Feature-specific nutrient management of onion (Allium cepa) using machine learning and compositional methods.

While onion cultivars, irrigation and soil and crop management have been given much attention in Brazil to boost onion yields, nutrient management at field scale is still challenging due to large dosage uncertainty. Our objective was to develop an accurate feature-based fertilization model for onion crops. We assembled climatic, edaphic, and managerial features as well as tissue tests into a database of 1182 observations from multi-environment fertilizer trials conducted during 13 years in southern Brazil.

Phytoremediation of Cu-contaminated vineyard soils in Brazil: A compendium of Brazilian pot studies.

Vineyard soils can be contaminated by copper (Cu) due to successive applications of fungicides and organic fertilizers. Soil remediation can be addressed by altering soil properties or selecting efficient Cu-extracting cover crops tolerant to Cu toxicity. Our objectives were to synthesize the Cu-extracting efficiency by plant species tested in Brazil, classify them according to Cu resistance to toxicity, and assess the effect of soil properties on attenuating Cu toxicity.

Prediction of Nitrogen Dosage in 'Alicante Bouschet' Vineyards with Machine Learning Models.

Vineyard soils normally do not provide the amount of nitrogen (N) necessary for red wine production. Traditionally, the N concentration in leaves guides the N fertilization of vineyards to reach high grape yields and chemical composition under the assumption. Moreover, the carryover effects of nutrients and carbohydrates stored by perennials such as grapevines are neglected.

Correction: Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

[This corrects the article DOI: 10.1371/journal.pone.

Garlic (Allium sativum) feature-specific nutrient dosage based on using machine learning models.

Brazil presents large yield gaps in garlic crops partly due to nutrient mismanagement at local scale. Machine learning (ML) provides powerful tools to handle numerous combinations of yield-impacting factors that help reducing the number of assumptions about nutrient management. The aim of the current study is to customize fertilizer recommendations to reach high garlic marketable yield at local scale in a pilot study.

Esmeralda Peach () Fruit Yield and Quality Response to Nitrogen Fertilization.

'Esmeralda' is an orange fleshed peach cultivar primarily used for juice extraction and secondarily used for the fresh fruit market. Fruit yield and quality depend on several local environmental and managerial factors, mainly on nitrogen, which must be balanced with other nutrients. Similar to other perennial crops, peach trees show carryover effects of carbohydrates and nutrients and of nutrients stored in their tissues.

Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

Accuracy of infrared (IR) models to measure soil particle-size distribution (PSD) depends on soil preparation, methodology (sedimentation, laser), settling times and relevant soil features. Compositional soil data may require log ratio (ilr) transformation to avoid numerical biases. Machine learning can relate numerous independent variables that may impact on NIR spectra to assess particle-size distribution.

Current and next-year cranberry yields predicted from local features and carryover effects.

Wisconsin and Quebec are the world leading cranberry-producing regions. Cranberries are grown in acidic, naturally low-fertility sandy beds. Cranberry fertilization is guided by general soil and tissue nutrient tests in addition to yield target and vegetative biomass.

Conditioning Machine Learning Models to Adjust Lowbush Blueberry Crop Management to the Local Agroecosystem.

Agroecosystem conditions limit the productivity of lowbush blueberry. Our objectives were to investigate the effects on berry yield of agroecosystem and crop management variables, then to develop a recommendation system to adjust nutrient and soil management of lowbush blueberry to given local meteorological conditions. We collected 1504 observations from N-P-K fertilizer trials conducted in Quebec, Canada.

Nutrient Diagnosis of at the Factor-Specific Level Using Machine Learning and Compositional Methods.

Brazil is home to 30% of the world's trees. The seedlings are fertilized at plantation to support biomass production until canopy closure. Thereafter, fertilization is guided by state standards that may not apply at the local scale where myriads of growth factors interact.

Balance design for robust foliar nutrient diagnosis of "Prata" banana (Musa spp.).

The "Cavendish" and "Prata" subgroups represent respectively 47% and 24% of the world banana production. Compared to world average progressing from 10.6 to 20.

Long-term impact of tillage practices and phosphorus fertilization on soil phosphorus forms as determined by p nuclear magnetic resonance spectroscopy.

Conservation tillage practices have become increasingly common in recent years to reduce soil erosion, improve water conservation, and increase soil organic matter. Research suggests that conservation tillage can stratify soil test phosphorus (P), but little is known about the effects on soil organic P. This study was conducted to assess the long-term effects of tillage practices (no-till [NT] and mouldboard plowing) and P fertilization (0 and 35 kg P ha) on the distribution of P species in the soil profile.

Nitrous oxide emissions from clayey soils amended with paper sludges and biosolids of separated pig slurry.

Wastes from animal production and from the paper industry are often used as amendments to agricultural soils. Although data exist on the impacts of raw animal wastes on NO production, little is known regarding the effects of paper wastes and biosolids from treated animal waste. We measured NO emissions for two consecutive snow-free seasons (mid-May through the end of October) from poorly drained clayey soils under corn ( L.

The plant ionome revisited by the nutrient balance concept.

Tissue analysis is commonly used in ecology and agronomy to portray plant nutrient signatures. Nutrient concentration data, or ionomes, belongs to the compositional data class, i.e.

Agri-environmental thresholds using Mehlich III soil phosphorus saturation index for vegetables in histosols.

The P concentration in Norton Creek which drains cultivated Histosols in Quebec showed median concentration exceeding up to 14 times the environmental guideline of 0.03 mg total P L(-1). The aim of this study was to develop environmental and agronomic thresholds using soil tests to provide a tool for P management in Histosols.