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Sgorlon, Enrico (2018) Integrated and sustainable management of intensive broiler farming according to the environmental balance logic. [Tesi di dottorato]

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Abstract (inglese)

With respect to meat production in Italy, poultry meat production is among the main ones with a production of 1.25 million tonnes, 68% of which is broiler meat (Avec, 2015). Most of the broiler meat come from standard indoor system farms and they are located in the North-East regions (Unaitalia, 2014), often concentrated in specific areas, that frequently leads to criticism due to emissions, in particular ammonia (NH3), nitrous oxide (N2O) and methane (CH4) produced and the difficulty to obtain a proper disposal of poultry manure. This is because the broiler farms in these areas are a lot and all are characterized by the absence of field where the poultry manure could be spread. The broiler standard indoor system is characterized by a standard production chain, which starts with the companies that produce the feed and closes with the companies that slaughter and prepare the finished product. However, the poultry chain has never given much importance to the co-product that inevitably forms, that is, the poultry manure. The poultry manure is a co-product, it has an excellent amounts of nitrogen and phosphorus (Chamblee and Todd, 2002). This situation leads to problems of the emissions of broiler farm and the correct management of the poultry manure and the consequent environmental impacts. For these reasons, the research follows three research lines: i) use mix of microorganisms (LW) in the broiler breeder phase (PM = poultry manure treatment, DW = drinking water treatment and CL = control or no treatments); ii) three utilization scenarios of poultry manure (direct field spread = DFS, production of organic fertilizers = POF and combustion plant = CP). The last two scenarios produce organic fertilizer, also (IFA, 2012); iii) application of a field simulation model and compare cultures with high (Hi) and low (Li) input, in particular respect nitrogen (N). The third line of research has been developed because, although not strictly related to the use of poultry manure, it concerns nitrogen (N) and its application to a crop. Since the poultry manure has a lot of nitrogen (N), it has been considered interesting to evaluate this element, considering the problems connected to it also and especially bound by the Nitrates Directive (91/676/CEE and DM 5046 of 25 February 2016). The first line, was evaluated using the methodology Life Cycle Assessment (LCA). The second with LCA and DeNitrification- DeComposition (DNDC) model approaches. Finally, the last with DNDC model.
From the first line of research (i), it can be deduced that, except the greater environmental impact of feed that are 81% of CL, 79% of PM and DW, microorganism treatments have reduced emissions from broiler breeding farm and hence, environmental impacts. The environmental impacts of the two types of treatment (PM and DW) are compared to the CL both. The Terrestrial Acidification (TA) expressed as kg SO2 eq., in PM is less than 11.057% and in DW is 4.876%. In the Particular Matter Formation (PMF) expressed as kg PM10 eq., in PM is less than 9.076 and in DW is less than 2.727. In the Eutrophication Potential (EP) expressed as kg PO4 eq., in the PM is less than 5.212 and in DW is less than 0.101. On the other hand, there have not been significant results with a lower environmental impact as regards the Climate Change (CC) expressed as kg CO2 eq. Finally, with regard to housing emissions, especially with respect to NH3, Monte Carlo analysis showed a significant reduction in emissions between the different scenarios. In PM there were less emissions of 69% and 77% in DW, respectively compared to CL.
Instead, from the second line of the research (ii), the environmental impacts of utilization scenarios of poultry manure (POF and CP) are both compared to the DFS. In Eutrophication (EP) expressed as kg PO4- eq., there is a lower environmental impact of 33% in the CP. Instead, it is higher of 16.2% in the POF, in agreement with other studies, also (González-García et al., 2014). Another important impact category to consider is the Acidification (AP) expressed as kg SO2 eq., that is higher in POF scenario of 2.5%, insteed it is less of 9.7% in CP. This becouse the N leach (nitrate), is 22.11, 20.17 and 16.43 kg N/ha/y in a time horizon of 100 years in production of POF, DFS and CP, respectivelly. The Photochemical Oxidation expressed as kg C2H4 eq., it is less of 5.2% in the POF and it is less of 28% in the CP. The Particular Matter Formation (PMF) expressed as PM10 eq., it is less of 18% in the CP. The Abiotic Depletion of Fossil Fuel (FD) expressed as MJ, it is less of 9.5% in the CP and insteed, it is higher of 5,4% in the POF. The Cumulative Energy Demand (CED) expressed as MJ, it is less of 8.1% in the POF and it is less of 4.9% in the CP. Regarding FD, and especially for the CED, values of higher environmental impact for POF, it is due to the high energy request.
Finally, from the thrid line of the research (iii), despite of its positive applications, the use of active light crop canopy remote sensors for in-season site-specific nitrogen (N) management, has some drawbacks. The development of algorithms to estimate in-season N rates is based on data that relates canopy spectral data to potential yield and N uptake over multiple years and locations. Furthermore, canopy sensing-based N rate algorithms use in-season estimation of canopy N status to prescribe N rate need to reach yield potential, but is does not account for crop streses between sensing and harvest. The goal of this third study was to develop and test a methodology for combining normalized difference vegetation index data (NDVI) and simulating the assess spatial variability of corn N stress and in-season N rate. Using two season data (2008-2009) of five corn fields located in the Venice lagoon watershed, spatial model calibration and simulation were conducted using the CERES – Maize model in DSSAT in conjunction with the GeoSpatial Simulaton (GeoSim) tool in the Quantum GIS software. The model was first optimized to properly predict the yield, and subsequently to match the simulated and the NDVI-derived leaf area index (LAI). Model accuracy in yield estimation was reached by soil parameters optimization and was not negatively influenced by model optimization for LAI. In order to evaluate the advantages of coupling modelling and spectral data, N stress was simulated and optimum rates able to minimize it were evaluated. The incorporation of proximal sensed-derived data into the model guaranteed to increase the accuracy of Nitrogen stress simulation, due to the relationship between NDVI, LAI and N stress. Manage an inseason site-specific fertilization aiming to minimize N stress could N efficiency not guarantee to satisfy other criteria, such as the maximum achievable yield, the economic convenience or the environmental impact of the fertilization.

