized, and data-driven decision making. However, spectral indexes describing lettuces growth and larger datasets than the currently accessible are crucial to address existing shortcomings between academic and industrial production systems that have been encountered in this work.

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Effect of planting density on yield and yield components of lettuce (Lactuca sativa L.) at two agro-ecologies of Ethiopia

Cited by 4 publications

References 4 publications

Growth and marketable yield of lettuce (Lactuca sativa L.) as affected by bio-slurry and chemical fertilizer application

Growth and marketable yield of lettuce (Lactuca sativa L.) as affected by bio-slurry and chemical fertilizer application

Heavy metal accumulation and food safety of lettuce (Lactuca sativa L.) amended by bioslurry and chemical fertilizer application

Lettuce Production in Intelligent Greenhouses—3D Imaging and Computer Vision for Plant Spacing Decisions

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