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.

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.

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.

Natural abundance analysis of the role played by N as indicator for the certification of organic-system deriving food.

Background: The natural abundance of stable isotope N (δ N) in production systems has emerged as an alternative to distinguish organic products from conventional ones. This study evaluated the use of δ N values recorded for nitrogen fertilizers, soil and plant tissue in order to set the differences between organic and conventional agricultural production systems applied to rice, potatoes, apple and banana crops.

Results: Values of δ N recorded for N sources ranged from +5.

Earthworm species in spp. plantations in Brazil and worldwide.

Bananas and plantains are major commodity/food crops that represent an important habitat for earthworms, although so far, no review is available on earthworm communities associated with banana/plantain crops worldwide. The Vale do Ribeira region is among the largest banana producing areas in Brazil, but little is known of the earthworms living there. Hence, the present study assessed earthworm populations and species in three banana plantations and adjacent Atlantic forest fragments along the Ribeira de Iguape River using standard (hand sorting) methodologies.

Plant ionome diagnosis using sound balances: case study with mango (Mangifera Indica).

Plant ionomes and soil nutrients are commonly diagnosed in agronomy using concentration and nutrient ratio ranges. However, both diagnoses are biased by redundancy of information, subcompositional incoherence and non-normal distribution inherent to compositional data, potentially leading to conflicting results and wrong inferences. Our objective was to present an unbiased statistical approach of plant nutrient diagnosis using a balance concept and mango (Mangifera indica) as test crop.

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.