Production and nutritional value of wheat and triticale cultivars in different harvest times in the Minas Gerais semiarid

The objective of the present study was to evaluate the productive performance and nutritional value of forage of wheat and triticale cultivars at different harvest times in the semiarid region of Minas Gerais. Eight wheat cultivars and two triticale cultivars harvested at three stages of plant development were evaluated: Rubberization, grain at the stage of soft mass and harvest maturation. The experimental design adopted was a randomized block in a factorial scheme 10 × 3, with three replicates, 10 cultivars and 3 developmental stages for plant collection. The main agronomic characteristics and nutritional value were evaluated of forage of the cultivars under study. The study demonstrated the potential of wheat and triticale cultivation for forage in the semiarid region of Minas Gerais. The mean dry matter yield of wheat cultivars was 5.90 t ha-1, 7.85 t ha-1 and 7.98 t ha-1 and triticale 6.47 t ha-1, 9.97 t ha-1 and 10.5 t ha-1 for the rubber harvesting stages, grain at the stage of soft mass and harvest maturation, respectively. For the average crude protein content, the wheat cultivars showed 15.07%, 9.13%, 10.60% and the triticale cultivars showed 14.4%, 9.31% and 10.05% for the harvest stages of rubber formation, grain at the stage of soft mass and harvest maturation, respectively. When evaluating the average levels of total digestible nutrients, the wheat and triticale cultivars showed an average of 48.90% and 48.67% in the rubber harvesting stage and 42.68% and 49.60% in the grain in the mass stage suave and 44.43% and 42.90% at harvest maturation. The highest yield of digestible dry matter was observed with the cultivars harvested at the grain stage at the soft mass stage. Triticale IPR 111 and Wheat IPR PANATY had greater productive potential and better nutritional quality for use as forage.

EFFECT OF MATURITY STAGES ON POTENTIAL NUTRITIVE VALUE OF VICIA CRACCA (L.) HAY

The aim of the current experiment was to determine the effect of harvesting stage on the potential nutritive value. Vicia cracca plant was harvested at three maturity stages (before flowering, flowering and seeding). Vicia cracca plants were dried at 70 °C and grinded in a hand-mill with 1 mm sieve for chemical analysis. Crude protein, crude oil, crude ash, condensed tannin, acid detergent fiber (ADF), and neutral detergent fiber (NDF) parameters were investigated as the chemical composition. Harvesting stage had a significant (p ≤ 0.01) effect on chemical composition. Dry matter, NDF and ADF contents were increased with advancing maturity whereas crude protein, crude oil, condensed tannin and crude ash contents were decreased. As a conclusion, the nutritive value of Vicia cracca plant decreased with increasing maturity. Vicia cracca hays harvested at three maturity stages were adequate in term of mineral content for ruminant. Therefore, the Vicia cracca plant can be harvested or grazed before flowering and flowering stages due to high crude protein, crude oil and low ADF and NDF.

Logistics Chain and Cost Assessment of Pruning-to-Energy Value Chains: Application of Life Cycle Cost Analysis Approach

Biomass from agricultural residue has significant potential as renewable energy resource. Therefore, cost-efficient processing and supply of agricultural residues are important to strategically plan and utilize this energy resource. This chapter describes the agricultural pruning to energy (PtE) value chains and presents the life cycle cost analysis (LCCA)-based cost assessment results, focusing on almond and peach tree pruning data obtained from Spain during 2015–2016. Along the main life cycle stages of PtE system, costs of harvesting, off-farm storage, transport, biomass loss, and management of biomass supply chain were considered. In terms of functional unit cost, the life cycle cost (LCC) was calculated to be about 126 €/t for almond PtE and 115 €/t for peach PtE value chain. In both cases, the harvesting stage was found to be cost at hot stage followed by the storage stage. The cost at harvesting stage was about 83% (of 126 €/t) and 82% (of 115 €/t) in the case of almond and peach cases, respectively. Similarly, the share of operational cost was about 74% and 76% for almond and peach cases, respectively. Therefore, more efforts should be made to improve the performance of logistics operations and management of such PtE initiatives.

Diagnosis and Recommendation Integrated System (DRIS) Norms for Identifying Yield Limiting Nutrients in Byadgi Chilli Fruits Grown in Northern Transitional Zone and Dry Zones of Karnataka (India)

Fruit samples collected from different part of northern Karnataka districts of Dharwad, Gadag and Haveri, when peak fruit harvesting stage were collected the samples, were processed and analysed for various nutrients and thus, the data bank was established. By using Diagnosis and Recommendation Integrated System (DRIS), nutrient expressions, which have shown higher variance and lower coefficient of variation, were selected as norms viz, N/P(4.98), N/K (0.73), N/Ca (1.17), N/Mg (4.65), S/N(0.10), N/Fe(0.02), N/Zn(0.08) etc. In addition, five nutrient ranges have been derived using mean and standard deviation as low, deficient, optimum, high and excess for each nutrient to serve as a guide for diagnostic purpose. The optimum N ranged from 2.30 to 2.84%, P from 0.48 to 0.56%, K from 3.16 to 3.44%, Ca from 2.08 to 2.74%, Mg from 0.60 to 0.88% and S from 0.24 to 0.27%. Among the micronutrients, the optimum Zn ranged from 28.71 to 29.78 ppm, Fe from 113.60 to 150.03 ppm for byadgi chilli crop.

