Modelling growth and nitrogen balance of barley under ambient and future conditions

According to current scenarios, atmospheric CO2 -concentration ([CO2]) and average air temperature will rise in the future. The predicted longer growing season in Finland would imply that more productive cultivars and even new crop species could be grown. Moreover, higher [CO2] is also likely to increase dry matter production of crops. This study analyzed the growth of spring barley (Hordeum vulgare L.) under ambient and suggested future conditions, and its response to N fertilization. Model simulations of soil temperature and of snow accumulation and melting were also studied. The calibration and validation results showed that the model performed well in simulating snow dynamics, soil temperature, the growth of barley, and the response of crop growth to N fertilization under present conditions. According to the simulation runs, if a cultivar was adapted to the length of the growing period, the increase in dry matter production was 23% in a low estimate scenario of climate change, and 56% in a high estimate scenario under a high level of nitrogen fertilization. The simulation study showed that the shoot dry weight increased by 43%, on average, under high N fertilization (150-200 kg N/ha), but by less (20%) under a low level of N (25-50 kg N/ha) when the conditions under a central scenario for the year 2050 were compared with the present ones

Integrating Vegetation Indices Models and Phenological Classification with Composite SAR and Optical Data for Cereal Yield Estimation in Finland (Part I)

Special Issue Microwave Remote Sensing.Abstract: During 1996–2006 the Ministry of Agriculture and Forestry in Finland, MTT Agrifood Research Finland and the Finnish Geodetic Institute carried out a joint remote sensing satellite research project. It evaluated the applicability of composite multispectral SAR and optical satellite data for cereal yield estimations in the annual crop inventory program. Three Vegetation Indices models (VGI, Infrared polynomial, NDVI and Composite multispetral SAR and NDVI) were validated to estimate cereal yield levels using solely optical and SAR satellite data (Composite Minimum Dataset). The average R2 for cereal yield (yb) was 0.627. The averaged composite SAR modeled grain yield level was 3,750 kg/ha (RMSE = 10.3%, 387 kg/ha) for high latitude spring cereals (4,018 kg/ha for spring wheat, 4,037 kg/ha for barley and 3,151 kg/ha for oats). Keywords: Composite multispectral modeling; SAR; classification; SatPhenClass algorithm; minimum dataset; cereal yield; phenology; LAI-bridge; CAP; IACS; FLPISPeer reviewe

Cereal yield modeling in Finland using optical and radar remote sensing : Special Issue Global Croplands

Peer reviewe

Growth Response of Cassava to Deficit Irrigation and Potassium Fertigation during the Early Growth Phase

Cassava (Manihot esculenta Crantz) experiences intermittent water deficit and suffers from potassium (K) deficiency that seriously constrains its yield in the tropics. Currently, the interaction effect between deficit irrigation and K fertigation on growth and yield of cassava is unknown, especially during the early growth phase. Therefore, pot experiments were conducted under controlled greenhouse conditions using cassava cuttings. Treatments initiated at 30 days after planting included three irrigation doses (30%, 60%, 100% pot capacity) and five K (0.01, 1, 4, 16, and 32 mM) concentrations. The plants were harvested 90 days after planting. Decreasing irrigation dose to 30% together with 16 mM K lowered the leaf water potential by 69%, leaf osmotic potential by 41%, photosynthesis by 35%, stomatal conductance by 41%, water usage by 50%, leaf area by 17%, and whole-plant dry mass by 41%, compared with full-irrigated plants. Lowering the K concentration below 16 mM reduced the values further. Notably, growth and yield were decreased the least compared with optimal, when irrigation dose was decreased to 60% together with 16 mM K. The results demonstrate that deficit irrigation strategies could be utilized to develop management practices to improve cassava productivity by means of K fertigation under low moisture conditions

Potassium Fertigation With Deficit Irrigation Improves the Nutritive Quality of Cassava

Water deficit limits cassava (Manihot esculenta Crantz) productivity in drought-prone areas and alters the nutritive quality of the crop. Potassium (K) may mitigate the effects of water deficit and improve the nutritional content of cassava, which would alleviate malnutrition among the human population in the tropics who depend on cassava as a staple food. Pot experiments were conducted under controlled glasshouse conditions to investigate the influence of deficit irrigation and K fertigation on the nutritive and anti-nutritive quality of biofortified cassava during the early growth phase. Treatments initiated at 30 days after planting were three irrigation doses (30, 60, 100% pot capacity) that were split to five K (0.01, 1, 4, 16, and 32 mM) concentrations. Plants were harvested at 90 days after planting, and the starch, energy, carotenoid, crude protein, fiber, minerals, and cyanide concentration of the leaves and roots were determined. Irrigation and K treatments showed significant (P <0.05) interactions for starch, carotenoid, energy, and cyanide concentration. An irrigation dose of 30% together with 0.01 mM K resulted in the lowest starch, carotenoid, energy, and fiber content, but highest cyanide concentration, relative to full-irrigated (100%) plants together with 16 mM K. When the K application rate was 16 mM the best nutritional quality was obtained, with the lowest cyanide concentration, regardless of irrigation dose. Moreover, nutritional traits showed strong positive associations, whereas cyanide concentration correlated negatively with all the nutritional traits. Notably, an irrigation dose of 60% together with 16 mM K reduced the nutritional content the least and showed minimal increase in cyanide concentration. The results indicate that K fertigation with adjusted irrigation may improve the dietary quality of young cassava and reduce antinutrients, which could enhance the nutrient bioavailability of cassava grown in drought-prone areas.Peer reviewe

