ALBERT

Description: In this study, an experiment was performed to evaluate the effect of lactic acid bacteria and 3-phenyllactic acid (PLA) on the fermentation quality and chemical composition of alfalfa silage. Several PLA-tolerant strains were screened from silages and identified. The selected strains (1 × 106 colony forming units/g fresh alfalfa) and PLA (1.0, 2.0, or 3.0 g/kg) were applied to alfalfa before ensiling. After 45 days of storage, the silages were unsealed and subjected to component analysis. Biochemical methods and 16S rDNA gene sequencing were used for the identification of the two strains as Lactobacillus plantarum. The characteristics of chemical and fermentation compounds indicated that PLA and the two strains efficiently improved the quality of the alfalfa silage. It can be concluded that the use of the strains and PLA can significantly improve the quality of silage.

Description: Reduction of soil greenhouse gas emissions is crucial to control increases in atmospheric CO2 concentrations. Permanent grasslands are of considerable importance in climate change mitigation strategies as they cover about 13% of the global agricultural area. However, uncertainties remain for the effects of management practices on soil respiration, especially over the short term. This study investigated the influence of different mowing intensities on soil respiration over the short term for Bromus erectus-dominated grasslands in the central Apennines. From 2016 to 2018, soil respiration, temperature, and moisture were measured under three different management systems: customary management, intensive use, and abandonment. Both soil water content and temperature changed over time, however mowing did not affect soil water content while occasionally altered soil temperature. The intensive use promoted higher seasonal mean soil respiration compared to the abandonment only during the 2016 growing season. Soil temperature was the main driver of soil respiration above a soil water content threshold that varied little among treatments (18.23–22.71%). Below the thresholds, soil moisture was the main driver of soil respiration. These data suggest that different mowing regimes have little influence on soil respiration over the short term in Bromus erectus-dominated grasslands. Thus, more intensive use would not have significative impacts on soil respiration, at least over the short term. Future studies need to clarify the role of root mycorrhizal and microbial respiration in the light of climate change, considering the seasonal redistribution of the rainfall.

Description: Life Cycle Assessment (the systematic analysis of the environmental impact of products during their entire life cycle), Carbon Footprint and Water Footprint assessments play an important role in decision-making processes. These assessments can help guide land management decisions and will likely play a larger role in the future, especially in natural areas with high biodiversity. Agriculture is a substantial consumer of fresh water, so it is important to identify causes and possible solutions to optimize agricultural water use. Water footprint assessments consider water consumption from several points of view and aid in reaching Sustainable Development Goals. Olive trees are a widespread agricultural crop growing in the Mediterranean Basin and are particularly important in the Umbria region in Italy. This paper estimates the water footprint impact related to the production of 1 kg of olives in a rainfed olive orchard managed using low environmental impact techniques. Eleven years of data collection (meteorological data, olives yield data, processes data) are analyzed for typical rural conditions. The results show that local management techniques have lower water requirements than standard international usages. These results can be used to improve and to further explore agricultural water use.

Description: Smart agriculture management systems with real-time control of plant health and vegetation are recognized as one of the crucial technologies determining agriculture development, playing a fundamental role in reducing yield losses and improving product quality. The earliest plant responses to various adverse factors are propagating stress signals, including electrical ones, and the changes in physiological processes induced by them. Among the latter, photosynthesis is of particular interest due to its key role in the production process. Of practical importance, photosynthesis activity can be registered not only in contact mode but by remote sensing using optical methods. The aim of the present work was to develop the approach to automatic determination of the main parameters of electrical signals and changes in photosynthesis activity and transpiration using continuous wavelet transform (CWT). Applying CWT based on derivatives of the Gaussian function allows accurate determination of the parameters of electrical signals as well as induced physiological responses. Moreover, CWT was applied for spatio-temporal mapping of the photosynthesis response to stress factors in pea leaf. The offered approach allowed automatic identification of the response start time in every pixel and visualization of the change propagation front. The results indicate high potential of CWT for automatic assessment of plants stress, including monitoring of plant health in large-scale agricultural lands and automated fields.