Abstract (italiano)

Per quanto riguarda la produzione di carne in Italia, la produzione di carne avicola è tra le principali con una produzione di 1,25 milioni di tonnellate, del quale il 68% sono polli da carne o broiler (Avec, 2015). La maggior parte della carne di broiler proviene da allevamenti intensivi e si trovano nelle regioni del Nord-Est (Unaitalia, 2014), spesso concentrate in aree specifiche, che frequentemente portano a criticismi dovuti alle emissioni, in particolare all'ammoniaca (NH3), all’ossido di diazoto (N2O) e al metano (CH4) prodotti e la difficoltà di ottenere un corretto smaltimento della lettiera. Questo perché gli allevamenti di polli da carne in queste aree sono molto numerosi e tutti sono caratterizzati dall'assenza di terreno in cui la lettiera potrebbe essere sparsa. L’allevamento intensivo del broiler è caratterizzato da una catena standard di produzione, che inizia con le aziende che producono il mangime e si chiude con le aziende che macellano e preparano il prodotto finito. Tuttavia, la catena di produzione non ha mai dato molta importanza al co-prodotto che inevitabilmente si produce, cioè la lettiera. La lettiera è un co-prodotto con una quantità eccellente di azoto e fosforo (Chamblee e Todd, 2002). Questa situazione porta a problemi dovuti alle emissioni prodotte negli allevamenti e alla corretta gestione della lettiera e di conseguenza agli impatti ambientali. Per questi motivi, la ricerca si sviluppa in tre linee: i) l’utilizzo di un pool di microrganismi (LW) nella fase di allevamento (PM = trattamento della lettiera, DW = trattamento dell'acqua di abbeveraggio e CL = controllo o nessun trattamento); ii) tre scenari di utilizzo della lettiera (spargimento diretto in campo = DFS, produzione di fertilizzanti organici = POF e impianto di combustione = CP). Gli ultimi due scenari producono anche fertilizzanti organici (IFA, 2012); iii) applicazione di un modello di simulazione sul campo e confronto di colture con elevato (Hi) e basso (Li) input, in particolare rispetto all'azoto (N). La terza linea di ricerca è stata sviluppata perché, sebbene non strettamente correlata all'utilizzo della lettiera, riguarda l'azoto (N) e la sua applicazione in campo. Poiché la lettiera ha molto azoto (N), si è stato considerato interessante valutare questo elemento, considerando i problemi ad essi connessi anche ed in particolarmente rispetto alla direttiva sui nitrati (91/676/CEE e DM 5046 del 25 febbraio 2016). La prima linea di ricerca, è stata valutata utilizzando la metodologia Life Cycle Assessment (LCA). Il seconda linea di ricerca con approccio metodologico LCA e DeNitrification- DeComposition (DNDC). Infine, l'ultima linea di ricerca con il modello DNDC.
Dalla prima linea di ricerca (i), si può dedurre che, ad eccezione del maggiore impatto ambientale dei mangimi che sono l'81% nel CL, il 79% nel PM e nel DW, i trattamenti con i microrganismi hanno ridotto le emissioni nell’allevamento dei broiler e quindi, gli ambientale impatti. Gli impatti ambientali dei due tipi di trattamento (PM e DW) sono stati entrambi confrontati con il CL. L'acidificazione terrestre (TA) espressa in kg di SO2 eq., nel PM è inferiore dell'11,057% e nel DW del 4,876% rispettivamente. Nella formazione del particolato (PMF) espressa come kg PM10 eq., nel PM è inferiore a 9.076 e nel DW è inferiore a 2.727. L’eutrofizzazione potenziale (EP) espressa come kg PO4 eq., nel PM è inferiore a 5.212 e nel DW è inferiore a 0.101. Non ci sono stati risultati significativi riguardo ad un minore impatto ambientale per quanto concerne il cambiamento climatico (CC) espresso in kg di CO2 eq. Infine, per quanto riguarda le emissioni dagli allevamenti, in particolare rispetto all'NH3, l'analisi Monte Carlo ha mostrato una significativa riduzione delle emissioni tra i diversi scenari. Nel PM ci sono state meno emissioni del 69% e nel DW meno emissioni del 77%, rispettivamente rispetto al CL.