Red-Green-Blue and Multispectral Imaging as Potential Tools for Estimating Growth and Nutritional Performance of Cassava under Deficit Irrigation and Potassium Fertigation

Cassava has high energy value and rich nutritional content, yet its productivity in the tropics is seriously constrained by abiotic stresses such as water deficit and low potassium (K) nutrition. Systems that allow evaluation of genotypes in the field and greenhouse for nondestructive estimation of plant performance would be useful means for monitoring the health of plants for crop-management decisions. We investigated whether the red–green–blue (RGB) and multispectral images could be used to detect the previsual effects of water deficit and low K in cassava, and whether the crop quality changes due to low moisture and low K could be observed from the images. Pot experiments were conducted with cassava cuttings. The experimental design was a split-plot arranged in a completely randomized design. Treatments were three irrigation doses split into various K rates. Plant images were captured beginning 30 days after planting (DAP) and ended at 90 DAP when plants were harvested. Results show that biomass, chlorophyll, and net photosynthesis were estimated with the highest accuracy (R2 = 0.90), followed by leaf area (R2 = 0.76). Starch, energy, carotenoid, and cyanide were also estimated satisfactorily (R2 > 0.80), although cyanide showed negative regression coefficients. All mineral elements showed lower estimation accuracy (R2 = 0.14–0.48) and exhibited weak associations with the spectral indices. Use of the normalized difference vegetation index (NDVI), green area (GA), and simple ratio (SR) indices allowed better estimation of growth and key nutritional traits. Irrigation dose 30% of pot capacity enriched with 0.01 mM K reduced most index values but increased the crop senescence index (CSI). Increasing K to 16 mM over the irrigation doses resulted in high index values, but low CSI. The findings indicate that RGB and multispectral imaging can provide indirect measurements of growth and key nutritional traits in cassava. Hence, they can be used as a tool in various breeding programs to facilitate cultivar evaluation and support management decisions to avert stress, such as the decision to irrigate or apply fertilizers

Red-Green-Blue and Multispectral Imaging as Potential Tools for Estimating Growth and Nutritional Performance of Cassava under Deficit Irrigation and Potassium Fertigation

Cassava has high energy value and rich nutritional content, yet its productivity in the tropics is seriously constrained by abiotic stresses such as water deficit and low potassium (K) nutrition. Systems that allow evaluation of genotypes in the field and greenhouse for nondestructive estimation of plant performance would be useful means for monitoring the health of plants for crop-management decisions. We investigated whether the red–green–blue (RGB) and multispectral images could be used to detect the previsual effects of water deficit and low K in cassava, and whether the crop quality changes due to low moisture and low K could be observed from the images. Pot experiments were conducted with cassava cuttings. The experimental design was a split-plot arranged in a completely randomized design. Treatments were three irrigation doses split into various K rates. Plant images were captured beginning 30 days after planting (DAP) and ended at 90 DAP when plants were harvested. Results show that biomass, chlorophyll, and net photosynthesis were estimated with the highest accuracy (R2 = 0.90), followed by leaf area (R2 = 0.76). Starch, energy, carotenoid, and cyanide were also estimated satisfactorily (R2 > 0.80), although cyanide showed negative regression coefficients. All mineral elements showed lower estimation accuracy (R2 = 0.14–0.48) and exhibited weak associations with the spectral indices. Use of the normalized difference vegetation index (NDVI), green area (GA), and simple ratio (SR) indices allowed better estimation of growth and key nutritional traits. Irrigation dose 30% of pot capacity enriched with 0.01 mM K reduced most index values but increased the crop senescence index (CSI). Increasing K to 16 mM over the irrigation doses resulted in high index values, but low CSI. The findings indicate that RGB and multispectral imaging can provide indirect measurements of growth and key nutritional traits in cassava. Hence, they can be used as a tool in various breeding programs to facilitate cultivar evaluation and support management decisions to avert stress, such as the decision to irrigate or apply fertilizers

Viherlannoitusopas

Denna guide behandlar möjligheterna att använda gröngödsling för att förbättra markkvaliteten. En gröngödslingsvall är ett bra alternativ för växelbruk av gräsvallar också på gårdar som inte annars odlar gräsvall. Frågor kring hur man grundar, sköter och avslutar en gräsvall åskådliggörs med exempel. Dessutom beskrivs ekonomiska kalkyler som beskriver skillnaderna i gräsvallens avkastning och kostnader jämfört med flerårig odling eller monokultur. Denna guide är en del av materialet som TEHO Plus-projektet producerat för jordbrukare och rådgivare och den kompletterar Gårdens miljöhandbok som projektet utarbetat.Tässä oppaassa käsitellään mahdollisuuksia käyttää viherlannoitusnurmea maan kasvukunnon parantamiseen. Viherlannoitusnurmi on hyvä vaihtoehto saada nurmea viljelykiertoon myös tiloilla, jotka eivät muuten viljele nurmea. Nurmen perustamiseen, hoitoon ja lopettamiseen liittyviä asioita havainnollistetaan esimerkeillä. Lisäksi käydään läpi talouslaskelmia, jotka kertovat viherlannoitusnurmen tuotto- ja kustannuseroista verrattuna saman kasvilajin jatkuvaan viljelyyn eli monokulttuuriin. Tämä opas on osa TEHO Plus -hankkeen tuottamaa materiaalia viljelijöiden ja neuvojien käyttöön, mikä täydentää hankkeen laatimaa Maatilan ympäristökäsikirjaa