Description: Since each greenhouse gas (GHG) has its own radiative capacity, all three gasses (CO2, CH4 and N2O) must be accounted for by calculating the net global warming potential (GWP) in a crop production system. To compare the impact of GHG fluxes from the rice growing and the fallow season on the annual gas fluxes, and their contribution to the GWP and carbon sequestration (CS) were evaluated. From May to April in Bibai (43°18′ N, 141°44′ E), in central Hokkaido, Japan, three rice paddy fields under actual management conditions were investigated to determine CS and the contribution of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) fluxes to GWP. Methane and N2O fluxes were measured by placing the chamber over the rice plants covering four hills and CO2 fluxes from rice plants root free space in paddy fields were taken as an indicator of soil microbial respiration (Rm) using the closed chamber method. Soil CS was calculated as the difference between net primary production (NPP) and loss of carbon (C) through Rm, emission of CH4 and harvest of crop C. Annual cumulative Rm ranged from 422 to 519 g C m−2 yr−1; which accounted for 54.7 to 55.5% of the rice growing season in particular. Annual cumulative CH4 emissions ranged from 75.5 to 116 g C m−2 yr−1 and this contribution occurred entirely during the rice growing period. Total cumulative N2O emissions ranged from 0.091 to 0.154 g N m−2 yr−1 and from 73.5 to 81.3% of the total N2O emissions recorded during the winter-fallow season. The CS ranged from −305 to −365 g C m−2 yr−1, suggesting that C input by NPP may not be compensate for the loss of soil C. The loss of C in the winter-fallow season was much higher (62 to 66%) than in the growing season. The annual net GWP from the investigated paddy fields ranged from 3823 to 5016 g CO2 equivalent m−2 yr−1. Annual GWPCH4 accounted for 71.9 to 86.1% of the annual net GWP predominantly from the rice growing period. These results indicate that CH4 dominated the net GWP of the rice paddy.

Description: The nutritive value of forage for herbivores has been for a long time determined by the concentration in protein and, hence in nitrogen (N), the concentration in different minerals (P, K, Ca, Mg, and oligo-elements), and the in vivo dry matter (DM) digestibility. Forage DM digestibility, the proportion of ingested DM being metabolized by ruminant animals has been related to different components of plant tissue composition such as Neutral Detergent Fiber (NDF) and Acid Detergent Fiber (ADF); the NDF concentration represents an estimate of cell wall content while the ADF concentration is an estimate of the more lignified cell wall content. Forage nutritive value is generally analyzed by relating the attributes of nutritive value to plant phenology, in order to predict the decline of these attributes with plant age. A more functional approach, initially developed for the analysis of N concentration dynamic analysis (Lemaire et al. 2008 and Lemaire et al. 2019), and extended for digestibility for this review, is based on the assumption that above-ground plant mass (W) is composed of two compartments: (i) the metabolic compartment (Wm), associated with plant growth process scaling with leaf area, having a high N concentration (%N), and a high Digestibility (%D); (ii) the structural compartment (Ws) associated with architectural plant development, scaling with plant height and thickness and having low %N and %D. With the postulate that Wm is allometrically related to W (Wm = c × Wα with α 〈 1), the ontogenetic decline of both %N and %D as the plant gets bigger and forage mass increases can be explained, and the purely empirical statistical approach of forage quality based on plant phenology can be replaced by a more mechanistic and comprehensive analysis linking forage production and forage quality dynamics within the same functional approach for a better understanding of genotype-environment-management interactions.

Description: Fresh market southern highbush blueberries are typically hand-harvested which requires an extensive labor force over a relative short period of time. With rising production costs and labor availability issues, interest in mechanical harvesting options is increasing. In 2017, an over-the-row (OTR) harvester was modified to reduce purchase cost while making hand labor more efficient. The picking heads were removed and dual worker stations were added on each side of the unit. Handheld olive shakers were suspended at each station. Experimental catch plates were installed on one side of the OTR harvester and soft, inclined surfaces over the rigid conveyors on both sides. ‘Meadowlark’ and ‘Farthing’ blueberries were harvested with this system and compared to those manually harvested by a commercial harvest crew. Samples from each harvest method were then commercially cooled and mechanically harvested fruit were commercially packed to determine packout data. Fruit firmness, bruise severity and composition were determined after one day at room temperature (22 °C) and after seven and fourteen days of storage at 1 °C. Average packout was very high for mechanically harvested fruit, 87% for ‘Meadowlark’ and 91% for ‘Farthing’. Initial firmness of both cultivars was lower for mechanically harvested fruit (208 g/mm) than hand-harvested fruit (243 g/mm). Fruit from the three treatments softened during storage, and although ‘Meadowlark’ remained firmer than ‘Farthing’ during storage, there were no differences due to catch surfaces. Hand-harvested fruit had no severe bruising (〉20% of cut surface area) at harvest, increasing to 2% after seven days, while mechanically harvested fruit from both fruit collection surfaces had 3% initial severe bruising that increased to 22% during storage. ‘Farthing’ had slightly higher soluble solids content and significantly higher total titratable acidity compared to ‘Meadowlark’. Additional modifications must be made to the next-generation OTR harvester to further reduce blueberry harvest and handling impacts.