Invece, riguardo la seconda linea di ricerca (ii), gli impatti ambientali dei diversi scenari di utilizzo ella lettiera (POF e CP) sono stati entrambi confrontati con il DFS. L’eutrofizzazione potenziale (EP) espressa in kg PO4- eq., ha mostrato un impatto ambientale inferiore del 33% nel CP. Invece, è superiore al 16,2% nel POF, in accordo con altri studi (González-García et al., 2014). Un'altra importante categoria di impatto ambientale considerata è l'acidificazione (AP) espressa in kg di SO2 eq., che è maggiore nel POF del 2,5%, mentre è inferiore al 9,7% in CP. Questo perché l’N lisciviato (nitrato) è 22.11, 20.17 e 16.43 kg N/ha/y in un orizzonte temporale di 100 anni nei rispettivi scenari POF, DFS e CP. L'ossidazione fotochimica espressa in kg C2H4eq., è inferiore al 5,2% nel POF ed è inferiore al 28% nel CP. La formazione di particolato (PMF) espressa come PM10 eq. è inferiore al 18% nel CP. L’esaurimento abiotico del combustibile fossile (FD) espresso come MJ, è inferiore al 9,5% nel CP ed invece è superiore al 5,4% nel POF. La domanda cumulativa di energia (CED) espressa come MJ, è inferiore all'8,1% nel POF e al 4,9% nel CP, rispettivamente. Per quanto riguarda il FD, e in particolare per il CED, i valori di maggiore di impatto ambientale per lo scenario POF, è dovuta ad una maggiore richiesta di alta energia.
Infine, per quanto concerne la terza linea di ricerca (iii), nonostante le sue applicazioni positive, l'uso di sensori remoti per la gestione dell'azoto (N) dipendente dall’andamento della stagione e da siti specifici per colture erbacee, presentano alcuni inconvenienti. Lo sviluppo di algoritmi per stimare le quantità di N durante la stagione si basa su dati che mettono in relazione i dati spettrali della chioma con la resa potenziale e l'assorbimento di N in più anni e luoghi. Inoltre, gli algoritmi dell’andamento dell’N usano la stima stagionale dell’N nella pianta per definire quanto N bisogna raggiungere per massimizzare il rendimento, ma non tiene in considerazione lo stress delle colture tra il rilevamento e il raccolto. L'obiettivo di questo terzo studio era di sviluppare e testare una metodologia per combinare i dati dell'indice di vegetazione normalizzata (NDVI) e simulare la variabilità spaziale di valutazione dello stress e del tasso di N nel mais durante la stagione. Utilizzando dati stagionali (2008-2009) di cinque campi di mais situati nella zona lagunare di Venezia, la calibrazione e la simulazione del modello spaziale sono state condotte utilizzando il modello CERES-Maize in DSSAT, in combinazione con lo strumento GeoSpatial Simulaton (GeoSim) del software Quantum GIS. Il modello è stato inizialmente ottimizzato per prevedere correttamente la resa e successivamente per abbinare il dato simulato con l'indice di area fogliare derivante da NDVI (LAI). L'accuratezza del modello nella stima della resa è stata raggiunta ottimizzando i parametri del suolo e non è stata influenzata negativamente ottimizzando il modello che considera il LAI. Per valutare eventuali vantaggi della modellazione accoppiata e dei dati spettrali, sono stati simulati gli stress N e sono stati valutati i tassi ottimali in grado di minimizzarli. L'incorporazione di dati prossimali derivanti dai sensori nel modello ha garantito un aumento dell'accuratezza della simulazione dello stress di azoto, dovuta alla relazione tra NDVI, LAI e stress N. Gestire una concimazione sito specifica e che varia durante la stagione al fine di ridurre al minimo lo stress N potrebbe non garantire il soddisfacimento di altri criteri, come la massima resa ottenibile, la convenienza economica o l'impatto ambientale della fertilizzazione.

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Tipo di EPrint:Tesi di dottorato
Relatore:Guercini, Stefano
Correlatore:Marra, Mario
Dottorato (corsi e scuole):Ciclo 29 > Corsi 29 > TERRITORIO, AMBIENTE, RISORSE E SALUTE
Data di deposito della tesi:25 Maggio 2018
Anno di Pubblicazione:19 Gennaio 2018
Parole chiave (italiano / inglese):DNDC, microorganisms, emissions, ammonia, environmental impact, broiler, litter, Life Cycle Assessment, organic fertiliser, renewable energy, microorganismi, emissioni, ammoniaca, impatto ambientale, broiler, lettiera, Valutazione del Ciclo di Vita, fertilizzante organico, produzione di energia
Settori scientifico-disciplinari MIUR:Area 07 - Scienze agrarie e veterinarie > AGR/10 Costruzioni rurali e territorio agroforestale
Struttura di riferimento:Dipartimenti > Dipartimento Territorio e Sistemi Agro-Forestali
Codice ID:11238
Depositato il:25 Ott 2018 16:58
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