Conservation Strip Tillage Leads to Persistent Alterations in the Rhizosphere Microbiota of Brassica napus Crops

Microbes play vital roles in many soil ecosystem functions and services, which are crucial for agricultural productivity. Among different agricultural management practices, soil tillage methods can result in changes in a soil's physical, chemical and biological properties, including the soil microbiome. In addition, crop type and the plant developmental stage are important drivers of rhizosphere bacterial microbiota structure and composition. Here, we have used high-throughput, 16S amplicon sequencing to explore the rhizosphere bacterial structure and composition of Brassica napus (winter oilseed rape) in two contrasting tillage practices; conventional-plough based tillage and conservation strip tillage, over three different plant growth stages (vegetative, flowering and harvesting stage). This was the first year that conservation strip tillage was used in this field, as in previous years plough based tillage practices has been used. Our findings show that tillage and growth stages were important determinants of microbial community structure and composition, but the effect of tillage became stronger at plant maturity. The combined effect of conservation strip tillage and harvesting stage had a impact on the rhizosphere microbiota selection. The rhizosphere bacterial community of winter oilseed rape under conservation strip tillage was different to that under conventional tillage. Our data suggests that different tillage regimes created distinct ecological niches that selected different microbiota with potential consequences for the ecosystem services provided to the plants and the soil environment.

Development of Microalgae-based Biofuels as a Viable Green Energy Source: Challenges and Future Perspectives

This paper presents a comprehensive account of the harvesting and processing technologies of microalgae and their applications in developing biofuels such as biodiesel, ethanol, biogas, syngas, and hydrogen. Microalgae have been reflected as an environmental pollution controlling agent due to their faster growth rate, making them a viable alternative to replace the current uses of non-renewable sources. The significantly large volumes of microalgae culture required for bio products are highlighted as a major concern of the complexity at the harvesting stage. At present, there are hardly any single methods that could generally be applied for processing the broad range of microalgae species with varying characteristics. Improvements are also required to effectively minimize the energy and cost required for the microalgae processing methods to be applicable at a commercial scale. By improving the techniques used at the harvesting stage, the costs associated with further processing steps to produce microalgae-based bio products and biofuels could be reduced. Future studies should also focus on identifying better algae strains that produce a high yield of good quality biofuel to economically viable algae biofuel.

Prediction of Sugar Content in Port Wine Vintage Grapes Using Machine Learning and Hyperspectral Imaging

The high quality of Port wine is the result of a sequence of winemaking operations, such as harvesting, maceration, fermentation, extraction and aging. These stages require proper monitoring and control, in order to consistently achieve the desired wine properties. The present work focuses on the harvesting stage, where the sugar content of grapes plays a key role as one of the critical maturity parameters. Our approach makes use of hyperspectral imaging technology to rapidly extract information from wine grape berries; the collected spectra are fed to machine learning algorithms that produce estimates of the sugar level. A consistent predictive capability is important for establishing the harvest date, as well as to select the best grapes to produce specific high-quality wines. We compared four different machine learning methods (including deep learning), assessing their generalization capacity for different vintages and varieties not included in the training process. Ridge regression, partial least squares, neural networks and convolutional neural networks were the methods considered to conduct this comparison. The results show that the estimated models can successfully predict the sugar content from hyperspectral data, with the convolutional neural network outperforming the other methods.

Novel Nondestructive Technique to Determine Optimum Harvesting Stage of ‘Ataúlfo’ Mango Fruit

A portable spectrometer was validated to determine optimum harvesting stage of ‘Ataúlfo’ using dry matter and skin color as fruit indicators. To build the model, samples were collected as follows: a. Unripe; b. Green Mature 1; c. Green Mature 2; d. Green Mature 3; and e. Fully mature. Fruit were scanned with a near infrared spectrometer at three temperatures (15, 25, and 35 °C). Skin color (‘a’ value) was measured with a Minolta 400 colorimeter. DM was attained in a conventional oven by drying samples for 72 h at 60 °C. Model was built and validated three times. The best model linearity was obtained on skin color ‘a’ (R2 = 0.98), whereas for DM the R2 was only 0.70. For the first validation, the best predicted value was skin color ‘a’ with an R2 = 0.9144, followed by DM with an R2 = 0.7056. On the second validation, the adjusted predicted value for skin color ‘a’ had an R2 = 0.8798, while DM had an R2 = 0.4445. When comparing NIR versus Heat Units Accumulation, in Nayarit, ‘Ataúlfo’ skin color average difference between the spectrometer vs the colorimeter was only -0.04. For ‘Ataúlfo’ from Sinaloa, skin color average difference was only -0.06, but the correlation was higher (R2 = 0.90). In conclusion, measuring skin color with the NIR spectrometer has potential as a nondestructive technique to determine the optimum harvesting stage of ‘Ataúlfo’ mango.