Description: The global production of broiler meat was forecasted to be 97.8 MT in 2019. The cost fluctuations create risks in production. In order to have an effective management system, process uncertainty must be taken into account. This approach considers the process as an interval with fuzzy numbers and, for managing the risks, it uses the variable α, a parameter determined by the manager in an interval between 0 and 1. Then two algorithms, namely the multi-objective imperialist competitive algorithm (MOICA) and multi-objective particle swarm optimization (MOPSO), were compared and applied. Since the process of production has many activities and each activity has possible options, the process does not have a unique solution. Therefore, the objective function and its assigned weights in terms of time, cost, and quality can be applied to select the best solution from those obtained. A vast amount of uncertainty can be observed, and effective management necessitates dealing with these uncertainty issues. The MOPSO algorithm showed better performance than the MOICA algorithm in this problem. Based on fuzzy logic and influenced by the uncertainty condition (α = 0), time, cost, and quality in the MOPSO and the MOICA algorithms were 1793.8 h, $260,571.7, and 46.66%, and 1792.5 h, $260,585.7, and 51.19%, respectively.

Description: The purpose of this study was to evaluate (a) the performance of two modern rice varieties (non-tolerant and tolerant for saline soils) under different fertilizer management options, and (b) assess the yield gap and income increase through proper crop and nutrient management at different levels of soil salinity. Experiments were carried out in moderate and high levels of soil salinity in West Java, Indonesia. A split plot design with three replications was used. The main plots included two rice varieties, Inpari-30 Ciherang sub1 and Inpari-34 (tolerant variety for saline soils), and subplots included eight fertilizer management treatments. Farmer participatory field trials were also established across three levels of soil salinity with four different rice varieties, Sidenuk, Inpari 30, Inpari 34, and Inpari 35, and a fertilizer package consisting of organic and inorganic fertilizers. Under low and moderate soil salinities, Sidenuk and Inpari 30 with recommended practice had higher productivity and economic benefit compared to the saline tolerant rice varieties, Inpari 34 and Inpari 35. However, under high soil salinity, the yields of Inpari 34 and Inpari 35 with recommended practice were 93% higher than farmers’ practice, representing an exploitable yield gap of 1.3 t ha-1 and benefit above fertilizer cost of USD 301 ha−1. The combination of tolerant varieties and improved nutrient management use for rice production can therefore be used as a strategy for improving farmers’ income and livelihoods in coastal areas of Indonesia.

Description: To achieve the optimal and diverse utilization of cotton (Gossypium hirsutum) plant residues in various agricultural, industrial, and environmental applications, the chemical composition of cotton biomass tissues across different plant parts (e.g., seed, boll, bur, leaves, stalk, stem, and root) is of essential information. Thus, in this work, we collected field-grown whole mature cotton plants and separated them into distinct biomass fractions including main stems, leaf blades, branches, petioles, roots, and reproductive parts (mid-season growth stage) or bur, peduncles/bract, and seed cotton (pre-defoliation stage). The contents of selected carbohydrates and amino acids in these cotton biomass materials were determined. Both essential and nonessential amino acids were enriched in cotton leaf blades and reproductive parts. The distribution pattern of the selected carbohydrates differed from that of amino acids—higher contents of carbohydrate were found in roots, main stems, and branches. Although glucose was the most abundant non-structural carbohydrate in cotton plant parts at mid-season, xylose was the most abundant in most plant parts at the pre-defoliation stage. Nutritional carbohydrates and amino acids were further accumulated in seeds at pre-defoliation. The information reported in this work would be helpful in exploring and optimizing management practices and processing strategies for utilizing cotton crop biomass materials as valuable and renewable natural resources.